LibCppBor provides a natural and easy-to-use syntax for constructing and parsing CBOR messages. It does not (yet) support all features of CBOR, nor (yet) support validation against CDDL schemata, though both are planned. CBOR features that aren't supported include:
LibCppBor requires C++-17.
LibCppBor represents CBOR data items as instances of the
Item class or, more precisely, as instances of subclasses of
Item is a pure interface. The subclasses of
Item correspond almost one-to-one with CBOR major types, and are named to match the CDDL names to which they correspond. They are:
Uintcorresponds to major type 0, and can hold unsigned integers up through (2^64 - 1).
Nintcorresponds to major type 1. It can only hold values from -1 to -(2^63 - 1), since it‘s internal representation is an int64_t. This can be fixed, but it seems unlikely that applications will need the omitted range from -(2^63) to (2^64 - 1), since it’s inconvenient to represent them in many programming languages.
Intis an abstract base of
Nintthat facilitates working with all signed integers representable with int64_t.
Bstrcorresponds to major type 2, a byte string.
Tstrcorresponds to major type 3, a text string.
Arraycorresponds to major type 4, an Array. It holds a variable-length array of
Mapcorresponds to major type 5, a Map. It holds a variable-length array of pairs of
Simplecorresponds to major type 7. It's an abstract class since items require more specific type.
Boolis the only currently-implemented subclass of
Note that major type 6, semantic tag, is not yet implemented.
In practice, users of LibCppBor will rarely use most of these classes when generating CBOR encodings. This is because LibCppBor provides straightforward conversions from the obvious normal C++ types. Specifically, the following conversions are provided in appropriate contexts:
Nint, as appropriate.
std::pair<char iterator, char iterator>convert to
std::pair<uint8_t iterator, uint8_t iterator>and
std::pair<uint8_t*, size_t>convert to
The set of
encode methods in
Item provide the interface for producing encoded CBOR. The basic process for “complete tree” generation (as opposed to “incremental” generation, which is discussed below) is to construct an
Item which models the data to be encoded, and then call one of the
encode methods, whichever is convenient for the encoding destination. A trivial example:
cppbor::Uint val(0); std::vector<uint8_t> encoding = val.encode();
It's relatively rare that single values are encoded as above. More often, the "root" data item will be an `Array` or `Map` which contains a more complex structure.For example :
using cppbor::Array; std::vector<uint8_t> vec = // ... Map val("key1", Array(Map("key_a", 99 "key_b", vec), "foo"), "key2", true); std::vector<uint8_t> encoding = val.encode();
This creates a map with two entries, with
Tstr keys “Outer1” and “Outer2”, respectively. The “Outer1” entry has as its value an
Array containing a
Map and a
Tstr. The “Outer2” entry has a
This example demonstrates how automatic conversion of C++ types to LibCppBor
Item subclass instances is done. Where the caller provides a C++ or C string, a
Tstr entry is added. Where the caller provides an integer literal or variable, a
Nint is added, depending on whether the value is positive or negative.
As an alternative, a more fluent-style API is provided for building up structures. For example:
using cppbor::Map; using cppbor::Array; std::vector<uint8_t> vec = // ... Map val(); val.add("key1", Array().add(Map().add("key_a", 99).add("key_b", vec)).add("foo")).add("key2", true); std::vector<uint8_t> encoding = val.encode();
An advantage of this interface over the constructor - based creation approach above is that it need not be done all at once. The `add` methods return a reference to the object added to to allow calls to be chained, but chaining is not necessary; calls can be made sequentially, as the data to add is available.
There are several variations of
Item::encode, all of which accomplish the same task but output the encoded data in different ways, and with somewhat different performance characteristics. The provided options are:
bool encode(uint8\_t** pos, const uint8\_t* end)encodes into the buffer referenced by the range [
*posis moved. If the encoding runs out of buffer space before finishing, the method returns false. This is the most efficient way to encode, into an already-allocated buffer.
void encode(EncodeCallback encodeCallback)calls
encodeCallbackfor each encoded byte. It's the responsibility of the implementor of the callback to behave safely in the event that the output buffer (if applicable) is exhausted. This is less efficient than the prior method because it imposes an additional function call for each byte.
template </*...*/> void encode(OutputIterator i)encodes into the provided iterator. SFINAE ensures that the template doesn't match for non-iterators. The implementation actually uses the callback-based method, plus has whatever overhead the iterator adds.
std::vector<uint8_t> encode()creates a new std::vector, reserves sufficient capacity to hold the encoding, and inserts the encoded bytes with a std::pushback_iterator and the previous method.
std::string toString()does the same as the previous method, but returns a string instead of a vector.
Incremental generation requires deeper understanding of CBOR, because the library can't do as much to ensure that the output is valid. The basic tool for intcremental generation is the
encodeHeader function. There are two variations, one which writes into a buffer, and one which uses a callback. Both simply write out the bytes of a header. To construct the same map as in the above examples, incrementally, one might write:
using namespace cppbor; // For example brevity std::vector encoding; auto iter = std::back_inserter(result); encodeHeader(MAP, 2 /* # of map entries */, iter); std::string s = "key1"; encodeHeader(TSTR, s.size(), iter); std::copy(s.begin(), s.end(), iter); encodeHeader(ARRAY, 2 /* # of array entries */, iter); Map().add("key_a", 99).add("key_b", vec).encode(iter) s = "foo"; encodeHeader(TSTR, foo.size(), iter); std::copy(s.begin(), s.end(), iter); s = "key2"; encodeHeader(TSTR, foo.size(), iter); std::copy(s.begin(), s.end(), iter); encodeHeader(SIMPLE, TRUE, iter);
As the above example demonstrates, the styles can be mixed -- Note the creation and encoding of the inner Map using the fluent style.
LibCppBor also supports parsing of encoded CBOR data, with the same feature set as encoding. There are two basic approaches to parsing, “full” and “stream”
Full parsing means completely parsing a (possibly-compound) data item from a byte buffer. The
parse functions that do not take a
ParseClient pointer do this. They return a
ParseResult which is a tuple of three values:
Assuming a successful parse, you can then use
Item::type() to discover the type of the parsed item (e.g. MAP), and then use the appropriate
Item::as*() method (e.g.
Item::asMap()) to get a pointer to an interface which allows you to retrieve specific values.
Stream parsing is more complex, but more flexible. To use StreamParsing, you must create your own subclass of
ParseClient and call one of the
parse functions that accepts it. See the
ParseClient methods docstrings for details.
One unusual feature of stream parsing is that the
ParseClient callback methods not only provide the parsed Item, but also pointers to the portion of the buffer that encode that Item. This is useful if, for example, you want to find an element inside of a structure, and then copy the encoding of that sub-structure, without bothering to parse the rest.
The full parser is implemented with the stream parser.
This is not an officially supported Google product