The gpb is a compiler for Google protocol buffer definitions files for Erlang.

See https://code.google.com/p/protobuf/ for further information on the Google protocol buffers.

Features of gpb

• Parses protocol buffer definition files and can generate:

  • record defintions, one record for each message
  • erlang code for encoding/decoding the messages to/from binaries

• Features of the protocol buffer definition files: gpb supports:

  • message definitions (also messages in messages)
  • scalar types
  • importing other proto files
  • nested types
  • message extensions
  • the 'packed' and 'default' options
  • generating metadata information
  • package namespacing (optional)

  gpb reads but ignores or throws away:

  • options other than 'packed' or 'default'
  • custom options

  gpb does not support:

  • groups
  • aggregate custom options introduced in protobuf 2.4.0
  • descriptors
  • rpc

• Characteristics of gpb:

  • Skipping over unknown message fields, when decoding, is supported
  • Merging of messages, also recursive merging, is supported
  • Gpb can optionally generate code for verification of values during encoding this makes it easy to catch e.g integers out of range, or values of the wrong type.
  • Gpb can optionally or conditionally copying the contents of 'bytes' fields, in order to let the runtime system free the larger message binary.
  • Gpb can optionally make use of the package attribute by prepending the name of the package to every contained message type (if defined), which is useful to avoid name clashes of message types across packages.
  • The generated encode/decoder has no run-time dependency to gpb, but there is normally a compile-time dependency for the generated code: to the #field{} record in gpb.hrl the for the get_msg_defs function, but it is possible to avoid this dependency by using the also the defs_as_proplists or -pldefs option.
  • Gpb can generate code both to files and to binaries.

• Introspection

  gpb generates some functions for examining messages, enums and services:

  • get_msg_defs(), get_msg_names(), get_enum_names()
  • find_msg_def(MsgName) and fetch_msg_def(MsgName)
  • find_enum_def(MsgName) and fetch_enum_def(MsgName)
  • enum_symbol_by_value(EnumName, Value),
  • enum_symbol_by_value_<EnumName>(Value), enum_value_by_symbol(EnumName, Enum) and enum_value_by_symbol_<EnumName>(Enum)
  • get_service_names(), get_service_def(ServiceName), get_rpc_names(ServiceName)
  • find_rpc_def(ServiceName, RpcName), fetch_rpc_def(ServiceName, RpcName)

  There are also some version information functions:

  • gpb:version_as_string() and gpb:version_as_list()
  • GeneratedCode:version_as_string() and GeneratedCode:version_as_list()
  • ?gpb_version (in gpb_version.hrl)
  • ?'GeneratedCode_gpb_version' (in GeneratedCode.hrl) The gpb can also generate a self-description of the proto file. The self-description is a description of the proto file, encoded to a binary using the descriptor.proto that comes with the Google protocol buffers library. Note that such an encoded self-descriptions won't be byte-by-byte identical to what the Google protocol buffers compiler will generate for the same proto, but should be roughly equivalent. * Erroneously encoded protobuf messages and fields will generally cause the decoder to crash. Examples of such erroneous encodings are: - varints with too many bits - strings, bytes, sub messages or packed repeated fields, where the encoded length is longer than the remaining binary * Maps (NB: currently experimental!) Gpb can generate encoders/decoders for maps, in accordance with EEP 43. NB: This is still at an experimental stage, and details may change. The general plan here is to wait until maps gets supported in Erlang/OTP (as of this writing, it appears to be still some months away), then experiment and benchmark a bit before settling for a design. Open questions in this area: (a) should non-present optional fields be represented as#{key => undefined}or should the binding be omitted altogether? Also (b), should there be someidbinding, representing the name of the message? Further: (c) decode: pass maps, or pass records around and convert to maps as a final step? Need to evaluate performance. * Reporting of errors in .proto files Gpb is not very good at error reporting, especially referencing errors, such as references to messages that are not defined. You might want to first verify withprotocthat the .proto files are valid before feeding them to gpb. * Caveats The gpb does accept reserved words as names for fields (just like protoc does), but not as names for messages. To correct this, one would have to either rewrite the grammar, or stop using yecc. (maybe rewrite it all as a protoc plugin?) The gpb will fail to decode floats that are NaN, +Inf and -Inf, and there is no possibility to encode such floats. Performance ----------- Here is a comparison between gpb (interpreted by the erlang vm) and the C++, Python and Java serializers/deserializers of protobuf-2.4.1 [MB/s] | gpb |pb/c++ |pb/c++ | pb/c++ | pb/py |pb/java| pb/java| | |(speed)|(size) | (lite) | |(size) | (speed)| --------------+-------+-------+-------+--------+-------+-------+--------+ small msgs | | | | | | | | serialize | 27.56 | 479.9 | 31.81 | 302.8 | 3.09 | 27.08 | 547.9 | deserialize | 27.30 | 269.8 | 28.16 | 381.7 | 2.49 | 32.00 | 325.1 | --------------+-------+-------+-------+--------+-------+-------+--------+ large msgs | | | | | | | | serialize | 18.83 | 447.7 | 26.87 | 284.8 | 2.20 | 24.82 | 314.2 | deserialize | 24.39 | 269.6 | 24.69 | 337.2 | 1.74 | 17.93 | 215.0 | --------------+-------+-------+-------+--------+-------+-------+--------+ The performances are measured as number of processed MB/s, serialized form. Higher values means better performance. The benchmarks are run with small and large messages (228 and 84584 bytes, respectively, in serialized form) The Java benchmark is run with optimization both for code size and for speed. The Python implementation cannot optimize for speed. SW: Python 2.6.6, Java SE 1.6.0_22, Erlang/OTP R16B01, g++ 4.6.1 Linux kernel 3.10, Debian, protobuf-2.4.1, HW: Intel Core i5 760, 2.8GHz, 4x256 kB L2 cache, 8MB L3 cache (Turbo boost turned off, CPU frequency pinned to 2.8 GHz) The benchmarks are all done with the exact same messages files and proto files. The source of the benchmarks was found in the Google protobuf's svn repository. The gpb does not support groups, but the benchmarks in the protobuf used groups, so I converted the google_message*.dat to use sub message structures instead. For protobuf, that change was only barely noticable. For performance, the generated Erlang code avoids creating sub binaries as far as possible. It has to for sub messages, strings and bytes, but for the rest of the types, it avoids creating sub binaries, both during encoding and decoding (for info, compile with thebin_opt_infooption) The Erlang code ran in the smp emulator, though only one CPU core was utilized. The generated C++ core was compiled with -O3. Mapping of protocol buffer datatypes to erlang ---------------------------------------------- .proto type Erlang type ---------------------------------------------------------------- double, float floating point number when encoding, integers, too, are accepted ---------------------------------------------------------------- int32, int64, uint32, uint64, sint32, sint64, fixed32, fixed64, sfixed32, sfixed64 integer ---------------------------------------------------------------- bool true | false ---------------------------------------------------------------- enum atom ---------------------------------------------------------------- message record (thus tuple) ---------------------------------------------------------------- string unicode string, thus list of integers ---------------------------------------------------------------- bytes binary Interaction with rebar ---------------------- Place the .proto files for instance in aproto/subdirectory. Any subdirectory, other than src/, is fine, since rebar will try to use another protobuf compiler for any .proto it finds in the src/ subdirectory. Here are some some lines for therebar.configfile: %% -*- erlang -*- {pre_hooks, [{compile, "mkdir -p include"}, %% ensure the include dir exists {compile, "/path/to/gpb/bin/protoc-erl -Ipwd/proto" "-o-erl src -o-hrl includepwd/proto/*.proto" }]}. {post_hooks, [{clean, "bash -c 'for f in proto/*.proto; " "do " " rm -f src/$(basename $f .proto).erl; " " rm -f include/$(basename $f .proto).hrl; " "done'"} ]}. {erl_opts, [{i, "/path/to/gpb/include"}]}. Version numbering ----------------- The gpb version number is fetched from the git latest git tag matching N.M where N and M are integers. This version is inserted into the gpb.app file as well as into the include/gpb_version.hrl. The version is the result of the command git describe --always --tags --match '[0-9]*.[0-9]*' Thus, to create a new version of gpb, the single source from where this version is fetched, is the git tag. (If you are importing gpb into another version control system than git, or using another build tool than rebar, you might have to adapt rebar.config and src/gpb.app.src accordingly.) The version number of the gpb on github is intended to always be only integers with dots, in order to be compatible with reltool. In other words, each push to github is considered a release, and the version number is bumped. To ensure this, there is apre-pushgit hook and two scripts,install-git-hooksandtag-next-minor-vsn`, in the helpers subdirectory. The ChangeLog file will not necessarily reflect all minor version bumps, only important updates. Places to update when making a new version: Write about the changes in the ChangeLog file, if it is a non-minor version bump. tag it in git Contributing ------------ Contributions are welcome, preferrably as pull requests or git patches or git fetch requests. Here are some guide lines: Use only spaces for indentation, no tabs The code must fit 80 columns Verify that the code and documentation compiles and that tests are ok: rebar clean compile eunit doc xref If you add a feature, test cases are most welcome, so that the feature won't get lost in any future refactorization * Use a git branch for your feature. This way, the git history will look better in case there is need to refetch.