Package: avast.betterproto
Avast forkThis is an Avast fork that we use to get stuff released quicker so we can use it
in our projects.Our package is released from the branchavast/release. This branch contains
changes that are necessary for our release. Most often, it will be based on themasterbranch of theupstreamremote (the original repo). If we need to
release some custom changes, those will be done in another branch andavast/releasewill be rebased onto it. This will require
a lot of force pushing - if you want to work withavast/release, you are on
your own.How to work with this repoThis fork was setup usingthis how-to
guide.Before you start work:# This will synchronize upstream/master (original repo) and origin/master (our fork)
git fetch --all --prune
git checkout master
git merge upstream/master --ff-only
git push origin masterIf you want to propose a change to the upstream:git checkout -b fix/small-bug
# Commit some work
git push -u origin fix/small-bug
# Create a Pull RequestIf you want to release our package with the change:git checkout avast/release
git rebase fix/small-bug
# Raise version in pyproject.toml
git push -f  # This will run testing Github actions
git tag -a v0.1.0  # Add any comments into the annotation
git push --tags  # This will trigger the release to PyPIBetter Protobuf / gRPC Support for Python:octocat: If you're reading this on github, please be aware that it might mention unreleased features! See the latest released README onpypi.This project aims to provide an improved experience when using Protobuf / gRPC in a modern Python environment by making use of modern language features and generating readable, understandable, idiomatic Python code. It will not support legacy features or environments (e.g. Protobuf 2). The following are supported:Protobuf 3 & gRPC code generationBoth binary & JSON serialization is built-inPython 3.6+ making use of:EnumsDataclassesasync/awaitTimezone-awaredatetimeandtimedeltaobjectsRelative importsMypy type checkingThis project is heavily inspired by, and borrows functionality from:https://github.com/protocolbuffers/protobuf/tree/master/pythonhttps://github.com/eigenein/protobuf/https://github.com/vmagamedov/grpclibMotivationThis project exists because I am unhappy with the state of the official Google protoc plugin for Python.Noasyncsupport (requires additionalgrpclibplugin)No typing support or code completion/intelligence (requires additionalmypyplugin)No__init__.pymodule files get generatedOutput is not importableImport paths break in Python 3 unless you mess withsys.pathBugs when names clash (e.g.codecspackage)Generated code is not idiomaticCompletely unreadable runtime code-generationMuch code looks like C++ or Java ported 1:1 to PythonCapitalized function names likeHasField()andSerializeToString()UsesSerializeToString()rather than the built-in__bytes__()Special wrapped types don't use Python'sNoneTimestamp/duration types don't use Python's built-indatetimemodule
This project is a reimplementation from the ground up focused on idiomatic modern Python to help fix some of the above. While it may not be a 1:1 drop-in replacement due to changed method names and call patterns, the wire format is identical.InstallationFirst, install the package. Note that the[compiler]feature flag tells it to install extra dependencies only needed by theprotocplugin:# Install both the library and compilerpipinstall"betterproto[compiler]"# Install just the library (to use the generated code output)pipinstallbetterprotoBetterprotois under active development. To install the latest beta version, usepip install --pre betterproto.Getting StartedCompiling proto filesNow, given you installed the compiler and have a proto file, e.gexample.proto:syntax="proto3";packagehello;// Greeting represents a message you can tell a user.messageGreeting{stringmessage=1;}You can run the following to invoke protoc directly:mkdirlib
protoc-I.--python_betterproto_out=libexample.protoor run the following to invoke protoc via grpcio-tools:pipinstallgrpcio-tools
python-mgrpc_tools.protoc-I.--python_betterproto_out=libexample.protoThis will generatelib/hello/__init__.pywhich looks like:# Generated by the protocol buffer compiler.  DO NOT EDIT!# sources: example.proto# plugin: python-betterprotofromdataclassesimportdataclassimportbetterproto@dataclassclassGreeting(betterproto.Message):"""Greeting represents a message you can tell a user."""message:str=betterproto.string_field(1)Now you can use it!>>>fromlib.helloimportGreeting>>>test=Greeting()>>>testGreeting(message='')>>>test.message="Hey!">>>testGreeting(message="Hey!")>>>serialized=bytes(test)>>>serializedb'\n\x04Hey!'>>>another=Greeting().parse(serialized)>>>anotherGreeting(message="Hey!")>>>another.to_dict(){"message":"Hey!"}>>>another.to_json(indent=2)'{\n"message": "Hey!"\n}'Async gRPC SupportThe generated ProtobufMessageclasses are compatible withgrpclibso you are free to use it if you like. That said, this project also includes support for async gRPC stub generation with better static type checking and code completion support. It is enabled by default.Given an example service definition:syntax="proto3";packageecho;messageEchoRequest{stringvalue=1;// Number of extra times to echouint32extra_times=2;}messageEchoResponse{repeatedstringvalues=1;}messageEchoStreamResponse{stringvalue=1;}serviceEcho{rpcEcho(EchoRequest)returns(EchoResponse);rpcEchoStream(EchoRequest)returns(streamEchoStreamResponse);}Generate echo proto file:python -m grpc_tools.protoc -I . --python_betterproto_out=. echo.protoA client can be implemented as follows:importasyncioimportechofromgrpclib.clientimportChannelasyncdefmain():channel=Channel(host="127.0.0.1",port=50051)service=echo.EchoStub(channel)response=awaitservice.echo(value="hello",extra_times=1)print(response)asyncforresponseinservice.echo_stream(value="hello",extra_times=1):print(response)# don't forget to close the channel when done!channel.close()if__name__=="__main__":loop=asyncio.get_event_loop()loop.run_until_complete(main())which would outputEchoResponse(values=['hello','hello'])EchoStreamResponse(value='hello')EchoStreamResponse(value='hello')This project also produces server-facing stubs that can be used to implement a Python
gRPC server.
To use them, simply subclass the base class in the generated files and override the
service methods:importasynciofromechoimportEchoBase,EchoResponse,EchoStreamResponsefromgrpclib.serverimportServerfromtypingimportAsyncIteratorclassEchoService(EchoBase):asyncdefecho(self,value:str,extra_times:int)->"EchoResponse":returnEchoResponse([valuefor_inrange(extra_times)])asyncdefecho_stream(self,value:str,extra_times:int)->AsyncIterator["EchoStreamResponse"]:for_inrange(extra_times):yieldEchoStreamResponse(value)asyncdefmain():server=Server([EchoService()])awaitserver.start("127.0.0.1",50051)awaitserver.wait_closed()if__name__=='__main__':loop=asyncio.get_event_loop()loop.run_until_complete(main())JSONBoth serializing and parsing are supported to/from JSON and Python dictionaries using the following methods:Dicts:Message().to_dict(),Message().from_dict(...)JSON:Message().to_json(),Message().from_json(...)For compatibility the default is to convert field names tocamelCase. You can control this behavior by passing a casing value, e.g:MyMessage().to_dict(casing=betterproto.Casing.SNAKE)Determining if a message was sentSometimes it is useful to be able to determine whether a message has been sent on the wire. This is how the Google wrapper types work to let you know whether a value is unset, set as the default (zero value), or set as something else, for example.Usebetterproto.serialized_on_wire(message)to determine if it was sent. This is a little bit different from the official Google generated Python code, and it lives outside the generatedMessageclass to prevent name clashes. Note that itonlysupports Proto 3 and thus canonlybe used to check ifMessagefields are set. You cannot check if a scalar was sent on the wire.# Old way (official Google Protobuf package)>>>mymessage.HasField('myfield')# New way (this project)>>>betterproto.serialized_on_wire(mymessage.myfield)One-of SupportProtobuf supports grouping fields in aoneofclause. Only one of the fields in the group may be set at a given time. For example, given the proto:syntax="proto3";messageTest{oneoffoo{boolon=1;int32count=2;stringname=3;}}You can usebetterproto.which_one_of(message, group_name)to determine which of the fields was set. It returns a tuple of the field name and value, or a blank string andNoneif unset.>>>test=Test()>>>betterproto.which_one_of(test,"foo")["",None]>>>test.on=True>>>betterproto.which_one_of(test,"foo")["on",True]# Setting one member of the group resets the others.>>>test.count=57>>>betterproto.which_one_of(test,"foo")["count",57]>>>test.onFalse# Default (zero) values also work.>>>test.name="">>>betterproto.which_one_of(test,"foo")["name",""]>>>test.count0>>>test.onFalseAgain this is a little different than the official Google code generator:# Old way (official Google protobuf package)>>>message.WhichOneof("group")"foo"# New way (this project)>>>betterproto.which_one_of(message,"group")["foo","foo's value"]Well-Known Google TypesGoogle provides several well-known message types like a timestamp, duration, and several wrappers used to provide optional zero value support. Each of these has a special JSON representation and is handled a little differently from normal messages. The Python mapping for these is as follows:Google MessagePython TypeDefaultgoogle.protobuf.durationdatetime.timedelta0google.protobuf.timestampTimezone-awaredatetime.datetime1970-01-01T00:00:00Zgoogle.protobuf.*ValueOptional[...]Nonegoogle.protobuf.*betterproto.lib.google.protobuf.*NoneFor the wrapper types, the Python type corresponds to the wrapped type, e.g.google.protobuf.BoolValuebecomesOptional[bool]whilegoogle.protobuf.Int32ValuebecomesOptional[int]. All of the optional values default toNone, so don't forget to check for that possible state. Given:syntax="proto3";import"google/protobuf/duration.proto";import"google/protobuf/timestamp.proto";import"google/protobuf/wrappers.proto";messageTest{google.protobuf.BoolValuemaybe=1;google.protobuf.Timestampts=2;google.protobuf.Durationduration=3;}You can do stuff like:>>>t=Test().from_dict({"maybe":True,"ts":"2019-01-01T12:00:00Z","duration":"1.200s"})>>>tTest(maybe=True,ts=datetime.datetime(2019,1,1,12,0,tzinfo=datetime.timezone.utc),duration=datetime.timedelta(seconds=1,microseconds=200000))>>>t.ts-t.durationdatetime.datetime(2019,1,1,11,59,58,800000,tzinfo=datetime.timezone.utc)>>>t.ts.isoformat()'2019-01-01T12:00:00+00:00'>>>t.maybe=None>>>t.to_dict(){'ts':'2019-01-01T12:00:00Z','duration':'1.200s'}DevelopmentJoin us onSlack!See how you can help →ContributingRequirementsPython (3.6 or higher)poetryNeeded to install dependencies in a virtual environmentpoethepoetfor running development tasks as defined in pyproject.tomlCan be installed to your host environment viapip install poethepoetthen executed as simplepoeor run from the poetry venv aspoetry run poeSetup# Get set up with the virtual env & dependenciespoetryrunpipinstall--upgradepip
poetryinstall# Activate the poetry environmentpoetryshellCode styleThis project enforcesblackpython code formatting.Before committing changes run:poeformatTo avoid merge conflicts later, non-black formatted python code will fail in CI.TestsThere are two types of tests:Standard testsCustom testsStandard testsAdding a standard test case is easy.Create a new directorybetterproto/tests/inputs/<name>add<name>.protowith a message calledTestadd<name>.jsonwith some test data (optional)It will be picked up automatically when you run the tests.See also:Standard Tests Development GuideCustom testsCustom tests are found intests/test_*.pyand are run with pytest.RunningHere's how to run the tests.# Generate assets from sample .proto files required by the testspoegenerate# Run the testspoetestTo run tests as they are run in CI (with tox) run:poefull-test(Re)compiling Google Well-known TypesBetterproto includes compiled versions for Google's well-known types atbetterproto/lib/google.
Be sure to regenerate these files when modifying the plugin output format, and validate by running the tests.Normally, the plugin does not compile any references togoogle.protobuf, since they are pre-compiled. To force compilation ofgoogle.protobuf, use the option--custom_opt=INCLUDE_GOOGLE.Assuming yourgoogle.protobufsource files (included with all releases ofprotoc) are located in/usr/local/include, you can regenerate them as follows:protoc\--plugin=protoc-gen-custom=src/betterproto/plugin/main.py\--custom_opt=INCLUDE_GOOGLE\--custom_out=src/betterproto/lib\-I/usr/local/include/\/usr/local/include/google/protobuf/*.protoTODOFixed length fieldsPacked fixed-lengthZig-zag signed fields (sint32, sint64)Don't encode zero values for nested typesEnumsRepeated message fieldsMapsMaps of message fieldsSupport passthrough of unknown fieldsRefs to nested typesImports in proto filesWell-known Google typesSupport as request inputSupport as response outputAutomatically wrap/unwrap responsesOneOf supportBasic support on the wireCheck which was set from the groupSetting one unsets the othersJSON that isn't completely naive.64-bit ints as stringsMapsListsBytes as base64Any supportEnum stringsWell known types support (timestamp, duration, wrappers)Support different casing (orig vs. camel vs. others?)Async service stubsUnary-unaryServer streaming responseClient streaming requestRenaming messages and fields to conform to Python name standardsRenaming clashes with language keywordsPython packageAutomate running testsCleanup!CommunityJoin us onSlack!LicenseCopyright © 2019 Daniel G. Taylorhttp://dgt.mit-license.org/