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<h1><a href="dlp_v2.html">Cloud Data Loss Prevention (DLP) API</a> . <a href="dlp_v2.projects.html">projects</a> . <a href="dlp_v2.projects.dlpJobs.html">dlpJobs</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#cancel">cancel(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Starts asynchronous cancellation on a long-running DlpJob. The server makes a best effort to cancel the DlpJob, but success is not guaranteed. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.</p>
<p class="toc_element">
  <code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
  <code><a href="#create">create(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a new job to inspect storage or calculate risk metrics. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more. When no InfoTypes or CustomInfoTypes are specified in inspect jobs, the system will automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated.</p>
<p class="toc_element">
  <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes a long-running DlpJob. This method indicates that the client is no longer interested in the DlpJob result. The job will be cancelled if possible. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.</p>
<p class="toc_element">
  <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets the latest state of a long-running DlpJob. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.</p>
<p class="toc_element">
  <code><a href="#list">list(parent, filter=None, locationId=None, orderBy=None, pageSize=None, pageToken=None, type=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists DlpJobs that match the specified filter in the request. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.</p>
<p class="toc_element">
  <code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="cancel">cancel(name, body=None, x__xgafv=None)</code>
  <pre>Starts asynchronous cancellation on a long-running DlpJob. The server makes a best effort to cancel the DlpJob, but success is not guaranteed. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.

Args:
  name: string, Required. The name of the DlpJob resource to be cancelled. (required)
  body: object, The request body.
    The object takes the form of:

{ # The request message for canceling a DLP job.
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`.
}</pre>
</div>

<div class="method">
    <code class="details" id="close">close()</code>
  <pre>Close httplib2 connections.</pre>
</div>

<div class="method">
    <code class="details" id="create">create(parent, body=None, x__xgafv=None)</code>
  <pre>Creates a new job to inspect storage or calculate risk metrics. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more. When no InfoTypes or CustomInfoTypes are specified in inspect jobs, the system will automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated.

Args:
  parent: string, Required. Parent resource name. The format of this value varies depending on whether you have [specified a processing location](https://cloud.google.com/dlp/docs/specifying-location): + Projects scope, location specified: `projects/`PROJECT_ID`/locations/`LOCATION_ID + Projects scope, no location specified (defaults to global): `projects/`PROJECT_ID The following example `parent` string specifies a parent project with the identifier `example-project`, and specifies the `europe-west3` location for processing data: parent=projects/example-project/locations/europe-west3 (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for CreateDlpJobRequest. Used to initiate long running jobs such as calculating risk metrics or inspecting Google Cloud Storage.
  &quot;inspectJob&quot;: { # Controls what and how to inspect for findings. # An inspection job scans a storage repository for InfoTypes.
    &quot;actions&quot;: [ # Actions to execute at the completion of the job.
      { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
        &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
        },
        &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
          &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
        },
        &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
        },
        &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
        },
        &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
        },
        &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
          &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
            &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
      },
    ],
    &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
      &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
        &quot;A String&quot;,
      ],
      &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
        { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
          &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
            { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                },
              },
            },
          ],
          &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
            &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
              &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
            },
            &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
              &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                &quot;A String&quot;,
              ],
            },
          },
          &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
          &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
          },
          &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
          &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
            &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
              42,
            ],
            &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
          },
          &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
            &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
            &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
          },
          &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
          },
        },
      ],
      &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
      &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
      &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
        { # Type of information detected by the API.
          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
        },
      ],
      &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
        &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
          { # Max findings configuration per infoType, per content item or long running DlpJob.
            &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
            &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
          },
        ],
        &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
        &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
      },
      &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
      &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
        { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
          &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          ],
          &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
            { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
              &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                  &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                    &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                  },
                  &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                    &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                      &quot;A String&quot;,
                    ],
                  },
                },
                &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                  &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                    { # Type of information detected by the API.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                  ],
                },
                &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
              },
              &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                  &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                    42,
                  ],
                  &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                },
                &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                  &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                  &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                },
                &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                  &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                  &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                },
              },
            },
          ],
        },
      ],
    },
    &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
    &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
      &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
        &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
        &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
        &quot;sampleMethod&quot;: &quot;A String&quot;,
        &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
      &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Google Cloud Storage bucket. # Google Cloud Storage options.
        &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
        &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
        &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
          &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
            &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
            &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
            &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
              &quot;A String&quot;,
            ],
          },
          &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
        },
        &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
          &quot;A String&quot;,
        ],
        &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
        &quot;sampleMethod&quot;: &quot;A String&quot;,
      },
      &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
        &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
          &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
        },
        &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
          &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
          &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
        },
      },
      &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
        &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
        &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
          &quot;a_key&quot;: &quot;A String&quot;,
        },
        &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
          &quot;A String&quot;,
        ],
        &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
          &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
            { # General identifier of a data field in a storage service.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          ],
        },
      },
      &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Google Cloud Storage and BigQuery.
        &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger.
        &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
        &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
        &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. For BigQuery: If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. For Datastore: If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
  },
  &quot;jobId&quot;: &quot;A String&quot;, # The job id can contain uppercase and lowercase letters, numbers, and hyphens; that is, it must match the regular expression: `[a-zA-Z\d-_]+`. The maximum length is 100 characters. Can be empty to allow the system to generate one.
  &quot;locationId&quot;: &quot;A String&quot;, # Deprecated. This field has no effect.
  &quot;riskJob&quot;: { # Configuration for a risk analysis job. See https://cloud.google.com/dlp/docs/concepts-risk-analysis to learn more. # A risk analysis job calculates re-identification risk metrics for a BigQuery table.
    &quot;actions&quot;: [ # Actions to execute at the completion of the job. Are executed in the order provided.
      { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
        &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
        },
        &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
          &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
        },
        &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
        },
        &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
        },
        &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
        },
        &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
          &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
            &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
      },
    ],
    &quot;privacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
      &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
        &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
      &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
        &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
          { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
            &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
              { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            ],
            &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        ],
        &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
          { # A column with a semantic tag attached.
            &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
            },
            &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          },
        ],
        &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
      },
      &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
        &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
          &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        },
        &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
      },
      &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
        &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
          { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
            &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
              { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            ],
            &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        ],
        &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
          { # A column with a semantic tag attached.
            &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
            },
            &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          },
        ],
        &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
      },
      &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
        &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
      &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
        &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
    &quot;sourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
    },
  },
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Combines all of the information about a DLP job.
  &quot;createTime&quot;: &quot;A String&quot;, # Time when the job was created.
  &quot;endTime&quot;: &quot;A String&quot;, # Time when the job finished.
  &quot;errors&quot;: [ # A stream of errors encountered running the job.
    { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
      &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;timestamps&quot;: [ # The times the error occurred.
        &quot;A String&quot;,
      ],
    },
  ],
  &quot;inspectDetails&quot;: { # The results of an inspect DataSource job. # Results from inspecting a data source.
    &quot;requestedOptions&quot;: { # Snapshot of the inspection configuration. # The configuration used for this job.
      &quot;jobConfig&quot;: { # Controls what and how to inspect for findings. # Inspect config.
        &quot;actions&quot;: [ # Actions to execute at the completion of the job.
          { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
            &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
            },
            &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
              &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
            },
            &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
            },
            &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
            },
            &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
            },
            &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
              &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            },
          },
        ],
        &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
          &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
            &quot;A String&quot;,
          ],
          &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
            { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
              &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
              &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                  &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                },
                &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                  &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                    &quot;A String&quot;,
                  ],
                },
              },
              &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
              &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
              },
              &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
              &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                  42,
                ],
                &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
              },
              &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
              },
              &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
              },
            },
          ],
          &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
          &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
          &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          ],
          &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
            &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
              { # Max findings configuration per infoType, per content item or long running DlpJob.
                &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
                &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
              },
            ],
            &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
            &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
          &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
            { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
              &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              ],
              &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                  &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                    &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                      &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                        &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                      },
                      &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                        &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                          &quot;A String&quot;,
                        ],
                      },
                    },
                    &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                      &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                        { # Type of information detected by the API.
                          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                        },
                      ],
                    },
                    &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                    &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                  },
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
            },
          ],
        },
        &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
        &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
          &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
            &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
            &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
            &quot;sampleMethod&quot;: &quot;A String&quot;,
            &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
          &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Google Cloud Storage bucket. # Google Cloud Storage options.
            &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
            &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
            &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
              &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
                &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
                &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                  &quot;A String&quot;,
                ],
                &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                  &quot;A String&quot;,
                ],
              },
              &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
            },
            &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
              &quot;A String&quot;,
            ],
            &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
            &quot;sampleMethod&quot;: &quot;A String&quot;,
          },
          &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
            &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
              &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
            },
            &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
              &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
              &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
            },
          },
          &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
            &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
            &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
              &quot;a_key&quot;: &quot;A String&quot;,
            },
            &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
              &quot;A String&quot;,
            ],
            &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
              &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
                { # General identifier of a data field in a storage service.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              ],
            },
          },
          &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Google Cloud Storage and BigQuery.
            &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger.
            &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
            &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
            &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. For BigQuery: If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. For Datastore: If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
        },
      },
      &quot;snapshotInspectTemplate&quot;: { # The inspectTemplate contains a configuration (set of types of sensitive data to be detected) to be used anywhere you otherwise would normally specify InspectConfig. See https://cloud.google.com/dlp/docs/concepts-templates to learn more. # If run with an InspectTemplate, a snapshot of its state at the time of this run.
        &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of an inspectTemplate.
        &quot;description&quot;: &quot;A String&quot;, # Short description (max 256 chars).
        &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 256 chars).
        &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # The core content of the template. Configuration of the scanning process.
          &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
            &quot;A String&quot;,
          ],
          &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
            { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
              &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
              &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                  &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                },
                &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                  &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                    &quot;A String&quot;,
                  ],
                },
              },
              &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
              &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
              },
              &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
              &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                  42,
                ],
                &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
              },
              &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
              },
              &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
              },
            },
          ],
          &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
          &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
          &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          ],
          &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
            &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
              { # Max findings configuration per infoType, per content item or long running DlpJob.
                &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
                &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
              },
            ],
            &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
            &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
          &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
            { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
              &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              ],
              &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                  &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                    &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                      &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                        &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                      },
                      &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                        &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                          &quot;A String&quot;,
                        ],
                      },
                    },
                    &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                      &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                        { # Type of information detected by the API.
                          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                        },
                      ],
                    },
                    &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                    &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                  },
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
            },
          ],
        },
        &quot;name&quot;: &quot;A String&quot;, # Output only. The template name. The template will have one of the following formats: `projects/PROJECT_ID/inspectTemplates/TEMPLATE_ID` OR `organizations/ORGANIZATION_ID/inspectTemplates/TEMPLATE_ID`;
        &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of an inspectTemplate.
      },
    },
    &quot;result&quot;: { # All result fields mentioned below are updated while the job is processing. # A summary of the outcome of this inspection job.
      &quot;hybridStats&quot;: { # Statistics related to processing hybrid inspect requests. # Statistics related to the processing of hybrid inspect.
        &quot;abortedCount&quot;: &quot;A String&quot;, # The number of hybrid inspection requests aborted because the job ran out of quota or was ended before they could be processed.
        &quot;pendingCount&quot;: &quot;A String&quot;, # The number of hybrid requests currently being processed. Only populated when called via method `getDlpJob`. A burst of traffic may cause hybrid inspect requests to be enqueued. Processing will take place as quickly as possible, but resource limitations may impact how long a request is enqueued for.
        &quot;processedCount&quot;: &quot;A String&quot;, # The number of hybrid inspection requests processed within this job.
      },
      &quot;infoTypeStats&quot;: [ # Statistics of how many instances of each info type were found during inspect job.
        { # Statistics regarding a specific InfoType.
          &quot;count&quot;: &quot;A String&quot;, # Number of findings for this infoType.
          &quot;infoType&quot;: { # Type of information detected by the API. # The type of finding this stat is for.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
          },
        },
      ],
      &quot;processedBytes&quot;: &quot;A String&quot;, # Total size in bytes that were processed.
      &quot;totalEstimatedBytes&quot;: &quot;A String&quot;, # Estimate of the number of bytes to process.
    },
  },
  &quot;jobTriggerName&quot;: &quot;A String&quot;, # If created by a job trigger, the resource name of the trigger that instantiated the job.
  &quot;name&quot;: &quot;A String&quot;, # The server-assigned name.
  &quot;riskDetails&quot;: { # Result of a risk analysis operation request. # Results from analyzing risk of a data source.
    &quot;categoricalStatsResult&quot;: { # Result of the categorical stats computation. # Categorical stats result
      &quot;valueFrequencyHistogramBuckets&quot;: [ # Histogram of value frequencies in the column.
        { # Histogram of value frequencies in the column.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of values in this bucket.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct values in this bucket.
          &quot;bucketValues&quot;: [ # Sample of value frequencies in this bucket. The total number of values returned per bucket is capped at 20.
            { # A value of a field, including its frequency.
              &quot;count&quot;: &quot;A String&quot;, # How many times the value is contained in the field.
              &quot;value&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # A value contained in the field in question.
                &quot;booleanValue&quot;: True or False, # boolean
                &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                  &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                  &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                  &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                },
                &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                &quot;floatValue&quot;: 3.14, # float
                &quot;integerValue&quot;: &quot;A String&quot;, # integer
                &quot;stringValue&quot;: &quot;A String&quot;, # string
                &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                  &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                  &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                  &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                  &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                },
                &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
              },
            },
          ],
          &quot;valueFrequencyLowerBound&quot;: &quot;A String&quot;, # Lower bound on the value frequency of the values in this bucket.
          &quot;valueFrequencyUpperBound&quot;: &quot;A String&quot;, # Upper bound on the value frequency of the values in this bucket.
        },
      ],
    },
    &quot;deltaPresenceEstimationResult&quot;: { # Result of the δ-presence computation. Note that these results are an estimation, not exact values. # Delta-presence result
      &quot;deltaPresenceEstimationHistogram&quot;: [ # The intervals [min_probability, max_probability) do not overlap. If a value doesn&#x27;t correspond to any such interval, the associated frequency is zero. For example, the following records: {min_probability: 0, max_probability: 0.1, frequency: 17} {min_probability: 0.2, max_probability: 0.3, frequency: 42} {min_probability: 0.3, max_probability: 0.4, frequency: 99} mean that there are no record with an estimated probability in [0.1, 0.2) nor larger or equal to 0.4.
        { # A DeltaPresenceEstimationHistogramBucket message with the following values: min_probability: 0.1 max_probability: 0.2 frequency: 42 means that there are 42 records for which δ is in [0.1, 0.2). An important particular case is when min_probability = max_probability = 1: then, every individual who shares this quasi-identifier combination is in the dataset.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Number of records within these probability bounds.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct quasi-identifier tuple values in this bucket.
          &quot;bucketValues&quot;: [ # Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20.
            { # A tuple of values for the quasi-identifier columns.
              &quot;estimatedProbability&quot;: 3.14, # The estimated probability that a given individual sharing these quasi-identifier values is in the dataset. This value, typically called δ, is the ratio between the number of records in the dataset with these quasi-identifier values, and the total number of individuals (inside *and* outside the dataset) with these quasi-identifier values. For example, if there are 15 individuals in the dataset who share the same quasi-identifier values, and an estimated 100 people in the entire population with these values, then δ is 0.15.
              &quot;quasiIdsValues&quot;: [ # The quasi-identifier values.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
            },
          ],
          &quot;maxProbability&quot;: 3.14, # Always greater than or equal to min_probability.
          &quot;minProbability&quot;: 3.14, # Between 0 and 1.
        },
      ],
    },
    &quot;kAnonymityResult&quot;: { # Result of the k-anonymity computation. # K-anonymity result
      &quot;equivalenceClassHistogramBuckets&quot;: [ # Histogram of k-anonymity equivalence classes.
        { # Histogram of k-anonymity equivalence classes.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of equivalence classes in this bucket.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct equivalence classes in this bucket.
          &quot;bucketValues&quot;: [ # Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20.
            { # The set of columns&#x27; values that share the same ldiversity value
              &quot;equivalenceClassSize&quot;: &quot;A String&quot;, # Size of the equivalence class, for example number of rows with the above set of values.
              &quot;quasiIdsValues&quot;: [ # Set of values defining the equivalence class. One value per quasi-identifier column in the original KAnonymity metric message. The order is always the same as the original request.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
            },
          ],
          &quot;equivalenceClassSizeLowerBound&quot;: &quot;A String&quot;, # Lower bound on the size of the equivalence classes in this bucket.
          &quot;equivalenceClassSizeUpperBound&quot;: &quot;A String&quot;, # Upper bound on the size of the equivalence classes in this bucket.
        },
      ],
    },
    &quot;kMapEstimationResult&quot;: { # Result of the reidentifiability analysis. Note that these results are an estimation, not exact values. # K-map result
      &quot;kMapEstimationHistogram&quot;: [ # The intervals [min_anonymity, max_anonymity] do not overlap. If a value doesn&#x27;t correspond to any such interval, the associated frequency is zero. For example, the following records: {min_anonymity: 1, max_anonymity: 1, frequency: 17} {min_anonymity: 2, max_anonymity: 3, frequency: 42} {min_anonymity: 5, max_anonymity: 10, frequency: 99} mean that there are no record with an estimated anonymity of 4, 5, or larger than 10.
        { # A KMapEstimationHistogramBucket message with the following values: min_anonymity: 3 max_anonymity: 5 frequency: 42 means that there are 42 records whose quasi-identifier values correspond to 3, 4 or 5 people in the overlying population. An important particular case is when min_anonymity = max_anonymity = 1: the frequency field then corresponds to the number of uniquely identifiable records.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Number of records within these anonymity bounds.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct quasi-identifier tuple values in this bucket.
          &quot;bucketValues&quot;: [ # Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20.
            { # A tuple of values for the quasi-identifier columns.
              &quot;estimatedAnonymity&quot;: &quot;A String&quot;, # The estimated anonymity for these quasi-identifier values.
              &quot;quasiIdsValues&quot;: [ # The quasi-identifier values.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
            },
          ],
          &quot;maxAnonymity&quot;: &quot;A String&quot;, # Always greater than or equal to min_anonymity.
          &quot;minAnonymity&quot;: &quot;A String&quot;, # Always positive.
        },
      ],
    },
    &quot;lDiversityResult&quot;: { # Result of the l-diversity computation. # L-divesity result
      &quot;sensitiveValueFrequencyHistogramBuckets&quot;: [ # Histogram of l-diversity equivalence class sensitive value frequencies.
        { # Histogram of l-diversity equivalence class sensitive value frequencies.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of equivalence classes in this bucket.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct equivalence classes in this bucket.
          &quot;bucketValues&quot;: [ # Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20.
            { # The set of columns&#x27; values that share the same ldiversity value.
              &quot;equivalenceClassSize&quot;: &quot;A String&quot;, # Size of the k-anonymity equivalence class.
              &quot;numDistinctSensitiveValues&quot;: &quot;A String&quot;, # Number of distinct sensitive values in this equivalence class.
              &quot;quasiIdsValues&quot;: [ # Quasi-identifier values defining the k-anonymity equivalence class. The order is always the same as the original request.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
              &quot;topSensitiveValues&quot;: [ # Estimated frequencies of top sensitive values.
                { # A value of a field, including its frequency.
                  &quot;count&quot;: &quot;A String&quot;, # How many times the value is contained in the field.
                  &quot;value&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # A value contained in the field in question.
                    &quot;booleanValue&quot;: True or False, # boolean
                    &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                      &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                      &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                      &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                    },
                    &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                    &quot;floatValue&quot;: 3.14, # float
                    &quot;integerValue&quot;: &quot;A String&quot;, # integer
                    &quot;stringValue&quot;: &quot;A String&quot;, # string
                    &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                      &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                      &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                      &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                      &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                    },
                    &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                  },
                },
              ],
            },
          ],
          &quot;sensitiveValueFrequencyLowerBound&quot;: &quot;A String&quot;, # Lower bound on the sensitive value frequencies of the equivalence classes in this bucket.
          &quot;sensitiveValueFrequencyUpperBound&quot;: &quot;A String&quot;, # Upper bound on the sensitive value frequencies of the equivalence classes in this bucket.
        },
      ],
    },
    &quot;numericalStatsResult&quot;: { # Result of the numerical stats computation. # Numerical stats result
      &quot;maxValue&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # Maximum value appearing in the column.
        &quot;booleanValue&quot;: True or False, # boolean
        &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
          &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
          &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
          &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
        },
        &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
        &quot;floatValue&quot;: 3.14, # float
        &quot;integerValue&quot;: &quot;A String&quot;, # integer
        &quot;stringValue&quot;: &quot;A String&quot;, # string
        &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
          &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
          &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
          &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
          &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
        },
        &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
      },
      &quot;minValue&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # Minimum value appearing in the column.
        &quot;booleanValue&quot;: True or False, # boolean
        &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
          &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
          &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
          &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
        },
        &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
        &quot;floatValue&quot;: 3.14, # float
        &quot;integerValue&quot;: &quot;A String&quot;, # integer
        &quot;stringValue&quot;: &quot;A String&quot;, # string
        &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
          &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
          &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
          &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
          &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
        },
        &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
      },
      &quot;quantileValues&quot;: [ # List of 99 values that partition the set of field values into 100 equal sized buckets.
        { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
          &quot;booleanValue&quot;: True or False, # boolean
          &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
            &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
            &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
            &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
          },
          &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
          &quot;floatValue&quot;: 3.14, # float
          &quot;integerValue&quot;: &quot;A String&quot;, # integer
          &quot;stringValue&quot;: &quot;A String&quot;, # string
          &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
            &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
            &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
            &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
            &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
          },
          &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
        },
      ],
    },
    &quot;requestedOptions&quot;: { # Risk analysis options. # The configuration used for this job.
      &quot;jobConfig&quot;: { # Configuration for a risk analysis job. See https://cloud.google.com/dlp/docs/concepts-risk-analysis to learn more. # The job config for the risk job.
        &quot;actions&quot;: [ # Actions to execute at the completion of the job. Are executed in the order provided.
          { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
            &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
            },
            &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
              &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
            },
            &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
            },
            &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
            },
            &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
            },
            &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
              &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            },
          },
        ],
        &quot;privacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
          &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
          &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
            &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
              { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                  { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                    &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  },
                ],
                &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            ],
            &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
              { # A column with a semantic tag attached.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                },
                &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              },
            ],
            &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
          },
          &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
            &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
              &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            },
            &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
          },
          &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
            &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
              { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                  { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                    &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  },
                ],
                &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            ],
            &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
              { # A column with a semantic tag attached.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                },
                &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              },
            ],
            &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
          },
          &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
            &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
          &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
        },
        &quot;sourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
    },
    &quot;requestedPrivacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
      &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
        &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
      &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
        &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
          { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
            &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
              { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            ],
            &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        ],
        &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
          { # A column with a semantic tag attached.
            &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
            },
            &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          },
        ],
        &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
      },
      &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
        &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
          &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        },
        &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
      },
      &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
        &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
          { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
            &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
              { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            ],
            &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        ],
        &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
          { # A column with a semantic tag attached.
            &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
            },
            &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          },
        ],
        &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
      },
      &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
        &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
      &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
        &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
    &quot;requestedSourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
    },
  },
  &quot;startTime&quot;: &quot;A String&quot;, # Time when the job started.
  &quot;state&quot;: &quot;A String&quot;, # State of a job.
  &quot;type&quot;: &quot;A String&quot;, # The type of job.
}</pre>
</div>

<div class="method">
    <code class="details" id="delete">delete(name, x__xgafv=None)</code>
  <pre>Deletes a long-running DlpJob. This method indicates that the client is no longer interested in the DlpJob result. The job will be cancelled if possible. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.

Args:
  name: string, Required. The name of the DlpJob resource to be deleted. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`.
}</pre>
</div>

<div class="method">
    <code class="details" id="get">get(name, x__xgafv=None)</code>
  <pre>Gets the latest state of a long-running DlpJob. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.

Args:
  name: string, Required. The name of the DlpJob resource. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Combines all of the information about a DLP job.
  &quot;createTime&quot;: &quot;A String&quot;, # Time when the job was created.
  &quot;endTime&quot;: &quot;A String&quot;, # Time when the job finished.
  &quot;errors&quot;: [ # A stream of errors encountered running the job.
    { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
      &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;timestamps&quot;: [ # The times the error occurred.
        &quot;A String&quot;,
      ],
    },
  ],
  &quot;inspectDetails&quot;: { # The results of an inspect DataSource job. # Results from inspecting a data source.
    &quot;requestedOptions&quot;: { # Snapshot of the inspection configuration. # The configuration used for this job.
      &quot;jobConfig&quot;: { # Controls what and how to inspect for findings. # Inspect config.
        &quot;actions&quot;: [ # Actions to execute at the completion of the job.
          { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
            &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
            },
            &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
              &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
            },
            &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
            },
            &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
            },
            &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
            },
            &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
              &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            },
          },
        ],
        &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
          &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
            &quot;A String&quot;,
          ],
          &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
            { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
              &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
              &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                  &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                },
                &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                  &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                    &quot;A String&quot;,
                  ],
                },
              },
              &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
              &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
              },
              &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
              &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                  42,
                ],
                &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
              },
              &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
              },
              &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
              },
            },
          ],
          &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
          &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
          &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          ],
          &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
            &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
              { # Max findings configuration per infoType, per content item or long running DlpJob.
                &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
                &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
              },
            ],
            &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
            &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
          &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
            { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
              &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              ],
              &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                  &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                    &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                      &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                        &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                      },
                      &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                        &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                          &quot;A String&quot;,
                        ],
                      },
                    },
                    &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                      &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                        { # Type of information detected by the API.
                          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                        },
                      ],
                    },
                    &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                    &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                  },
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
            },
          ],
        },
        &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
        &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
          &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
            &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
            &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
            &quot;sampleMethod&quot;: &quot;A String&quot;,
            &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
          &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Google Cloud Storage bucket. # Google Cloud Storage options.
            &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
            &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
            &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
              &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
                &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
                &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                  &quot;A String&quot;,
                ],
                &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                  &quot;A String&quot;,
                ],
              },
              &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
            },
            &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
              &quot;A String&quot;,
            ],
            &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
            &quot;sampleMethod&quot;: &quot;A String&quot;,
          },
          &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
            &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
              &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
            },
            &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
              &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
              &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
            },
          },
          &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
            &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
            &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
              &quot;a_key&quot;: &quot;A String&quot;,
            },
            &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
              &quot;A String&quot;,
            ],
            &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
              &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
                { # General identifier of a data field in a storage service.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              ],
            },
          },
          &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Google Cloud Storage and BigQuery.
            &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger.
            &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
            &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
            &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. For BigQuery: If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. For Datastore: If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
        },
      },
      &quot;snapshotInspectTemplate&quot;: { # The inspectTemplate contains a configuration (set of types of sensitive data to be detected) to be used anywhere you otherwise would normally specify InspectConfig. See https://cloud.google.com/dlp/docs/concepts-templates to learn more. # If run with an InspectTemplate, a snapshot of its state at the time of this run.
        &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of an inspectTemplate.
        &quot;description&quot;: &quot;A String&quot;, # Short description (max 256 chars).
        &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 256 chars).
        &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # The core content of the template. Configuration of the scanning process.
          &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
            &quot;A String&quot;,
          ],
          &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
            { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
              &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
              &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                  &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                },
                &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                  &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                    &quot;A String&quot;,
                  ],
                },
              },
              &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
              &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
              },
              &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
              &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                  42,
                ],
                &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
              },
              &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
              },
              &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
              },
            },
          ],
          &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
          &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
          &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
            { # Type of information detected by the API.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          ],
          &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
            &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
              { # Max findings configuration per infoType, per content item or long running DlpJob.
                &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
                &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
              },
            ],
            &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
            &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
          },
          &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
          &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
            { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
              &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              ],
              &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                  &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                    &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                      &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                        &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                      },
                      &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                        &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                          &quot;A String&quot;,
                        ],
                      },
                    },
                    &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                      &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                        { # Type of information detected by the API.
                          &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                        },
                      ],
                    },
                    &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                    &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                  },
                  &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                    &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                      &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                        42,
                      ],
                      &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                    },
                    &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                      &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                      &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                    },
                    &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                      &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                      &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                    },
                  },
                },
              ],
            },
          ],
        },
        &quot;name&quot;: &quot;A String&quot;, # Output only. The template name. The template will have one of the following formats: `projects/PROJECT_ID/inspectTemplates/TEMPLATE_ID` OR `organizations/ORGANIZATION_ID/inspectTemplates/TEMPLATE_ID`;
        &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of an inspectTemplate.
      },
    },
    &quot;result&quot;: { # All result fields mentioned below are updated while the job is processing. # A summary of the outcome of this inspection job.
      &quot;hybridStats&quot;: { # Statistics related to processing hybrid inspect requests. # Statistics related to the processing of hybrid inspect.
        &quot;abortedCount&quot;: &quot;A String&quot;, # The number of hybrid inspection requests aborted because the job ran out of quota or was ended before they could be processed.
        &quot;pendingCount&quot;: &quot;A String&quot;, # The number of hybrid requests currently being processed. Only populated when called via method `getDlpJob`. A burst of traffic may cause hybrid inspect requests to be enqueued. Processing will take place as quickly as possible, but resource limitations may impact how long a request is enqueued for.
        &quot;processedCount&quot;: &quot;A String&quot;, # The number of hybrid inspection requests processed within this job.
      },
      &quot;infoTypeStats&quot;: [ # Statistics of how many instances of each info type were found during inspect job.
        { # Statistics regarding a specific InfoType.
          &quot;count&quot;: &quot;A String&quot;, # Number of findings for this infoType.
          &quot;infoType&quot;: { # Type of information detected by the API. # The type of finding this stat is for.
            &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
          },
        },
      ],
      &quot;processedBytes&quot;: &quot;A String&quot;, # Total size in bytes that were processed.
      &quot;totalEstimatedBytes&quot;: &quot;A String&quot;, # Estimate of the number of bytes to process.
    },
  },
  &quot;jobTriggerName&quot;: &quot;A String&quot;, # If created by a job trigger, the resource name of the trigger that instantiated the job.
  &quot;name&quot;: &quot;A String&quot;, # The server-assigned name.
  &quot;riskDetails&quot;: { # Result of a risk analysis operation request. # Results from analyzing risk of a data source.
    &quot;categoricalStatsResult&quot;: { # Result of the categorical stats computation. # Categorical stats result
      &quot;valueFrequencyHistogramBuckets&quot;: [ # Histogram of value frequencies in the column.
        { # Histogram of value frequencies in the column.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of values in this bucket.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct values in this bucket.
          &quot;bucketValues&quot;: [ # Sample of value frequencies in this bucket. The total number of values returned per bucket is capped at 20.
            { # A value of a field, including its frequency.
              &quot;count&quot;: &quot;A String&quot;, # How many times the value is contained in the field.
              &quot;value&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # A value contained in the field in question.
                &quot;booleanValue&quot;: True or False, # boolean
                &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                  &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                  &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                  &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                },
                &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                &quot;floatValue&quot;: 3.14, # float
                &quot;integerValue&quot;: &quot;A String&quot;, # integer
                &quot;stringValue&quot;: &quot;A String&quot;, # string
                &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                  &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                  &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                  &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                  &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                },
                &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
              },
            },
          ],
          &quot;valueFrequencyLowerBound&quot;: &quot;A String&quot;, # Lower bound on the value frequency of the values in this bucket.
          &quot;valueFrequencyUpperBound&quot;: &quot;A String&quot;, # Upper bound on the value frequency of the values in this bucket.
        },
      ],
    },
    &quot;deltaPresenceEstimationResult&quot;: { # Result of the δ-presence computation. Note that these results are an estimation, not exact values. # Delta-presence result
      &quot;deltaPresenceEstimationHistogram&quot;: [ # The intervals [min_probability, max_probability) do not overlap. If a value doesn&#x27;t correspond to any such interval, the associated frequency is zero. For example, the following records: {min_probability: 0, max_probability: 0.1, frequency: 17} {min_probability: 0.2, max_probability: 0.3, frequency: 42} {min_probability: 0.3, max_probability: 0.4, frequency: 99} mean that there are no record with an estimated probability in [0.1, 0.2) nor larger or equal to 0.4.
        { # A DeltaPresenceEstimationHistogramBucket message with the following values: min_probability: 0.1 max_probability: 0.2 frequency: 42 means that there are 42 records for which δ is in [0.1, 0.2). An important particular case is when min_probability = max_probability = 1: then, every individual who shares this quasi-identifier combination is in the dataset.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Number of records within these probability bounds.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct quasi-identifier tuple values in this bucket.
          &quot;bucketValues&quot;: [ # Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20.
            { # A tuple of values for the quasi-identifier columns.
              &quot;estimatedProbability&quot;: 3.14, # The estimated probability that a given individual sharing these quasi-identifier values is in the dataset. This value, typically called δ, is the ratio between the number of records in the dataset with these quasi-identifier values, and the total number of individuals (inside *and* outside the dataset) with these quasi-identifier values. For example, if there are 15 individuals in the dataset who share the same quasi-identifier values, and an estimated 100 people in the entire population with these values, then δ is 0.15.
              &quot;quasiIdsValues&quot;: [ # The quasi-identifier values.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
            },
          ],
          &quot;maxProbability&quot;: 3.14, # Always greater than or equal to min_probability.
          &quot;minProbability&quot;: 3.14, # Between 0 and 1.
        },
      ],
    },
    &quot;kAnonymityResult&quot;: { # Result of the k-anonymity computation. # K-anonymity result
      &quot;equivalenceClassHistogramBuckets&quot;: [ # Histogram of k-anonymity equivalence classes.
        { # Histogram of k-anonymity equivalence classes.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of equivalence classes in this bucket.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct equivalence classes in this bucket.
          &quot;bucketValues&quot;: [ # Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20.
            { # The set of columns&#x27; values that share the same ldiversity value
              &quot;equivalenceClassSize&quot;: &quot;A String&quot;, # Size of the equivalence class, for example number of rows with the above set of values.
              &quot;quasiIdsValues&quot;: [ # Set of values defining the equivalence class. One value per quasi-identifier column in the original KAnonymity metric message. The order is always the same as the original request.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
            },
          ],
          &quot;equivalenceClassSizeLowerBound&quot;: &quot;A String&quot;, # Lower bound on the size of the equivalence classes in this bucket.
          &quot;equivalenceClassSizeUpperBound&quot;: &quot;A String&quot;, # Upper bound on the size of the equivalence classes in this bucket.
        },
      ],
    },
    &quot;kMapEstimationResult&quot;: { # Result of the reidentifiability analysis. Note that these results are an estimation, not exact values. # K-map result
      &quot;kMapEstimationHistogram&quot;: [ # The intervals [min_anonymity, max_anonymity] do not overlap. If a value doesn&#x27;t correspond to any such interval, the associated frequency is zero. For example, the following records: {min_anonymity: 1, max_anonymity: 1, frequency: 17} {min_anonymity: 2, max_anonymity: 3, frequency: 42} {min_anonymity: 5, max_anonymity: 10, frequency: 99} mean that there are no record with an estimated anonymity of 4, 5, or larger than 10.
        { # A KMapEstimationHistogramBucket message with the following values: min_anonymity: 3 max_anonymity: 5 frequency: 42 means that there are 42 records whose quasi-identifier values correspond to 3, 4 or 5 people in the overlying population. An important particular case is when min_anonymity = max_anonymity = 1: the frequency field then corresponds to the number of uniquely identifiable records.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Number of records within these anonymity bounds.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct quasi-identifier tuple values in this bucket.
          &quot;bucketValues&quot;: [ # Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20.
            { # A tuple of values for the quasi-identifier columns.
              &quot;estimatedAnonymity&quot;: &quot;A String&quot;, # The estimated anonymity for these quasi-identifier values.
              &quot;quasiIdsValues&quot;: [ # The quasi-identifier values.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
            },
          ],
          &quot;maxAnonymity&quot;: &quot;A String&quot;, # Always greater than or equal to min_anonymity.
          &quot;minAnonymity&quot;: &quot;A String&quot;, # Always positive.
        },
      ],
    },
    &quot;lDiversityResult&quot;: { # Result of the l-diversity computation. # L-divesity result
      &quot;sensitiveValueFrequencyHistogramBuckets&quot;: [ # Histogram of l-diversity equivalence class sensitive value frequencies.
        { # Histogram of l-diversity equivalence class sensitive value frequencies.
          &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of equivalence classes in this bucket.
          &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct equivalence classes in this bucket.
          &quot;bucketValues&quot;: [ # Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20.
            { # The set of columns&#x27; values that share the same ldiversity value.
              &quot;equivalenceClassSize&quot;: &quot;A String&quot;, # Size of the k-anonymity equivalence class.
              &quot;numDistinctSensitiveValues&quot;: &quot;A String&quot;, # Number of distinct sensitive values in this equivalence class.
              &quot;quasiIdsValues&quot;: [ # Quasi-identifier values defining the k-anonymity equivalence class. The order is always the same as the original request.
                { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                  &quot;booleanValue&quot;: True or False, # boolean
                  &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                    &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                    &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                    &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                  },
                  &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                  &quot;floatValue&quot;: 3.14, # float
                  &quot;integerValue&quot;: &quot;A String&quot;, # integer
                  &quot;stringValue&quot;: &quot;A String&quot;, # string
                  &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                    &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                    &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                    &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                    &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                  },
                  &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                },
              ],
              &quot;topSensitiveValues&quot;: [ # Estimated frequencies of top sensitive values.
                { # A value of a field, including its frequency.
                  &quot;count&quot;: &quot;A String&quot;, # How many times the value is contained in the field.
                  &quot;value&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # A value contained in the field in question.
                    &quot;booleanValue&quot;: True or False, # boolean
                    &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                      &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                      &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                      &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                    },
                    &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                    &quot;floatValue&quot;: 3.14, # float
                    &quot;integerValue&quot;: &quot;A String&quot;, # integer
                    &quot;stringValue&quot;: &quot;A String&quot;, # string
                    &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                      &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                      &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                      &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                      &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                    },
                    &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                  },
                },
              ],
            },
          ],
          &quot;sensitiveValueFrequencyLowerBound&quot;: &quot;A String&quot;, # Lower bound on the sensitive value frequencies of the equivalence classes in this bucket.
          &quot;sensitiveValueFrequencyUpperBound&quot;: &quot;A String&quot;, # Upper bound on the sensitive value frequencies of the equivalence classes in this bucket.
        },
      ],
    },
    &quot;numericalStatsResult&quot;: { # Result of the numerical stats computation. # Numerical stats result
      &quot;maxValue&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # Maximum value appearing in the column.
        &quot;booleanValue&quot;: True or False, # boolean
        &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
          &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
          &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
          &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
        },
        &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
        &quot;floatValue&quot;: 3.14, # float
        &quot;integerValue&quot;: &quot;A String&quot;, # integer
        &quot;stringValue&quot;: &quot;A String&quot;, # string
        &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
          &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
          &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
          &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
          &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
        },
        &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
      },
      &quot;minValue&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # Minimum value appearing in the column.
        &quot;booleanValue&quot;: True or False, # boolean
        &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
          &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
          &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
          &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
        },
        &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
        &quot;floatValue&quot;: 3.14, # float
        &quot;integerValue&quot;: &quot;A String&quot;, # integer
        &quot;stringValue&quot;: &quot;A String&quot;, # string
        &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
          &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
          &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
          &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
          &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
        },
        &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
      },
      &quot;quantileValues&quot;: [ # List of 99 values that partition the set of field values into 100 equal sized buckets.
        { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
          &quot;booleanValue&quot;: True or False, # boolean
          &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
            &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
            &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
            &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
          },
          &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
          &quot;floatValue&quot;: 3.14, # float
          &quot;integerValue&quot;: &quot;A String&quot;, # integer
          &quot;stringValue&quot;: &quot;A String&quot;, # string
          &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
            &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
            &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
            &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
            &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
          },
          &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
        },
      ],
    },
    &quot;requestedOptions&quot;: { # Risk analysis options. # The configuration used for this job.
      &quot;jobConfig&quot;: { # Configuration for a risk analysis job. See https://cloud.google.com/dlp/docs/concepts-risk-analysis to learn more. # The job config for the risk job.
        &quot;actions&quot;: [ # Actions to execute at the completion of the job. Are executed in the order provided.
          { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
            &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
            },
            &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
              &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
            },
            &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
            },
            &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
            },
            &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
            },
            &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
              &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            },
          },
        ],
        &quot;privacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
          &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
          &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
            &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
              { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                  { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                    &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  },
                ],
                &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            ],
            &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
              { # A column with a semantic tag attached.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                },
                &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              },
            ],
            &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
          },
          &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
            &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
              &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            },
            &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
          },
          &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
            &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
              { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                  { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                    &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  },
                ],
                &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            ],
            &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
              { # A column with a semantic tag attached.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                },
                &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              },
            ],
            &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
          },
          &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
            &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
          &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
        },
        &quot;sourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
    },
    &quot;requestedPrivacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
      &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
        &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
      &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
        &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
          { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
            &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
              { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            ],
            &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        ],
        &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
          { # A column with a semantic tag attached.
            &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
            },
            &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          },
        ],
        &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
      },
      &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
        &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
          &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        },
        &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
      },
      &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
        &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
          { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
            &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
              { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            ],
            &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        ],
        &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
          { # A column with a semantic tag attached.
            &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
            &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
            },
            &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
            },
          },
        ],
        &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
      },
      &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
        &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
          { # General identifier of a data field in a storage service.
            &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
          },
        ],
        &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
      &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
        &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
        },
      },
    },
    &quot;requestedSourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
    },
  },
  &quot;startTime&quot;: &quot;A String&quot;, # Time when the job started.
  &quot;state&quot;: &quot;A String&quot;, # State of a job.
  &quot;type&quot;: &quot;A String&quot;, # The type of job.
}</pre>
</div>

<div class="method">
    <code class="details" id="list">list(parent, filter=None, locationId=None, orderBy=None, pageSize=None, pageToken=None, type=None, x__xgafv=None)</code>
  <pre>Lists DlpJobs that match the specified filter in the request. See https://cloud.google.com/dlp/docs/inspecting-storage and https://cloud.google.com/dlp/docs/compute-risk-analysis to learn more.

Args:
  parent: string, Required. Parent resource name. The format of this value varies depending on whether you have [specified a processing location](https://cloud.google.com/dlp/docs/specifying-location): + Projects scope, location specified: `projects/`PROJECT_ID`/locations/`LOCATION_ID + Projects scope, no location specified (defaults to global): `projects/`PROJECT_ID The following example `parent` string specifies a parent project with the identifier `example-project`, and specifies the `europe-west3` location for processing data: parent=projects/example-project/locations/europe-west3 (required)
  filter: string, Allows filtering. Supported syntax: * Filter expressions are made up of one or more restrictions. * Restrictions can be combined by `AND` or `OR` logical operators. A sequence of restrictions implicitly uses `AND`. * A restriction has the form of `{field} {operator} {value}`. * Supported fields/values for inspect jobs: - `state` - PENDING|RUNNING|CANCELED|FINISHED|FAILED - `inspected_storage` - DATASTORE|CLOUD_STORAGE|BIGQUERY - `trigger_name` - The resource name of the trigger that created job. - &#x27;end_time` - Corresponds to time the job finished. - &#x27;start_time` - Corresponds to time the job finished. * Supported fields for risk analysis jobs: - `state` - RUNNING|CANCELED|FINISHED|FAILED - &#x27;end_time` - Corresponds to time the job finished. - &#x27;start_time` - Corresponds to time the job finished. * The operator must be `=` or `!=`. Examples: * inspected_storage = cloud_storage AND state = done * inspected_storage = cloud_storage OR inspected_storage = bigquery * inspected_storage = cloud_storage AND (state = done OR state = canceled) * end_time &gt; \&quot;2017-12-12T00:00:00+00:00\&quot; The length of this field should be no more than 500 characters.
  locationId: string, Deprecated. This field has no effect.
  orderBy: string, Comma separated list of fields to order by, followed by `asc` or `desc` postfix. This list is case-insensitive, default sorting order is ascending, redundant space characters are insignificant. Example: `name asc, end_time asc, create_time desc` Supported fields are: - `create_time`: corresponds to time the job was created. - `end_time`: corresponds to time the job ended. - `name`: corresponds to job&#x27;s name. - `state`: corresponds to `state`
  pageSize: integer, The standard list page size.
  pageToken: string, The standard list page token.
  type: string, The type of job. Defaults to `DlpJobType.INSPECT`
    Allowed values
      DLP_JOB_TYPE_UNSPECIFIED - Defaults to INSPECT_JOB.
      INSPECT_JOB - The job inspected Google Cloud for sensitive data.
      RISK_ANALYSIS_JOB - The job executed a Risk Analysis computation.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The response message for listing DLP jobs.
  &quot;jobs&quot;: [ # A list of DlpJobs that matches the specified filter in the request.
    { # Combines all of the information about a DLP job.
      &quot;createTime&quot;: &quot;A String&quot;, # Time when the job was created.
      &quot;endTime&quot;: &quot;A String&quot;, # Time when the job finished.
      &quot;errors&quot;: [ # A stream of errors encountered running the job.
        { # Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
          &quot;details&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Detailed error codes and messages.
            &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
            &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
              {
                &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
              },
            ],
            &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
          },
          &quot;timestamps&quot;: [ # The times the error occurred.
            &quot;A String&quot;,
          ],
        },
      ],
      &quot;inspectDetails&quot;: { # The results of an inspect DataSource job. # Results from inspecting a data source.
        &quot;requestedOptions&quot;: { # Snapshot of the inspection configuration. # The configuration used for this job.
          &quot;jobConfig&quot;: { # Controls what and how to inspect for findings. # Inspect config.
            &quot;actions&quot;: [ # Actions to execute at the completion of the job.
              { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
                &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
                },
                &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
                  &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
                },
                &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
                },
                &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
                },
                &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
                },
                &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
                  &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                    &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                    &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                    },
                  },
                },
              },
            ],
            &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # How and what to scan for.
              &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
                &quot;A String&quot;,
              ],
              &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
                { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
                  &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                    { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                      &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                        &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                          &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                            42,
                          ],
                          &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                        },
                        &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                          &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                          &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                        },
                        &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                          &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                          &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                        },
                      },
                    },
                  ],
                  &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                    &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                      &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                    },
                    &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                      &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                        &quot;A String&quot;,
                      ],
                    },
                  },
                  &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
                  &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                    &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                  },
                  &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
                  &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                    &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                    &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
                  },
                  &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
                  },
                },
              ],
              &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
              &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
              &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              ],
              &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
                &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
                  { # Max findings configuration per infoType, per content item or long running DlpJob.
                    &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                    &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
                  },
                ],
                &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
                &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
              },
              &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
              &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
                { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
                  &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                    { # Type of information detected by the API.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                  ],
                  &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                    { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                      &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                        &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                          &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                            &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                          },
                          &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                            &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                              &quot;A String&quot;,
                            ],
                          },
                        },
                        &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                          &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                            { # Type of information detected by the API.
                              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                            },
                          ],
                        },
                        &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                        &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                          &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                            42,
                          ],
                          &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                        },
                      },
                      &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                        &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                          &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                            42,
                          ],
                          &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                        },
                        &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                          &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                          &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                        },
                        &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                          &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                          &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                        },
                      },
                    },
                  ],
                },
              ],
            },
            &quot;inspectTemplateName&quot;: &quot;A String&quot;, # If provided, will be used as the default for all values in InspectConfig. `inspect_config` will be merged into the values persisted as part of the template.
            &quot;storageConfig&quot;: { # Shared message indicating Cloud storage type. # The data to scan.
              &quot;bigQueryOptions&quot;: { # Options defining BigQuery table and row identifiers. # BigQuery options.
                &quot;excludedFields&quot;: [ # References to fields excluded from scanning. This allows you to skip inspection of entire columns which you know have no findings.
                  { # General identifier of a data field in a storage service.
                    &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                  },
                ],
                &quot;identifyingFields&quot;: [ # Table fields that may uniquely identify a row within the table. When `actions.saveFindings.outputConfig.table` is specified, the values of columns specified here are available in the output table under `location.content_locations.record_location.record_key.id_values`. Nested fields such as `person.birthdate.year` are allowed.
                  { # General identifier of a data field in a storage service.
                    &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                  },
                ],
                &quot;rowsLimit&quot;: &quot;A String&quot;, # Max number of rows to scan. If the table has more rows than this value, the rest of the rows are omitted. If not set, or if set to 0, all rows will be scanned. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
                &quot;rowsLimitPercent&quot;: 42, # Max percentage of rows to scan. The rest are omitted. The number of rows scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of rows_limit and rows_limit_percent can be specified. Cannot be used in conjunction with TimespanConfig.
                &quot;sampleMethod&quot;: &quot;A String&quot;,
                &quot;tableReference&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Complete BigQuery table reference.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
              &quot;cloudStorageOptions&quot;: { # Options defining a file or a set of files within a Google Cloud Storage bucket. # Google Cloud Storage options.
                &quot;bytesLimitPerFile&quot;: &quot;A String&quot;, # Max number of bytes to scan from a file. If a scanned file&#x27;s size is bigger than this value then the rest of the bytes are omitted. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
                &quot;bytesLimitPerFilePercent&quot;: 42, # Max percentage of bytes to scan from a file. The rest are omitted. The number of bytes scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0. Only one of bytes_limit_per_file and bytes_limit_per_file_percent can be specified. Cannot be set if de-identification is requested.
                &quot;fileSet&quot;: { # Set of files to scan. # The set of one or more files to scan.
                  &quot;regexFileSet&quot;: { # Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in `include_regex` and do not match any items in `exclude_regex`. Note that a file that matches items from both lists will _not_ be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory1/.*&quot;], exclude_regex: [&quot;directory1/excluded.*&quot;]}`: * `gs://mybucket/directory1/myfile` will be included * `gs://mybucket/directory1/directory2/myfile` will be included (`.*` matches across `/`) * `gs://mybucket/directory0/directory1/myfile` will _not_ be included (the full path doesn&#x27;t match any items in `include_regex`) * `gs://mybucket/directory1/excludedfile` will _not_ be included (the path matches an item in `exclude_regex`) If `include_regex` is left empty, it will match all files by default (this is equivalent to setting `include_regex: [&quot;.*&quot;]`). Some other common use cases: * `{bucket_name: &quot;mybucket&quot;, exclude_regex: [&quot;.*\.pdf&quot;]}` will include all files in `mybucket` except for .pdf files * `{bucket_name: &quot;mybucket&quot;, include_regex: [&quot;directory/[^/]+&quot;]}` will include all files directly under `gs://mybucket/directory/`, without matching across `/` # The regex-filtered set of files to scan. Exactly one of `url` or `regex_file_set` must be set.
                    &quot;bucketName&quot;: &quot;A String&quot;, # The name of a Cloud Storage bucket. Required.
                    &quot;excludeRegex&quot;: [ # A list of regular expressions matching file paths to exclude. All files in the bucket that match at least one of these regular expressions will be excluded from the scan. Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                      &quot;A String&quot;,
                    ],
                    &quot;includeRegex&quot;: [ # A list of regular expressions matching file paths to include. All files in the bucket that match at least one of these regular expressions will be included in the set of files, except for those that also match an item in `exclude_regex`. Leaving this field empty will match all files by default (this is equivalent to including `.*` in the list). Regular expressions use RE2 [syntax](https://github.com/google/re2/wiki/Syntax); a guide can be found under the google/re2 repository on GitHub.
                      &quot;A String&quot;,
                    ],
                  },
                  &quot;url&quot;: &quot;A String&quot;, # The Cloud Storage url of the file(s) to scan, in the format `gs:///`. Trailing wildcard in the path is allowed. If the url ends in a trailing slash, the bucket or directory represented by the url will be scanned non-recursively (content in sub-directories will not be scanned). This means that `gs://mybucket/` is equivalent to `gs://mybucket/*`, and `gs://mybucket/directory/` is equivalent to `gs://mybucket/directory/*`. Exactly one of `url` or `regex_file_set` must be set.
                },
                &quot;fileTypes&quot;: [ # List of file type groups to include in the scan. If empty, all files are scanned and available data format processors are applied. In addition, the binary content of the selected files is always scanned as well. Images are scanned only as binary if the specified region does not support image inspection and no file_types were specified. Image inspection is restricted to &#x27;global&#x27;, &#x27;us&#x27;, &#x27;asia&#x27;, and &#x27;europe&#x27;.
                  &quot;A String&quot;,
                ],
                &quot;filesLimitPercent&quot;: 42, # Limits the number of files to scan to this percentage of the input FileSet. Number of files scanned is rounded down. Must be between 0 and 100, inclusively. Both 0 and 100 means no limit. Defaults to 0.
                &quot;sampleMethod&quot;: &quot;A String&quot;,
              },
              &quot;datastoreOptions&quot;: { # Options defining a data set within Google Cloud Datastore. # Google Cloud Datastore options.
                &quot;kind&quot;: { # A representation of a Datastore kind. # The kind to process.
                  &quot;name&quot;: &quot;A String&quot;, # The name of the kind.
                },
                &quot;partitionId&quot;: { # Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID. # A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty.
                  &quot;namespaceId&quot;: &quot;A String&quot;, # If not empty, the ID of the namespace to which the entities belong.
                  &quot;projectId&quot;: &quot;A String&quot;, # The ID of the project to which the entities belong.
                },
              },
              &quot;hybridOptions&quot;: { # Configuration to control jobs where the content being inspected is outside of Google Cloud Platform. # Hybrid inspection options.
                &quot;description&quot;: &quot;A String&quot;, # A short description of where the data is coming from. Will be stored once in the job. 256 max length.
                &quot;labels&quot;: { # To organize findings, these labels will be added to each finding. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`. No more than 10 labels can be associated with a given finding. Examples: * `&quot;environment&quot; : &quot;production&quot;` * `&quot;pipeline&quot; : &quot;etl&quot;`
                  &quot;a_key&quot;: &quot;A String&quot;,
                },
                &quot;requiredFindingLabelKeys&quot;: [ # These are labels that each inspection request must include within their &#x27;finding_labels&#x27; map. Request may contain others, but any missing one of these will be rejected. Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?`. No more than 10 keys can be required.
                  &quot;A String&quot;,
                ],
                &quot;tableOptions&quot;: { # Instructions regarding the table content being inspected. # If the container is a table, additional information to make findings meaningful such as the columns that are primary keys.
                  &quot;identifyingFields&quot;: [ # The columns that are the primary keys for table objects included in ContentItem. A copy of this cell&#x27;s value will stored alongside alongside each finding so that the finding can be traced to the specific row it came from. No more than 3 may be provided.
                    { # General identifier of a data field in a storage service.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  ],
                },
              },
              &quot;timespanConfig&quot;: { # Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Google Cloud Storage and BigQuery.
                &quot;enableAutoPopulationOfTimespanConfig&quot;: True or False, # When the job is started by a JobTrigger we will automatically figure out a valid start_time to avoid scanning files that have not been modified since the last time the JobTrigger executed. This will be based on the time of the execution of the last run of the JobTrigger.
                &quot;endTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows newer than this value. If not set, no upper time limit is applied.
                &quot;startTime&quot;: &quot;A String&quot;, # Exclude files, tables, or rows older than this value. If not set, no lower time limit is applied.
                &quot;timestampField&quot;: { # General identifier of a data field in a storage service. # Specification of the field containing the timestamp of scanned items. Used for data sources like Datastore and BigQuery. For BigQuery: If this value is not specified and the table was modified between the given start and end times, the entire table will be scanned. If this value is specified, then rows are filtered based on the given start and end times. Rows with a `NULL` value in the provided BigQuery column are skipped. Valid data types of the provided BigQuery column are: `INTEGER`, `DATE`, `TIMESTAMP`, and `DATETIME`. For Datastore: If this value is specified, then entities are filtered based on the given start and end times. If an entity does not contain the provided timestamp property or contains empty or invalid values, then it is included. Valid data types of the provided timestamp property are: `TIMESTAMP`.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            },
          },
          &quot;snapshotInspectTemplate&quot;: { # The inspectTemplate contains a configuration (set of types of sensitive data to be detected) to be used anywhere you otherwise would normally specify InspectConfig. See https://cloud.google.com/dlp/docs/concepts-templates to learn more. # If run with an InspectTemplate, a snapshot of its state at the time of this run.
            &quot;createTime&quot;: &quot;A String&quot;, # Output only. The creation timestamp of an inspectTemplate.
            &quot;description&quot;: &quot;A String&quot;, # Short description (max 256 chars).
            &quot;displayName&quot;: &quot;A String&quot;, # Display name (max 256 chars).
            &quot;inspectConfig&quot;: { # Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used. # The core content of the template. Configuration of the scanning process.
              &quot;contentOptions&quot;: [ # List of options defining data content to scan. If empty, text, images, and other content will be included.
                &quot;A String&quot;,
              ],
              &quot;customInfoTypes&quot;: [ # CustomInfoTypes provided by the user. See https://cloud.google.com/dlp/docs/creating-custom-infotypes to learn more.
                { # Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
                  &quot;detectionRules&quot;: [ # Set of detection rules to apply to all findings of this CustomInfoType. Rules are applied in order that they are specified. Not supported for the `surrogate_type` CustomInfoType.
                    { # Deprecated; use `InspectionRuleSet` instead. Rule for modifying a `CustomInfoType` to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the `surrogate_type` custom infoType.
                      &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                        &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                          &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                            42,
                          ],
                          &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                        },
                        &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                          &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                          &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                        },
                        &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                          &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                          &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                        },
                      },
                    },
                  ],
                  &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # A list of phrases to detect as a CustomInfoType.
                    &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                      &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                    },
                    &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                      &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                        &quot;A String&quot;,
                      ],
                    },
                  },
                  &quot;exclusionType&quot;: &quot;A String&quot;, # If set to EXCLUSION_TYPE_EXCLUDE this infoType will not cause a finding to be returned. It still can be used for rules matching.
                  &quot;infoType&quot;: { # Type of information detected by the API. # CustomInfoType can either be a new infoType, or an extension of built-in infoType, when the name matches one of existing infoTypes and that infoType is specified in `InspectContent.info_types` field. Specifying the latter adds findings to the one detected by the system. If built-in info type is not specified in `InspectContent.info_types` list then the name is treated as a custom info type.
                    &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                  },
                  &quot;likelihood&quot;: &quot;A String&quot;, # Likelihood to return for this CustomInfoType. This base value can be altered by a detection rule if the finding meets the criteria specified by the rule. Defaults to `VERY_LIKELY` if not specified.
                  &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression based CustomInfoType.
                    &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                      42,
                    ],
                    &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                  },
                  &quot;storedType&quot;: { # A reference to a StoredInfoType to use with scanning. # Load an existing `StoredInfoType` resource for use in `InspectDataSource`. Not currently supported in `InspectContent`.
                    &quot;createTime&quot;: &quot;A String&quot;, # Timestamp indicating when the version of the `StoredInfoType` used for inspection was created. Output-only field, populated by the system.
                    &quot;name&quot;: &quot;A String&quot;, # Resource name of the requested `StoredInfoType`, for example `organizations/433245324/storedInfoTypes/432452342` or `projects/project-id/storedInfoTypes/432452342`.
                  },
                  &quot;surrogateType&quot;: { # Message for detecting output from deidentification transformations such as [`CryptoReplaceFfxFpeConfig`](https://cloud.google.com/dlp/docs/reference/rest/v2/organizations.deidentifyTemplates#cryptoreplaceffxfpeconfig). These types of transformations are those that perform pseudonymization, thereby producing a &quot;surrogate&quot; as output. This should be used in conjunction with a field on the transformation such as `surrogate_info_type`. This CustomInfoType does not support the use of `detection_rules`. # Message for detecting output from deidentification transformations that support reversing.
                  },
                },
              ],
              &quot;excludeInfoTypes&quot;: True or False, # When true, excludes type information of the findings.
              &quot;includeQuote&quot;: True or False, # When true, a contextual quote from the data that triggered a finding is included in the response; see Finding.quote.
              &quot;infoTypes&quot;: [ # Restricts what info_types to look for. The values must correspond to InfoType values returned by ListInfoTypes or listed at https://cloud.google.com/dlp/docs/infotypes-reference. When no InfoTypes or CustomInfoTypes are specified in a request, the system may automatically choose what detectors to run. By default this may be all types, but may change over time as detectors are updated. If you need precise control and predictability as to what detectors are run you should specify specific InfoTypes listed in the reference, otherwise a default list will be used, which may change over time.
                { # Type of information detected by the API.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              ],
              &quot;limits&quot;: { # Configuration to control the number of findings returned. Cannot be set if de-identification is requested. # Configuration to control the number of findings returned.
                &quot;maxFindingsPerInfoType&quot;: [ # Configuration of findings limit given for specified infoTypes.
                  { # Max findings configuration per infoType, per content item or long running DlpJob.
                    &quot;infoType&quot;: { # Type of information detected by the API. # Type of information the findings limit applies to. Only one limit per info_type should be provided. If InfoTypeLimit does not have an info_type, the DLP API applies the limit against all info_types that are found but not specified in another InfoTypeLimit.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                    &quot;maxFindings&quot;: 42, # Max findings limit for the given infoType.
                  },
                ],
                &quot;maxFindingsPerItem&quot;: 42, # Max number of findings that will be returned for each item scanned. When set within `InspectJobConfig`, the maximum returned is 2000 regardless if this is set higher. When set within `InspectContentRequest`, this field is ignored.
                &quot;maxFindingsPerRequest&quot;: 42, # Max number of findings that will be returned per request/job. When set within `InspectContentRequest`, the maximum returned is 2000 regardless if this is set higher.
              },
              &quot;minLikelihood&quot;: &quot;A String&quot;, # Only returns findings equal or above this threshold. The default is POSSIBLE. See https://cloud.google.com/dlp/docs/likelihood to learn more.
              &quot;ruleSet&quot;: [ # Set of rules to apply to the findings for this InspectConfig. Exclusion rules, contained in the set are executed in the end, other rules are executed in the order they are specified for each info type.
                { # Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
                  &quot;infoTypes&quot;: [ # List of infoTypes this rule set is applied to.
                    { # Type of information detected by the API.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                  ],
                  &quot;rules&quot;: [ # Set of rules to be applied to infoTypes. The rules are applied in order.
                    { # A single inspection rule to be applied to infoTypes, specified in `InspectionRuleSet`.
                      &quot;exclusionRule&quot;: { # The rule that specifies conditions when findings of infoTypes specified in `InspectionRuleSet` are removed from results. # Exclusion rule.
                        &quot;dictionary&quot;: { # Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode [Basic Multilingual Plane](https://en.wikipedia.org/wiki/Plane_%28Unicode%29#Basic_Multilingual_Plane) will be replaced with whitespace when scanning for matches, so the dictionary phrase &quot;Sam Johnson&quot; will match all three phrases &quot;sam johnson&quot;, &quot;Sam, Johnson&quot;, and &quot;Sam (Johnson)&quot;. Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word &quot;jen&quot; will match the first three letters of the text &quot;jen123&quot; but will return no matches for &quot;jennifer&quot;. Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The [limits](https://cloud.google.com/dlp/limits) page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using `LargeCustomDictionaryConfig` in the `StoredInfoType` API. # Dictionary which defines the rule.
                          &quot;cloudStoragePath&quot;: { # Message representing a single file or path in Cloud Storage. # Newline-delimited file of words in Cloud Storage. Only a single file is accepted.
                            &quot;path&quot;: &quot;A String&quot;, # A url representing a file or path (no wildcards) in Cloud Storage. Example: gs://[BUCKET_NAME]/dictionary.txt
                          },
                          &quot;wordList&quot;: { # Message defining a list of words or phrases to search for in the data. # List of words or phrases to search for.
                            &quot;words&quot;: [ # Words or phrases defining the dictionary. The dictionary must contain at least one phrase and every phrase must contain at least 2 characters that are letters or digits. [required]
                              &quot;A String&quot;,
                            ],
                          },
                        },
                        &quot;excludeInfoTypes&quot;: { # List of exclude infoTypes. # Set of infoTypes for which findings would affect this rule.
                          &quot;infoTypes&quot;: [ # InfoType list in ExclusionRule rule drops a finding when it overlaps or contained within with a finding of an infoType from this list. For example, for `InspectionRuleSet.info_types` containing &quot;PHONE_NUMBER&quot;` and `exclusion_rule` containing `exclude_info_types.info_types` with &quot;EMAIL_ADDRESS&quot; the phone number findings are dropped if they overlap with EMAIL_ADDRESS finding. That leads to &quot;555-222-2222@example.org&quot; to generate only a single finding, namely email address.
                            { # Type of information detected by the API.
                              &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                            },
                          ],
                        },
                        &quot;matchingType&quot;: &quot;A String&quot;, # How the rule is applied, see MatchingType documentation for details.
                        &quot;regex&quot;: { # Message defining a custom regular expression. # Regular expression which defines the rule.
                          &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                            42,
                          ],
                          &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                        },
                      },
                      &quot;hotwordRule&quot;: { # The rule that adjusts the likelihood of findings within a certain proximity of hotwords. # Hotword-based detection rule.
                        &quot;hotwordRegex&quot;: { # Message defining a custom regular expression. # Regular expression pattern defining what qualifies as a hotword.
                          &quot;groupIndexes&quot;: [ # The index of the submatch to extract as findings. When not specified, the entire match is returned. No more than 3 may be included.
                            42,
                          ],
                          &quot;pattern&quot;: &quot;A String&quot;, # Pattern defining the regular expression. Its syntax (https://github.com/google/re2/wiki/Syntax) can be found under the google/re2 repository on GitHub.
                        },
                        &quot;likelihoodAdjustment&quot;: { # Message for specifying an adjustment to the likelihood of a finding as part of a detection rule. # Likelihood adjustment to apply to all matching findings.
                          &quot;fixedLikelihood&quot;: &quot;A String&quot;, # Set the likelihood of a finding to a fixed value.
                          &quot;relativeLikelihood&quot;: 42, # Increase or decrease the likelihood by the specified number of levels. For example, if a finding would be `POSSIBLE` without the detection rule and `relative_likelihood` is 1, then it is upgraded to `LIKELY`, while a value of -1 would downgrade it to `UNLIKELY`. Likelihood may never drop below `VERY_UNLIKELY` or exceed `VERY_LIKELY`, so applying an adjustment of 1 followed by an adjustment of -1 when base likelihood is `VERY_LIKELY` will result in a final likelihood of `LIKELY`.
                        },
                        &quot;proximity&quot;: { # Message for specifying a window around a finding to apply a detection rule. # Proximity of the finding within which the entire hotword must reside. The total length of the window cannot exceed 1000 characters. Note that the finding itself will be included in the window, so that hotwords may be used to match substrings of the finding itself. For example, the certainty of a phone number regex &quot;\(\d{3}\) \d{3}-\d{4}&quot; could be adjusted upwards if the area code is known to be the local area code of a company office using the hotword regex &quot;\(xxx\)&quot;, where &quot;xxx&quot; is the area code in question.
                          &quot;windowAfter&quot;: 42, # Number of characters after the finding to consider.
                          &quot;windowBefore&quot;: 42, # Number of characters before the finding to consider.
                        },
                      },
                    },
                  ],
                },
              ],
            },
            &quot;name&quot;: &quot;A String&quot;, # Output only. The template name. The template will have one of the following formats: `projects/PROJECT_ID/inspectTemplates/TEMPLATE_ID` OR `organizations/ORGANIZATION_ID/inspectTemplates/TEMPLATE_ID`;
            &quot;updateTime&quot;: &quot;A String&quot;, # Output only. The last update timestamp of an inspectTemplate.
          },
        },
        &quot;result&quot;: { # All result fields mentioned below are updated while the job is processing. # A summary of the outcome of this inspection job.
          &quot;hybridStats&quot;: { # Statistics related to processing hybrid inspect requests. # Statistics related to the processing of hybrid inspect.
            &quot;abortedCount&quot;: &quot;A String&quot;, # The number of hybrid inspection requests aborted because the job ran out of quota or was ended before they could be processed.
            &quot;pendingCount&quot;: &quot;A String&quot;, # The number of hybrid requests currently being processed. Only populated when called via method `getDlpJob`. A burst of traffic may cause hybrid inspect requests to be enqueued. Processing will take place as quickly as possible, but resource limitations may impact how long a request is enqueued for.
            &quot;processedCount&quot;: &quot;A String&quot;, # The number of hybrid inspection requests processed within this job.
          },
          &quot;infoTypeStats&quot;: [ # Statistics of how many instances of each info type were found during inspect job.
            { # Statistics regarding a specific InfoType.
              &quot;count&quot;: &quot;A String&quot;, # Number of findings for this infoType.
              &quot;infoType&quot;: { # Type of information detected by the API. # The type of finding this stat is for.
                &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
              },
            },
          ],
          &quot;processedBytes&quot;: &quot;A String&quot;, # Total size in bytes that were processed.
          &quot;totalEstimatedBytes&quot;: &quot;A String&quot;, # Estimate of the number of bytes to process.
        },
      },
      &quot;jobTriggerName&quot;: &quot;A String&quot;, # If created by a job trigger, the resource name of the trigger that instantiated the job.
      &quot;name&quot;: &quot;A String&quot;, # The server-assigned name.
      &quot;riskDetails&quot;: { # Result of a risk analysis operation request. # Results from analyzing risk of a data source.
        &quot;categoricalStatsResult&quot;: { # Result of the categorical stats computation. # Categorical stats result
          &quot;valueFrequencyHistogramBuckets&quot;: [ # Histogram of value frequencies in the column.
            { # Histogram of value frequencies in the column.
              &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of values in this bucket.
              &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct values in this bucket.
              &quot;bucketValues&quot;: [ # Sample of value frequencies in this bucket. The total number of values returned per bucket is capped at 20.
                { # A value of a field, including its frequency.
                  &quot;count&quot;: &quot;A String&quot;, # How many times the value is contained in the field.
                  &quot;value&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # A value contained in the field in question.
                    &quot;booleanValue&quot;: True or False, # boolean
                    &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                      &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                      &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                      &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                    },
                    &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                    &quot;floatValue&quot;: 3.14, # float
                    &quot;integerValue&quot;: &quot;A String&quot;, # integer
                    &quot;stringValue&quot;: &quot;A String&quot;, # string
                    &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                      &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                      &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                      &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                      &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                    },
                    &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                  },
                },
              ],
              &quot;valueFrequencyLowerBound&quot;: &quot;A String&quot;, # Lower bound on the value frequency of the values in this bucket.
              &quot;valueFrequencyUpperBound&quot;: &quot;A String&quot;, # Upper bound on the value frequency of the values in this bucket.
            },
          ],
        },
        &quot;deltaPresenceEstimationResult&quot;: { # Result of the δ-presence computation. Note that these results are an estimation, not exact values. # Delta-presence result
          &quot;deltaPresenceEstimationHistogram&quot;: [ # The intervals [min_probability, max_probability) do not overlap. If a value doesn&#x27;t correspond to any such interval, the associated frequency is zero. For example, the following records: {min_probability: 0, max_probability: 0.1, frequency: 17} {min_probability: 0.2, max_probability: 0.3, frequency: 42} {min_probability: 0.3, max_probability: 0.4, frequency: 99} mean that there are no record with an estimated probability in [0.1, 0.2) nor larger or equal to 0.4.
            { # A DeltaPresenceEstimationHistogramBucket message with the following values: min_probability: 0.1 max_probability: 0.2 frequency: 42 means that there are 42 records for which δ is in [0.1, 0.2). An important particular case is when min_probability = max_probability = 1: then, every individual who shares this quasi-identifier combination is in the dataset.
              &quot;bucketSize&quot;: &quot;A String&quot;, # Number of records within these probability bounds.
              &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct quasi-identifier tuple values in this bucket.
              &quot;bucketValues&quot;: [ # Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20.
                { # A tuple of values for the quasi-identifier columns.
                  &quot;estimatedProbability&quot;: 3.14, # The estimated probability that a given individual sharing these quasi-identifier values is in the dataset. This value, typically called δ, is the ratio between the number of records in the dataset with these quasi-identifier values, and the total number of individuals (inside *and* outside the dataset) with these quasi-identifier values. For example, if there are 15 individuals in the dataset who share the same quasi-identifier values, and an estimated 100 people in the entire population with these values, then δ is 0.15.
                  &quot;quasiIdsValues&quot;: [ # The quasi-identifier values.
                    { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                      &quot;booleanValue&quot;: True or False, # boolean
                      &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                        &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                        &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                        &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                      },
                      &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                      &quot;floatValue&quot;: 3.14, # float
                      &quot;integerValue&quot;: &quot;A String&quot;, # integer
                      &quot;stringValue&quot;: &quot;A String&quot;, # string
                      &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                        &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                        &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                        &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                        &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                      },
                      &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                    },
                  ],
                },
              ],
              &quot;maxProbability&quot;: 3.14, # Always greater than or equal to min_probability.
              &quot;minProbability&quot;: 3.14, # Between 0 and 1.
            },
          ],
        },
        &quot;kAnonymityResult&quot;: { # Result of the k-anonymity computation. # K-anonymity result
          &quot;equivalenceClassHistogramBuckets&quot;: [ # Histogram of k-anonymity equivalence classes.
            { # Histogram of k-anonymity equivalence classes.
              &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of equivalence classes in this bucket.
              &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct equivalence classes in this bucket.
              &quot;bucketValues&quot;: [ # Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20.
                { # The set of columns&#x27; values that share the same ldiversity value
                  &quot;equivalenceClassSize&quot;: &quot;A String&quot;, # Size of the equivalence class, for example number of rows with the above set of values.
                  &quot;quasiIdsValues&quot;: [ # Set of values defining the equivalence class. One value per quasi-identifier column in the original KAnonymity metric message. The order is always the same as the original request.
                    { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                      &quot;booleanValue&quot;: True or False, # boolean
                      &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                        &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                        &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                        &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                      },
                      &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                      &quot;floatValue&quot;: 3.14, # float
                      &quot;integerValue&quot;: &quot;A String&quot;, # integer
                      &quot;stringValue&quot;: &quot;A String&quot;, # string
                      &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                        &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                        &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                        &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                        &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                      },
                      &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                    },
                  ],
                },
              ],
              &quot;equivalenceClassSizeLowerBound&quot;: &quot;A String&quot;, # Lower bound on the size of the equivalence classes in this bucket.
              &quot;equivalenceClassSizeUpperBound&quot;: &quot;A String&quot;, # Upper bound on the size of the equivalence classes in this bucket.
            },
          ],
        },
        &quot;kMapEstimationResult&quot;: { # Result of the reidentifiability analysis. Note that these results are an estimation, not exact values. # K-map result
          &quot;kMapEstimationHistogram&quot;: [ # The intervals [min_anonymity, max_anonymity] do not overlap. If a value doesn&#x27;t correspond to any such interval, the associated frequency is zero. For example, the following records: {min_anonymity: 1, max_anonymity: 1, frequency: 17} {min_anonymity: 2, max_anonymity: 3, frequency: 42} {min_anonymity: 5, max_anonymity: 10, frequency: 99} mean that there are no record with an estimated anonymity of 4, 5, or larger than 10.
            { # A KMapEstimationHistogramBucket message with the following values: min_anonymity: 3 max_anonymity: 5 frequency: 42 means that there are 42 records whose quasi-identifier values correspond to 3, 4 or 5 people in the overlying population. An important particular case is when min_anonymity = max_anonymity = 1: the frequency field then corresponds to the number of uniquely identifiable records.
              &quot;bucketSize&quot;: &quot;A String&quot;, # Number of records within these anonymity bounds.
              &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct quasi-identifier tuple values in this bucket.
              &quot;bucketValues&quot;: [ # Sample of quasi-identifier tuple values in this bucket. The total number of classes returned per bucket is capped at 20.
                { # A tuple of values for the quasi-identifier columns.
                  &quot;estimatedAnonymity&quot;: &quot;A String&quot;, # The estimated anonymity for these quasi-identifier values.
                  &quot;quasiIdsValues&quot;: [ # The quasi-identifier values.
                    { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                      &quot;booleanValue&quot;: True or False, # boolean
                      &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                        &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                        &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                        &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                      },
                      &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                      &quot;floatValue&quot;: 3.14, # float
                      &quot;integerValue&quot;: &quot;A String&quot;, # integer
                      &quot;stringValue&quot;: &quot;A String&quot;, # string
                      &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                        &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                        &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                        &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                        &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                      },
                      &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                    },
                  ],
                },
              ],
              &quot;maxAnonymity&quot;: &quot;A String&quot;, # Always greater than or equal to min_anonymity.
              &quot;minAnonymity&quot;: &quot;A String&quot;, # Always positive.
            },
          ],
        },
        &quot;lDiversityResult&quot;: { # Result of the l-diversity computation. # L-divesity result
          &quot;sensitiveValueFrequencyHistogramBuckets&quot;: [ # Histogram of l-diversity equivalence class sensitive value frequencies.
            { # Histogram of l-diversity equivalence class sensitive value frequencies.
              &quot;bucketSize&quot;: &quot;A String&quot;, # Total number of equivalence classes in this bucket.
              &quot;bucketValueCount&quot;: &quot;A String&quot;, # Total number of distinct equivalence classes in this bucket.
              &quot;bucketValues&quot;: [ # Sample of equivalence classes in this bucket. The total number of classes returned per bucket is capped at 20.
                { # The set of columns&#x27; values that share the same ldiversity value.
                  &quot;equivalenceClassSize&quot;: &quot;A String&quot;, # Size of the k-anonymity equivalence class.
                  &quot;numDistinctSensitiveValues&quot;: &quot;A String&quot;, # Number of distinct sensitive values in this equivalence class.
                  &quot;quasiIdsValues&quot;: [ # Quasi-identifier values defining the k-anonymity equivalence class. The order is always the same as the original request.
                    { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
                      &quot;booleanValue&quot;: True or False, # boolean
                      &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                        &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                        &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                        &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                      },
                      &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                      &quot;floatValue&quot;: 3.14, # float
                      &quot;integerValue&quot;: &quot;A String&quot;, # integer
                      &quot;stringValue&quot;: &quot;A String&quot;, # string
                      &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                        &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                        &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                        &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                        &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                      },
                      &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                    },
                  ],
                  &quot;topSensitiveValues&quot;: [ # Estimated frequencies of top sensitive values.
                    { # A value of a field, including its frequency.
                      &quot;count&quot;: &quot;A String&quot;, # How many times the value is contained in the field.
                      &quot;value&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # A value contained in the field in question.
                        &quot;booleanValue&quot;: True or False, # boolean
                        &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                          &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                          &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                          &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
                        },
                        &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
                        &quot;floatValue&quot;: 3.14, # float
                        &quot;integerValue&quot;: &quot;A String&quot;, # integer
                        &quot;stringValue&quot;: &quot;A String&quot;, # string
                        &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                          &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                          &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                          &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                          &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
                        },
                        &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
                      },
                    },
                  ],
                },
              ],
              &quot;sensitiveValueFrequencyLowerBound&quot;: &quot;A String&quot;, # Lower bound on the sensitive value frequencies of the equivalence classes in this bucket.
              &quot;sensitiveValueFrequencyUpperBound&quot;: &quot;A String&quot;, # Upper bound on the sensitive value frequencies of the equivalence classes in this bucket.
            },
          ],
        },
        &quot;numericalStatsResult&quot;: { # Result of the numerical stats computation. # Numerical stats result
          &quot;maxValue&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # Maximum value appearing in the column.
            &quot;booleanValue&quot;: True or False, # boolean
            &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
              &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
              &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
              &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
            },
            &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
            &quot;floatValue&quot;: 3.14, # float
            &quot;integerValue&quot;: &quot;A String&quot;, # integer
            &quot;stringValue&quot;: &quot;A String&quot;, # string
            &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
              &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
              &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
              &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
              &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
            },
            &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
          },
          &quot;minValue&quot;: { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data. # Minimum value appearing in the column.
            &quot;booleanValue&quot;: True or False, # boolean
            &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
              &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
              &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
              &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
            },
            &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
            &quot;floatValue&quot;: 3.14, # float
            &quot;integerValue&quot;: &quot;A String&quot;, # integer
            &quot;stringValue&quot;: &quot;A String&quot;, # string
            &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
              &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
              &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
              &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
              &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
            },
            &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
          },
          &quot;quantileValues&quot;: [ # List of 99 values that partition the set of field values into 100 equal sized buckets.
            { # Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a &#x27;Value&#x27; is based on its representation as a UTF-8 encoded string. For example, if &#x27;integer_value&#x27; is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
              &quot;booleanValue&quot;: True or False, # boolean
              &quot;dateValue&quot;: { # Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values * A month and day value, with a zero year, such as an anniversary * A year on its own, with zero month and day values * A year and month value, with a zero day, such as a credit card expiration date Related types are google.type.TimeOfDay and `google.protobuf.Timestamp`. # date
                &quot;day&quot;: 42, # Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn&#x27;t significant.
                &quot;month&quot;: 42, # Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.
                &quot;year&quot;: 42, # Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.
              },
              &quot;dayOfWeekValue&quot;: &quot;A String&quot;, # day of week
              &quot;floatValue&quot;: 3.14, # float
              &quot;integerValue&quot;: &quot;A String&quot;, # integer
              &quot;stringValue&quot;: &quot;A String&quot;, # string
              &quot;timeValue&quot;: { # Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and `google.protobuf.Timestamp`. # time of day
                &quot;hours&quot;: 42, # Hours of day in 24 hour format. Should be from 0 to 23. An API may choose to allow the value &quot;24:00:00&quot; for scenarios like business closing time.
                &quot;minutes&quot;: 42, # Minutes of hour of day. Must be from 0 to 59.
                &quot;nanos&quot;: 42, # Fractions of seconds in nanoseconds. Must be from 0 to 999,999,999.
                &quot;seconds&quot;: 42, # Seconds of minutes of the time. Must normally be from 0 to 59. An API may allow the value 60 if it allows leap-seconds.
              },
              &quot;timestampValue&quot;: &quot;A String&quot;, # timestamp
            },
          ],
        },
        &quot;requestedOptions&quot;: { # Risk analysis options. # The configuration used for this job.
          &quot;jobConfig&quot;: { # Configuration for a risk analysis job. See https://cloud.google.com/dlp/docs/concepts-risk-analysis to learn more. # The job config for the risk job.
            &quot;actions&quot;: [ # Actions to execute at the completion of the job. Are executed in the order provided.
              { # A task to execute on the completion of a job. See https://cloud.google.com/dlp/docs/concepts-actions to learn more.
                &quot;jobNotificationEmails&quot;: { # Enable email notification to project owners and editors on jobs&#x27;s completion/failure. # Enable email notification for project owners and editors on job&#x27;s completion/failure.
                },
                &quot;pubSub&quot;: { # Publish a message into given Pub/Sub topic when DlpJob has completed. The message contains a single field, `DlpJobName`, which is equal to the finished job&#x27;s [`DlpJob.name`](https://cloud.google.com/dlp/docs/reference/rest/v2/projects.dlpJobs#DlpJob). Compatible with: Inspect, Risk # Publish a notification to a pubsub topic.
                  &quot;topic&quot;: &quot;A String&quot;, # Cloud Pub/Sub topic to send notifications to. The topic must have given publishing access rights to the DLP API service account executing the long running DlpJob sending the notifications. Format is projects/{project}/topics/{topic}.
                },
                &quot;publishFindingsToCloudDataCatalog&quot;: { # Publish findings of a DlpJob to Cloud Data Catalog. Labels summarizing the results of the DlpJob will be applied to the entry for the resource scanned in Cloud Data Catalog. Any labels previously written by another DlpJob will be deleted. InfoType naming patterns are strictly enforced when using this feature. Note that the findings will be persisted in Cloud Data Catalog storage and are governed by Data Catalog service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified and only allowed if all resources being scanned are BigQuery tables. Compatible with: Inspect # Publish findings to Cloud Datahub.
                },
                &quot;publishSummaryToCscc&quot;: { # Publish the result summary of a DlpJob to the Cloud Security Command Center (CSCC Alpha). This action is only available for projects which are parts of an organization and whitelisted for the alpha Cloud Security Command Center. The action will publish count of finding instances and their info types. The summary of findings will be persisted in CSCC and are governed by CSCC service-specific policy, see https://cloud.google.com/terms/service-terms Only a single instance of this action can be specified. Compatible with: Inspect # Publish summary to Cloud Security Command Center (Alpha).
                },
                &quot;publishToStackdriver&quot;: { # Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as &#x27;Custom&#x27; under the Stackdriver label &#x27;info_type&#x27;. # Enable Stackdriver metric dlp.googleapis.com/finding_count.
                },
                &quot;saveFindings&quot;: { # If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk # Save resulting findings in a provided location.
                  &quot;outputConfig&quot;: { # Cloud repository for storing output. # Location to store findings outside of DLP.
                    &quot;outputSchema&quot;: &quot;A String&quot;, # Schema used for writing the findings for Inspect jobs. This field is only used for Inspect and must be unspecified for Risk jobs. Columns are derived from the `Finding` object. If appending to an existing table, any columns from the predefined schema that are missing will be added. No columns in the existing table will be deleted. If unspecified, then all available columns will be used for a new table or an (existing) table with no schema, and no changes will be made to an existing table that has a schema. Only for use with external storage.
                    &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Store findings in an existing table or a new table in an existing dataset. If table_id is not set a new one will be generated for you with the following format: dlp_googleapis_yyyy_mm_dd_[dlp_job_id]. Pacific timezone will be used for generating the date details. For Inspect, each column in an existing output table must have the same name, type, and mode of a field in the `Finding` object. For Risk, an existing output table should be the output of a previous Risk analysis job run on the same source table, with the same privacy metric and quasi-identifiers. Risk jobs that analyze the same table but compute a different privacy metric, or use different sets of quasi-identifiers, cannot store their results in the same table.
                      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                    },
                  },
                },
              },
            ],
            &quot;privacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
              &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
              &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
                &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
                  { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                    &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                      { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                        &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                        &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                        },
                      },
                    ],
                    &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                    &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                    },
                  },
                ],
                &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
                  { # A column with a semantic tag attached.
                    &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                    &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                    },
                    &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                  },
                ],
                &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
              },
              &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
                &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
                  &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
                    &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                  },
                },
                &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
                  { # General identifier of a data field in a storage service.
                    &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                  },
                ],
              },
              &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
                &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
                  { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                    &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                      { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                        &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                        &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                          &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                        },
                      },
                    ],
                    &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                    &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                      &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                      &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                      &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                    },
                  },
                ],
                &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
                  { # A column with a semantic tag attached.
                    &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                    &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                    },
                    &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                      &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                    },
                  },
                ],
                &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
              },
              &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
                &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
                  { # General identifier of a data field in a storage service.
                    &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                  },
                ],
                &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
              &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
              },
            },
            &quot;sourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
              &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
              &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
              &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
            },
          },
        },
        &quot;requestedPrivacyMetric&quot;: { # Privacy metric to compute for reidentification risk analysis. # Privacy metric to compute.
          &quot;categoricalStatsConfig&quot;: { # Compute numerical stats over an individual column, including number of distinct values and value count distribution. # Categorical stats
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute categorical stats on. All column types are supported except for arrays and structs. However, it may be more informative to use NumericalStats when the field type is supported, depending on the data.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
          &quot;deltaPresenceEstimationConfig&quot;: { # δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead. # delta-presence
            &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers field must appear in exactly one field of one auxiliary table.
              { # An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                  { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                    &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  },
                ],
                &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            ],
            &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two fields can have the same tag.
              { # A column with a semantic tag attached.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                },
                &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              },
            ],
            &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
          },
          &quot;kAnonymityConfig&quot;: { # k-anonymity metric, used for analysis of reidentification risk. # K-anonymity
            &quot;entityId&quot;: { # An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the `EntityId` might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity. # Message indicating that multiple rows might be associated to a single individual. If the same entity_id is associated to multiple quasi-identifier tuples over distinct rows, we consider the entire collection of tuples as the composite quasi-identifier. This collection is a multiset: the order in which the different tuples appear in the dataset is ignored, but their frequency is taken into account. Important note: a maximum of 1000 rows can be associated to a single entity ID. If more rows are associated with the same entity ID, some might be ignored.
              &quot;field&quot;: { # General identifier of a data field in a storage service. # Composite key indicating which field contains the entity identifier.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            },
            &quot;quasiIds&quot;: [ # Set of fields to compute k-anonymity over. When multiple fields are specified, they are considered a single composite key. Structs and repeated data types are not supported; however, nested fields are supported so long as they are not structs themselves or nested within a repeated field.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
          },
          &quot;kMapEstimationConfig&quot;: { # Reidentifiability metric. This corresponds to a risk model similar to what is called &quot;journalist risk&quot; in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset. # k-map
            &quot;auxiliaryTables&quot;: [ # Several auxiliary tables can be used in the analysis. Each custom_tag used to tag a quasi-identifiers column must appear in exactly one column of one auxiliary table.
              { # An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
                &quot;quasiIds&quot;: [ # Required. Quasi-identifier columns.
                  { # A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
                    &quot;customTag&quot;: &quot;A String&quot;, # A auxiliary field.
                    &quot;field&quot;: { # General identifier of a data field in a storage service. # Identifies the column.
                      &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                    },
                  },
                ],
                &quot;relativeFrequency&quot;: { # General identifier of a data field in a storage service. # Required. The relative frequency column must contain a floating-point number between 0 and 1 (inclusive). Null values are assumed to be zero.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;table&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Required. Auxiliary table location.
                  &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
                  &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
                  &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
                },
              },
            ],
            &quot;quasiIds&quot;: [ # Required. Fields considered to be quasi-identifiers. No two columns can have the same tag.
              { # A column with a semantic tag attached.
                &quot;customTag&quot;: &quot;A String&quot;, # A column can be tagged with a custom tag. In this case, the user must indicate an auxiliary table that contains statistical information on the possible values of this column (below).
                &quot;field&quot;: { # General identifier of a data field in a storage service. # Required. Identifies the column.
                  &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
                },
                &quot;inferred&quot;: { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for `Empty` is empty JSON object `{}`. # If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
                },
                &quot;infoType&quot;: { # Type of information detected by the API. # A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available. We currently support US ZIP codes, region codes, ages and genders. To programmatically obtain the list of supported InfoTypes, use ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
                  &quot;name&quot;: &quot;A String&quot;, # Name of the information type. Either a name of your choosing when creating a CustomInfoType, or one of the names listed at https://cloud.google.com/dlp/docs/infotypes-reference when specifying a built-in type. When sending Cloud DLP results to Data Catalog, infoType names should conform to the pattern `[A-Za-z0-9$-_]{1,64}`.
                },
              },
            ],
            &quot;regionCode&quot;: &quot;A String&quot;, # ISO 3166-1 alpha-2 region code to use in the statistical modeling. Set if no column is tagged with a region-specific InfoType (like US_ZIP_5) or a region code.
          },
          &quot;lDiversityConfig&quot;: { # l-diversity metric, used for analysis of reidentification risk. # l-diversity
            &quot;quasiIds&quot;: [ # Set of quasi-identifiers indicating how equivalence classes are defined for the l-diversity computation. When multiple fields are specified, they are considered a single composite key.
              { # General identifier of a data field in a storage service.
                &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
              },
            ],
            &quot;sensitiveAttribute&quot;: { # General identifier of a data field in a storage service. # Sensitive field for computing the l-value.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
          &quot;numericalStatsConfig&quot;: { # Compute numerical stats over an individual column, including min, max, and quantiles. # Numerical stats
            &quot;field&quot;: { # General identifier of a data field in a storage service. # Field to compute numerical stats on. Supported types are integer, float, date, datetime, timestamp, time.
              &quot;name&quot;: &quot;A String&quot;, # Name describing the field.
            },
          },
        },
        &quot;requestedSourceTable&quot;: { # Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: `:.` or `..`. # Input dataset to compute metrics over.
          &quot;datasetId&quot;: &quot;A String&quot;, # Dataset ID of the table.
          &quot;projectId&quot;: &quot;A String&quot;, # The Google Cloud Platform project ID of the project containing the table. If omitted, project ID is inferred from the API call.
          &quot;tableId&quot;: &quot;A String&quot;, # Name of the table.
        },
      },
      &quot;startTime&quot;: &quot;A String&quot;, # Time when the job started.
      &quot;state&quot;: &quot;A String&quot;, # State of a job.
      &quot;type&quot;: &quot;A String&quot;, # The type of job.
    },
  ],
  &quot;nextPageToken&quot;: &quot;A String&quot;, # The standard List next-page token.
}</pre>
</div>

<div class="method">
    <code class="details" id="list_next">list_next(previous_request, previous_response)</code>
  <pre>Retrieves the next page of results.

Args:
  previous_request: The request for the previous page. (required)
  previous_response: The response from the request for the previous page. (required)

Returns:
  A request object that you can call &#x27;execute()&#x27; on to request the next
  page. Returns None if there are no more items in the collection.
    </pre>
</div>

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