Contributors are essential to Scapy (as they are to most open source projects). Here is some advice to help you help the project!
We try to keep Scapy as powerful as possible, to support as many protocols and platforms as possible, to keep and make the code (and the commit history) as clean as possible.
Since Scapy can be slow and memory consuming, we try to limit CPU and memory usage, particularly in parts of the code often called.
You want to spend time working on Scapy but have no (or little) idea what to do? You can look for open issues labeled “contributions wanted”, or look at the contributions roadmap
If you have any ideas of useful contributions that you cannot (or do not want to) do yourself, open an issue and include “contributions wanted” in the title.
Once you have chosen a contribution, open an issue to let other people know you‘re working on it (or assign the existing issue to yourself) and track your progress. You might want to ask whether you’re working in an appropriate direction, to avoid the frustration of seeing your contribution rejected after a lot of work.
If you have installed Scapy through a package manager (from your Linux or BSD system, from PyPI, etc.), please get and install the current development code, and check that the bug still exists before submitting an issue.
If you‘re not sure whether a behavior is a bug or not, submit an issue and ask, don’t be shy!
If you want a feature in Scapy, but cannot implement it yourself or want some hints on how to do that, open an issue and include “enhancement” in the title.
Explain if possible the API you would like to have (e.g., give examples of function calls, packet creations, etc.).
The code should be PEP-8 compliant; you can check your code with pep8 and the command tox -e flake8
Pylint can help you write good Python code (even if respecting Pylint rules is sometimes either too hard or even undesirable; human brain needed!).
Google Python Style Guide is a nice read!
Avoid creating unnecessary list
objects, particularly if they can be huge (e.g., when possible, use for line in fdesc
instead of for line in fdesc.readlines()
; more generally prefer generators over lists).
Please consider adding tests for your new features or that trigger the bug you are fixing. This will prevent a regression from being unnoticed. Do not use the variable _
in your tests, as it could break them.
If you find yourself in a situation where your tests locally succeed but fail if executed on the CI, try to enable the debugging option for the dissector by setting conf.debug_dissector = 1
.
New protocols can go either in scapy/layers
or to scapy/contrib
. Protocols in scapy/layers
should be usually found on common networks, while protocols in scapy/contrib
should be uncommon or specific.
To be precise, scapy/layers
protocols should not be importing scapy/contrib
protocols, whereas scapy/contrib
protocols may import both scapy/contrib
and scapy/layers
protocols.
The detailed requirements are explained in Design patterns on Scapy's doc.
Protocol-related features should be implemented within the same module as the protocol layers(s) (e.g., traceroute()
is implemented in scapy/layers/inet.py
).
Other features may be implemented in a module (scapy/modules
) or a contribution (scapy/contrib
).
If you contribute to Scapy's core (e.g., scapy/base_classes.py
, scapy/packet.py
, etc.), please be very careful with performances and memory footprint, as it is easy to write Python code that wastes memory or CPU cycles.
As an example, Packet().__init__()
is called each time a layer is parsed from a string (during a network capture or a PCAP file read). Adding inefficient code here will have a disastrous effect on Scapy's performances.
Scapy has an internal logging system based on logging
.
In the past, Scapy was generally too verbose on packet dissection, leading many new users to disable all logs, which makes it harder for them to find real issues afterwards. You should comply with these guidelines to make sure logging in Scapy remains helpful.
scapy.error.log_interactive
. You are free to use any log level.scapy.error.log_runtime
.logging.INFO
level, unless the issue is critical or tied to security. For instance: “DNS Decompression loop detected !” is allowed as WARNING, but “Could not dissect packet” or “Invalid value detected” are not.scapy.error.log_loading
only while Scapy is loading, to display import errors for instance.The project aims to provide code that works both on Python 2 and Python 3. Therefore, some rules need to be applied to achieve compatibility:
b"\x00\x01\x02"
except SomeError as e:
lambda x, y: x + f(y)
instead of lambda (x, y): x + f(y)
.__bool__ = __nonzero__
must be used when declaring __nonzero__
methods__next__ = next
must be used when declaring next
methods in iteratorsStopIteration
must NOT be used in generators (but it can still be used in iterators)io.BytesIO
must be used instead of StringIO
when using bytes__cmp__
must not be used.Maintainers tend to be picky, and you might feel frustrated that your code (which is perfectly working in your use case) is not merged faster.
Please don't be offended, and keep in mind that maintainers are concerned about code maintainability and readability, commit history (we use the history a lot, for example to find regressions or understand why certain decisions have been made), performances, integration in Scapy, API consistency (so that someone who knows how to use Scapy will know how to use your code), etc.
Thanks for reading, happy hacking!