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35
.gitea/workflows/release.yml
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name: Release
run-name: ${{ gitea.actor }} is runs ci pipeline
on:
push:
branches:
- master
jobs:
packaging:
name: Distribution
runs-on: ubuntu-latest
env:
EXT_FIX: "6"
steps:
- uses: actions/checkout@v4
- name: Set up Python 3.9
uses: actions/setup-python@v5
with:
python-version: '3.9'
- name: Install poetry
run: python -m pip install poetry chardet
- name: Install poetry compiler
run: poetry install -E compiler
- name: Set poetry version
run: PV=$(poetry version -s) && poetry version ${PV}+jar3b${EXT_FIX}
- name: Build package
run: poetry build
- name: Add pypi source
run: poetry source add --priority=supplemental ahax https://git.ahax86.ru/api/packages/pub/pypi
- name: Add pypi credentials
run: poetry config http-basic.ahax ${{ secrets.REPO_USER }} ${{ secrets.REPO_PASS }}
- name: Push to pypi
run: poetry publish -r ahax -u ${{ secrets.REPO_USER }} -p ${{ secrets.REPO_PASS }} -n

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.github/CONTRIBUTING.md vendored
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# Contributing
There's lots to do, and we're working hard, so any help is welcome!
- :speech_balloon: Join us on [Discord](https://discord.gg/DEVteTupPb)!
What can you do?
- :+1: Vote on [issues](https://github.com/danielgtaylor/python-betterproto/issues).
- :speech_balloon: Give feedback on [Pull Requests](https://github.com/danielgtaylor/python-betterproto/pulls) and [Issues](https://github.com/danielgtaylor/python-betterproto/issues):
- Suggestions
- Express approval
- Raise concerns
- :small_red_triangle: Create an issue:
- File a bug (please check its not a duplicate)
- Propose an enhancement
- :white_check_mark: Create a PR:
- [Creating a failing test-case](https://github.com/danielgtaylor/python-betterproto/blob/master/tests/README.md) to make bug-fixing easier
- Fix any of the open issues
- [Good first issues](https://github.com/danielgtaylor/python-betterproto/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
- [Issues with tests](https://github.com/danielgtaylor/python-betterproto/issues?q=is%3Aissue+is%3Aopen+label%3A%22has+test%22)
- New bugfix or idea
- If you'd like to discuss your idea first, join us on Discord!

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.github/ISSUE_TEMPLATE/bug_report.yml vendored
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name: Bug Report
description: Report broken or incorrect behaviour
labels: ["bug", "investigation needed"]
body:
- type: markdown
attributes:
value: >
Thanks for taking the time to fill out a bug report!
If you're not sure it's a bug and you just have a question, the [community Discord channel](https://discord.gg/DEVteTupPb) is a better place for general questions than a GitHub issue.
- type: input
attributes:
label: Summary
description: A simple summary of your bug report
validations:
required: true
- type: textarea
attributes:
label: Reproduction Steps
description: >
What you did to make it happen.
Ideally there should be a short code snippet in this section to help reproduce the bug.
validations:
required: true
- type: textarea
attributes:
label: Expected Results
description: >
What did you expect to happen?
validations:
required: true
- type: textarea
attributes:
label: Actual Results
description: >
What actually happened?
validations:
required: true
- type: textarea
attributes:
label: System Information
description: >
Paste the result of `protoc --version; python --version; pip show betterproto` below.
validations:
required: true
- type: checkboxes
attributes:
label: Checklist
options:
- label: I have searched the issues for duplicates.
required: true
- label: I have shown the entire traceback, if possible.
required: true
- label: I have verified this issue occurs on the latest prelease of betterproto which can be installed using `pip install -U --pre betterproto`, if possible.
required: true

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.github/ISSUE_TEMPLATE/config.yml vendored
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@ -1,6 +0,0 @@
name:
description:
contact_links:
- name: For questions about the library
about: Support questions are better answered in our Discord group.
url: https://discord.gg/DEVteTupPb

49
.github/ISSUE_TEMPLATE/feature_request.yml vendored
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name: Feature Request
description: Suggest a feature for this library
labels: ["enhancement"]
body:
- type: input
attributes:
label: Summary
description: >
What problem is your feature trying to solve? What would become easier or possible if feature was implemented?
validations:
required: true
- type: dropdown
attributes:
multiple: false
label: What is the feature request for?
options:
- The core library
- RPC handling
- The documentation
validations:
required: true
- type: textarea
attributes:
label: The Problem
description: >
What problem is your feature trying to solve?
What would become easier or possible if feature was implemented?
validations:
required: true
- type: textarea
attributes:
label: The Ideal Solution
description: >
What is your ideal solution to the problem?
What would you like this feature to do?
validations:
required: true
- type: textarea
attributes:
label: The Current Solution
description: >
What is the current solution to the problem, if any?
validations:
required: false

16
.github/PULL_REQUEST_TEMPLATE.md vendored
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## Summary
<!-- What is this pull request for? Does it fix any issues? -->
## Checklist
<!-- Put an x inside [ ] to check it, like so: [x] -->
- [ ] If code changes were made then they have been tested.
- [ ] I have updated the documentation to reflect the changes.
- [ ] This PR fixes an issue.
- [ ] This PR adds something new (e.g. new method or parameters).
- [ ] This change has an associated test.
- [ ] This PR is a breaking change (e.g. methods or parameters removed/renamed)
- [ ] This PR is **not** a code change (e.g. documentation, README, ...)

78
.github/workflows/ci.yml vendored
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@ -1,65 +1,23 @@
name: CI
on:
push:
branches:
- master
pull_request:
branches:
- '**'
on: [push, pull_request]
jobs:
tests:
name: ${{ matrix.os }} / ${{ matrix.python-version }}
runs-on: ${{ matrix.os }}-latest
strategy:
fail-fast: false
matrix:
os: [Ubuntu, MacOS, Windows]
python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Get full Python version
id: full-python-version
shell: bash
run: echo "version=$(python -c "import sys; print('-'.join(str(v) for v in sys.version_info))")" >> "$GITHUB_OUTPUT"
- name: Install poetry
shell: bash
run: |
python -m pip install poetry
echo "$HOME/.poetry/bin" >> $GITHUB_PATH
- name: Configure poetry
shell: bash
run: poetry config virtualenvs.in-project true
- name: Set up cache
uses: actions/cache@v4
id: cache
with:
path: .venv
key: venv-${{ runner.os }}-${{ steps.full-python-version.outputs.version }}-${{ hashFiles('**/poetry.lock') }}
- name: Ensure cache is healthy
if: steps.cache.outputs.cache-hit == 'true'
shell: bash
run: poetry run pip --version >/dev/null 2>&1 || rm -rf .venv
- name: Install dependencies
shell: bash
run: poetry install -E compiler
- name: Generate code from proto files
shell: bash
run: poetry run python -m tests.generate -v
- name: Execute test suite
shell: bash
run: poetry run python -m pytest tests/
- uses: actions/checkout@v1
- uses: actions/setup-python@v1
with:
python-version: 3.7
- uses: dschep/install-pipenv-action@v1
- name: Install dependencies
run: |
sudo apt install protobuf-compiler
pipenv install --dev
- name: Run tests
run: |
pipenv run generate
pipenv run test

18
.github/workflows/code-quality.yml vendored
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@ -1,18 +0,0 @@
name: Code Quality
on:
push:
branches:
- master
pull_request:
branches:
- '**'
jobs:
check-formatting:
name: Check code/doc formatting
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
- uses: pre-commit/action@v3.0.1

46
.github/workflows/codeql-analysis.yml vendored
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@ -1,46 +0,0 @@
name: "CodeQL"
on:
push:
branches: [ "master" ]
pull_request:
branches:
- '**'
schedule:
- cron: '19 1 * * 6'
jobs:
analyze:
name: Analyze
runs-on: ubuntu-latest
permissions:
actions: read
contents: read
security-events: write
strategy:
fail-fast: false
matrix:
language: [ 'python' ]
steps:
- name: Checkout repository
uses: actions/checkout@v4
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@v3
with:
languages: ${{ matrix.language }}
# If you wish to specify custom queries, you can do so here or in a config file.
# By default, queries listed here will override any specified in a config file.
# Prefix the list here with "+" to use these queries and those in the config file.
# Details on CodeQL's query packs refer to : https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
# queries: security-extended,security-and-quality
- name: Autobuild
uses: github/codeql-action/autobuild@v3
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@v3

31
.github/workflows/release.yml vendored
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@ -1,31 +0,0 @@
name: Release
on:
push:
branches:
- master
tags:
- '**'
pull_request:
branches:
- '**'
jobs:
packaging:
name: Distribution
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python 3.9
uses: actions/setup-python@v5
with:
python-version: 3.9
- name: Install poetry
run: python -m pip install poetry
- name: Build package
run: poetry build
- name: Publish package to PyPI
if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags')
env:
POETRY_PYPI_TOKEN_PYPI: ${{ secrets.pypi }}
run: poetry publish -n

18
.gitignore vendored
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@ -1,21 +1,13 @@
.coverage
.DS_Store
.env
.vscode/settings.json
.mypy_cache
.pytest_cache
.python-version
build/
tests/output_*
betterproto/tests/*.bin
betterproto/tests/*_pb2.py
betterproto/tests/*.py
!betterproto/tests/generate.py
!betterproto/tests/test_*.py
**/__pycache__
dist
**/*.egg-info
output
.idea
.DS_Store
.tox
.venv
.asv
venv
.devcontainer
.ruff_cache

25
.pre-commit-config.yaml
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@ -1,25 +0,0 @@
ci:
autofix_prs: false
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.9.1
hooks:
- id: ruff-format
args: ["--diff", "src", "tests"]
- id: ruff
args: ["--select", "I", "src", "tests"]
- repo: https://github.com/PyCQA/doc8
rev: 0.10.1
hooks:
- id: doc8
additional_dependencies:
- toml
- repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks
rev: v2.14.0
hooks:
- id: pretty-format-java
args: [--autofix, --aosp]
files: ^.*\.java$

17
.readthedocs.yml
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@ -1,17 +0,0 @@
version: 2
formats: []
build:
image: latest
sphinx:
configuration: docs/conf.py
fail_on_warning: false
python:
version: 3.7
install:
- method: pip
path: .
extra_requirements:
- dev

241
CHANGELOG.md
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@ -1,241 +0,0 @@
# Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
- Versions suffixed with `b*` are in `beta` and can be installed with `pip install --pre betterproto`.
## [2.0.0b7] - 2024-08-11
- **Breaking**: Support `Pydantic` v2 and dropping support for v1 [#588](https://github.com/danielgtaylor/python-betterproto/pull/588)
- **Breaking**: The attempting to access an unset `oneof` now raises an `AttributeError`
field. To see how to access `oneof` fields now, refer to [#558](https://github.com/danielgtaylor/python-betterproto/pull/558)
and [README.md](https://github.com/danielgtaylor/python-betterproto#one-of-support).
- **Breaking**: A custom `Enum` has been implemented to match the behaviour of being an open set. Any checks for `isinstance(enum_member, enum.Enum)` and `issubclass(EnumSubclass, enum.Enum)` will now return `False`. This change also has the side effect of
preventing any passthrough of `Enum` members (i.e. `Foo.RED.GREEN` doesn't work any more). See [#293](https://github.com/danielgtaylor/python-betterproto/pull/293) for more info, this fixed many bugs related to `Enum` handling.
- Add support for `pickle` methods [#535](https://github.com/danielgtaylor/python-betterproto/pull/535)
- Add support for `Struct` and `Value` types [#551](https://github.com/danielgtaylor/python-betterproto/pull/551)
- Add support for [`Rich` package](https://rich.readthedocs.io/en/latest/index.html) for pretty printing [#508](https://github.com/danielgtaylor/python-betterproto/pull/508)
- Improve support for streaming messages [#518](https://github.com/danielgtaylor/python-betterproto/pull/518) [#529](https://github.com/danielgtaylor/python-betterproto/pull/529)
- Improve performance of serializing / de-serializing messages [#545](https://github.com/danielgtaylor/python-betterproto/pull/545)
- Improve the handling of message name collisions with typing by allowing the method / type of imports to be configured.
Refer to [#582](https://github.com/danielgtaylor/python-betterproto/pull/582)
and [README.md](https://github.com/danielgtaylor/python-betterproto#configuration-typing-imports).
- Fix roundtrip parsing of `datetime`s [#534](https://github.com/danielgtaylor/python-betterproto/pull/534)
- Fix accessing unset optional fields [#523](https://github.com/danielgtaylor/python-betterproto/pull/523)
- Fix `Message` equality comparison [#513](https://github.com/danielgtaylor/python-betterproto/pull/513)
- Fix behaviour with long comment messages [#532](https://github.com/danielgtaylor/python-betterproto/pull/532)
- Add a warning when calling a deprecated message [#596](https://github.com/danielgtaylor/python-betterproto/pull/596)
## [2.0.0b6] - 2023-06-25
- **Breaking**: the minimum Python version has been bumped to `3.7` [#444](https://github.com/danielgtaylor/python-betterproto/pull/444)
- Support generating [Pydantic dataclasses](https://docs.pydantic.dev/latest/usage/dataclasses).
Pydantic dataclasses are are drop-in replacement for dataclasses in the standard library that additionally supports validation.
Pass `--python_betterproto_opt=pydantic_dataclasses` to enable this feature.
Refer to [#406](https://github.com/danielgtaylor/python-betterproto/pull/406)
and [README.md](https://github.com/danielgtaylor/python-betterproto#generating-pydantic-models) for more information.
- Added support for `@generated` marker [#382](https://github.com/danielgtaylor/python-betterproto/pull/382)
- Pull down the `include_default_values` argument to `to_json()` [#405](https://github.com/danielgtaylor/python-betterproto/pull/405)
- Pythonize input_type name in py_input_message [#436](https://github.com/danielgtaylor/python-betterproto/pull/436)
- Widen `from_dict()` to accept any `Mapping` [#451](https://github.com/danielgtaylor/python-betterproto/pull/451)
- Replace `pkg_resources` with `importlib` [#462](https://github.com/danielgtaylor/python-betterproto/pull/462)
- Fix typechecker compatiblity checks in server streaming methods [#413](https://github.com/danielgtaylor/python-betterproto/pull/413)
- Fix "empty-valued" repeated fields not being serialised [#417](https://github.com/danielgtaylor/python-betterproto/pull/417)
- Fix `dict` encoding for timezone-aware `datetimes` [#468](https://github.com/danielgtaylor/python-betterproto/pull/468)
- Fix `to_pydict()` serialization for optional fields [#495](https://github.com/danielgtaylor/python-betterproto/pull/495)
- Handle empty value objects properly [#481](https://github.com/danielgtaylor/python-betterproto/pull/481)
## [2.0.0b5] - 2022-08-01
- **Breaking**: Client and Service Stubs no longer pack and unpack the input message fields as parameters [#331](https://github.com/danielgtaylor/python-betterproto/pull/311)
Update your client calls and server handlers as follows:
Clients before:
```py
response = await service.echo(value="hello", extra_times=1)
```
Clients after:
```py
response = await service.echo(EchoRequest(value="hello", extra_times=1))
```
Servers before:
```py
async def echo(self, value: str, extra_times: int) -> EchoResponse: ...
```
Servers after:
```py
async def echo(self, echo_request: EchoRequest) -> EchoResponse:
# Use echo_request.value
# Use echo_request.extra_times
...
```
- Add `to/from_pydict()` for `Message` [#203](https://github.com/danielgtaylor/python-betterproto/pull/203)
- Format field comments also as docstrings [#304](https://github.com/danielgtaylor/python-betterproto/pull/304)
- Implement `__deepcopy__` for `Message` [#339](https://github.com/danielgtaylor/python-betterproto/pull/339)
- Run isort on compiled code [#355](https://github.com/danielgtaylor/python-betterproto/pull/355)
- Expose timeout, deadline and metadata parameters from grpclib [#352](https://github.com/danielgtaylor/python-betterproto/pull/352)
- Make `Message.__getattribute__` invisible to type checkers [#359](https://github.com/danielgtaylor/python-betterproto/pull/359)
- Fix map field edge-case [#254](https://github.com/danielgtaylor/python-betterproto/pull/254)
- Fix message text in `NotImplementedError` [#325](https://github.com/danielgtaylor/python-betterproto/pull/325)
- Fix `Message.from_dict()` in the presence of optional datetime fields [#329](https://github.com/danielgtaylor/python-betterproto/pull/329)
- Support Jinja2 3.0 to prevent version conflicts [#330](https://github.com/danielgtaylor/python-betterproto/pull/330)
- Fix overwriting top level `__init__.py` [#337](https://github.com/danielgtaylor/python-betterproto/pull/337)
- Remove deprecation warnings when fields are initialised with non-default values [#348](https://github.com/danielgtaylor/python-betterproto/pull/348)
- Ensure nested class names are converted to PascalCase [#353](https://github.com/danielgtaylor/python-betterproto/pull/353)
- Fix `Message.to_dict()` mutating the underlying Message [#378](https://github.com/danielgtaylor/python-betterproto/pull/378)
- Fix some parameters being missing from services [#381](https://github.com/danielgtaylor/python-betterproto/pull/381)
## [2.0.0b4] - 2022-01-03
- **Breaking**: the minimum Python version has been bumped to `3.6.2`
- Always add `AsyncIterator` to imports if there are services [#264](https://github.com/danielgtaylor/python-betterproto/pull/264)
- Allow parsing of messages from `ByteStrings` [#266](https://github.com/danielgtaylor/python-betterproto/pull/266)
- Add support for proto3 optional [#281](https://github.com/danielgtaylor/python-betterproto/pull/281)
- Fix compilation of fields with names identical to builtin types [#294](https://github.com/danielgtaylor/python-betterproto/pull/294)
- Fix default values for enum service args [#299](https://github.com/danielgtaylor/python-betterproto/pull/299)
## [2.0.0b3] - 2021-04-07
- Generate grpclib service stubs [#170](https://github.com/danielgtaylor/python-betterproto/pull/170)
- Add \_\_version\_\_ attribute to package [#134](https://github.com/danielgtaylor/python-betterproto/pull/134)
- Use betterproto generated messages in the plugin [#161](https://github.com/danielgtaylor/python-betterproto/pull/161)
- Sort the list of sources in generated file headers [#164](https://github.com/danielgtaylor/python-betterproto/pull/164)
- Micro-optimization: use tuples instead of lists for conditions [#228](https://github.com/danielgtaylor/python-betterproto/pull/228)
- Improve datestring parsing [#213](https://github.com/danielgtaylor/python-betterproto/pull/213)
- Fix serialization of repeated fields with empty messages [#180](https://github.com/danielgtaylor/python-betterproto/pull/180)
- Fix compilation of fields named 'bytes' or 'str' [#226](https://github.com/danielgtaylor/python-betterproto/pull/226)
- Fix json serialization of infinite and nan floats/doubles [#215](https://github.com/danielgtaylor/python-betterproto/pull/215)
- Fix template bug resulting in empty \_\_post_init\_\_ methods [#162](https://github.com/danielgtaylor/python-betterproto/pull/162)
- Fix serialization of zero-value messages in a oneof group [#176](https://github.com/danielgtaylor/python-betterproto/pull/176)
- Fix missing typing and datetime imports [#183](https://github.com/danielgtaylor/python-betterproto/pull/183)
- Fix code generation for empty services [#222](https://github.com/danielgtaylor/python-betterproto/pull/222)
- Fix Message.to_dict and from_dict handling of repeated timestamps and durations [#211](https://github.com/danielgtaylor/python-betterproto/pull/211)
- Fix incorrect routes in generated client when service is not in a package [#177](https://github.com/danielgtaylor/python-betterproto/pull/177)
## [2.0.0b2] - 2020-11-24
- Add support for deprecated message and fields [#126](https://github.com/danielgtaylor/python-betterproto/pull/126)
- Add support for recursive messages [#130](https://github.com/danielgtaylor/python-betterproto/pull/130)
- Add support for `bool(Message)` [#142](https://github.com/danielgtaylor/python-betterproto/pull/142)
- Improve support for Python 3.9 [#140](https://github.com/danielgtaylor/python-betterproto/pull/140) [#173](https://github.com/danielgtaylor/python-betterproto/pull/173)
- Improve keyword sanitisation for generated code [#137](https://github.com/danielgtaylor/python-betterproto/pull/137)
- Fix missing serialized_on_wire when message contains only lists [#81](https://github.com/danielgtaylor/python-betterproto/pull/81)
- Fix circular dependencies [#100](https://github.com/danielgtaylor/python-betterproto/pull/100)
- Fix to_dict enum fields when numbering is not consecutive [#102](https://github.com/danielgtaylor/python-betterproto/pull/102)
- Fix argument generation for stub methods when using `import` with proto definition [#103](https://github.com/danielgtaylor/python-betterproto/pull/103)
- Fix missing async/await keywords when casing [#104](https://github.com/danielgtaylor/python-betterproto/pull/104)
- Fix mutable default arguments in generated code [#105](https://github.com/danielgtaylor/python-betterproto/pull/105)
- Fix serialisation of default values in oneofs when calling to_dict() or to_json() [#110](https://github.com/danielgtaylor/python-betterproto/pull/110)
- Fix static type checking for grpclib client [#124](https://github.com/danielgtaylor/python-betterproto/pull/124)
- Fix python3.6 compatibility issue with dataclasses [#124](https://github.com/danielgtaylor/python-betterproto/pull/124)
- Fix handling of trailer-only responses [#127](https://github.com/danielgtaylor/python-betterproto/pull/127)
- Refactor plugin.py to use modular dataclasses in tree-like structure to represent parsed data [#121](https://github.com/danielgtaylor/python-betterproto/pull/121)
- Refactor template compilation logic [#136](https://github.com/danielgtaylor/python-betterproto/pull/136)
- Replace use of platform provided protoc with development dependency on grpcio-tools [#107](https://github.com/danielgtaylor/python-betterproto/pull/107)
- Switch to using `poe` from `make` to manage project development tasks [#118](https://github.com/danielgtaylor/python-betterproto/pull/118)
- Improve CI platform coverage [#128](https://github.com/danielgtaylor/python-betterproto/pull/128)
## [2.0.0b1] - 2020-07-04
[Upgrade Guide](./docs/upgrading.md)
> Several bugfixes and improvements required or will require small breaking changes, necessitating a new version.
> `2.0.0` will be released once the interface is stable.
- Add support for gRPC and **stream-stream** [#83](https://github.com/danielgtaylor/python-betterproto/pull/83)
- Switch from `pipenv` to `poetry` for development [#75](https://github.com/danielgtaylor/python-betterproto/pull/75)
- Fix two packages with the same name suffix should not cause naming conflict [#25](https://github.com/danielgtaylor/python-betterproto/issues/25)
- Fix Import child package from root [#57](https://github.com/danielgtaylor/python-betterproto/issues/57)
- Fix Import child package from package [#58](https://github.com/danielgtaylor/python-betterproto/issues/58)
- Fix Import parent package from child package [#59](https://github.com/danielgtaylor/python-betterproto/issues/59)
- Fix Import root package from child package [#60](https://github.com/danielgtaylor/python-betterproto/issues/60)
- Fix Import root package from root [#61](https://github.com/danielgtaylor/python-betterproto/issues/61)
- Fix ALL_CAPS message fields are parsed incorrectly. [#11](https://github.com/danielgtaylor/python-betterproto/issues/11)
## [1.2.5] - 2020-04-27
- Add .j2 suffix to python template names to avoid confusing certain build tools [#72](https://github.com/danielgtaylor/python-betterproto/pull/72)
## [1.2.4] - 2020-04-26
- Enforce utf-8 for reading the readme in setup.py [#67](https://github.com/danielgtaylor/python-betterproto/pull/67)
- Only import types from grpclib when type checking [#52](https://github.com/danielgtaylor/python-betterproto/pull/52)
- Improve performance of serialize/deserialize by caching type information of fields in class [#46](https://github.com/danielgtaylor/python-betterproto/pull/46)
- Support using Google's wrapper types as RPC output values [#40](https://github.com/danielgtaylor/python-betterproto/pull/40)
- Fixes issue where protoc did not recognize plugin.py as win32 application [#38](https://github.com/danielgtaylor/python-betterproto/pull/38)
- Fix services using non-pythonified field names [#34](https://github.com/danielgtaylor/python-betterproto/pull/34)
- Add ability to provide metadata, timeout & deadline args to requests [#32](https://github.com/danielgtaylor/python-betterproto/pull/32)
## [1.2.3] - 2020-04-15
- Exclude empty lists from `to_dict` by default [#16](https://github.com/danielgtaylor/python-betterproto/pull/16)
- Add `include_default_values` parameter for `to_dict` [#12](https://github.com/danielgtaylor/python-betterproto/pull/12)
- Fix class names being prepended with duplicates when using protocol buffers that are nested more than once [#21](https://github.com/danielgtaylor/python-betterproto/pull/21)
- Add support for python 3.6 [#30](https://github.com/danielgtaylor/python-betterproto/pull/30)
## [1.2.2] - 2020-01-09
- Mention lack of Proto 2 support in README.
- Fix serialization of constructor parameters [#10](https://github.com/danielgtaylor/python-betterproto/pull/10)
- Fix `casing` parameter propagation [#7](https://github.com/danielgtaylor/python-betterproto/pull/7)
## [1.2.1] - 2019-10-29
- Fix comment indentation bug in rendered gRPC methods.
## [1.2.0] - 2019-10-28
- Generated code output auto-formatting via [Black](https://github.com/psf/black)
- Simplified gRPC helper functions
## [1.1.0] - 2019-10-27
- Better JSON casing support
- Handle field names which clash with Python reserved words
- Better handling of default values from type introspection
- Support for Google Duration & Timestamp types
- Support for Google wrapper types
- Documentation updates
## [1.0.1] - 2019-10-22
- README to the PyPI details page
## [1.0.0] - 2019-10-22
- Initial release
[1.2.5]: https://github.com/danielgtaylor/python-betterproto/compare/v1.2.4...v1.2.5
[1.2.4]: https://github.com/danielgtaylor/python-betterproto/compare/v1.2.3...v1.2.4
[1.2.3]: https://github.com/danielgtaylor/python-betterproto/compare/v1.2.2...v1.2.3
[1.2.2]: https://github.com/danielgtaylor/python-betterproto/compare/v1.2.1...v1.2.2
[1.2.1]: https://github.com/danielgtaylor/python-betterproto/compare/v1.2.0...v1.2.1
[1.2.0]: https://github.com/danielgtaylor/python-betterproto/compare/v1.1.0...v1.2.0
[1.1.0]: https://github.com/danielgtaylor/python-betterproto/compare/v1.0.1...v1.1.0
[1.0.1]: https://github.com/danielgtaylor/python-betterproto/compare/v1.0.0...v1.0.1
[1.0.0]: https://github.com/danielgtaylor/python-betterproto/releases/tag/v1.0.0

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@ -1,21 +0,0 @@
MIT License
Copyright (c) 2023 Daniel G. Taylor
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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plugin = "protoc --plugin=protoc-gen-custom=betterproto/plugin.py --custom_out=output"
generate = "python betterproto/tests/generate.py"
test = "pytest ./betterproto/tests"

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"sha256:e29e24dd6e7f39f200a5bb55dcaa645d38a397dd5a6674f6042ef02df5795046"
],
"index": "pypi",
"version": "==0.730"
},
"mypy-extensions": {
"hashes": [
"sha256:a161e3b917053de87dbe469987e173e49fb454eca10ef28b48b384538cc11458"
],
"version": "==0.4.2"
},
"packaging": {
"hashes": [
"sha256:28b924174df7a2fa32c1953825ff29c61e2f5e082343165438812f00d3a7fc47",
"sha256:d9551545c6d761f3def1677baf08ab2a3ca17c56879e70fecba2fc4dde4ed108"
],
"version": "==19.2"
},
"pluggy": {
"hashes": [
"sha256:0db4b7601aae1d35b4a033282da476845aa19185c1e6964b25cf324b5e4ec3e6",
"sha256:fa5fa1622fa6dd5c030e9cad086fa19ef6a0cf6d7a2d12318e10cb49d6d68f34"
],
"version": "==0.13.0"
},
"py": {
"hashes": [
"sha256:64f65755aee5b381cea27766a3a147c3f15b9b6b9ac88676de66ba2ae36793fa",
"sha256:dc639b046a6e2cff5bbe40194ad65936d6ba360b52b3c3fe1d08a82dd50b5e53"
],
"version": "==1.8.0"
},
"pycodestyle": {
"hashes": [
"sha256:95a2219d12372f05704562a14ec30bc76b05a5b297b21a5dfe3f6fac3491ae56",
"sha256:e40a936c9a450ad81df37f549d676d127b1b66000a6c500caa2b085bc0ca976c"
],
"version": "==2.5.0"
},
"pyflakes": {
"hashes": [
"sha256:17dbeb2e3f4d772725c777fabc446d5634d1038f234e77343108ce445ea69ce0",
"sha256:d976835886f8c5b31d47970ed689944a0262b5f3afa00a5a7b4dc81e5449f8a2"
],
"version": "==2.1.1"
},
"pyparsing": {
"hashes": [
"sha256:6f98a7b9397e206d78cc01df10131398f1c8b8510a2f4d97d9abd82e1aacdd80",
"sha256:d9338df12903bbf5d65a0e4e87c2161968b10d2e489652bb47001d82a9b028b4"
],
"version": "==2.4.2"
},
"pytest": {
"hashes": [
"sha256:7e4800063ccfc306a53c461442526c5571e1462f61583506ce97e4da6a1d88c8",
"sha256:ca563435f4941d0cb34767301c27bc65c510cb82e90b9ecf9cb52dc2c63caaa0"
],
"index": "pypi",
"version": "==5.2.1"
},
"rope": {
"hashes": [
"sha256:6b728fdc3e98a83446c27a91fc5d56808a004f8beab7a31ab1d7224cecc7d969",
"sha256:c5c5a6a87f7b1a2095fb311135e2a3d1f194f5ecb96900fdd0a9100881f48aaf",
"sha256:f0dcf719b63200d492b85535ebe5ea9b29e0d0b8aebeb87fe03fc1a65924fdaf"
],
"index": "pypi",
"version": "==0.14.0"
},
"six": {
"hashes": [
"sha256:3350809f0555b11f552448330d0b52d5f24c91a322ea4a15ef22629740f3761c",
"sha256:d16a0141ec1a18405cd4ce8b4613101da75da0e9a7aec5bdd4fa804d0e0eba73"
],
"version": "==1.12.0"
},
"typed-ast": {
"hashes": [
"sha256:18511a0b3e7922276346bcb47e2ef9f38fb90fd31cb9223eed42c85d1312344e",
"sha256:262c247a82d005e43b5b7f69aff746370538e176131c32dda9cb0f324d27141e",
"sha256:2b907eb046d049bcd9892e3076c7a6456c93a25bebfe554e931620c90e6a25b0",
"sha256:354c16e5babd09f5cb0ee000d54cfa38401d8b8891eefa878ac772f827181a3c",
"sha256:4e0b70c6fc4d010f8107726af5fd37921b666f5b31d9331f0bd24ad9a088e631",
"sha256:630968c5cdee51a11c05a30453f8cd65e0cc1d2ad0d9192819df9978984529f4",
"sha256:66480f95b8167c9c5c5c87f32cf437d585937970f3fc24386f313a4c97b44e34",
"sha256:71211d26ffd12d63a83e079ff258ac9d56a1376a25bc80b1cdcdf601b855b90b",
"sha256:95bd11af7eafc16e829af2d3df510cecfd4387f6453355188342c3e79a2ec87a",
"sha256:bc6c7d3fa1325a0c6613512a093bc2a2a15aeec350451cbdf9e1d4bffe3e3233",
"sha256:cc34a6f5b426748a507dd5d1de4c1978f2eb5626d51326e43280941206c209e1",
"sha256:d755f03c1e4a51e9b24d899561fec4ccaf51f210d52abdf8c07ee2849b212a36",
"sha256:d7c45933b1bdfaf9f36c579671fec15d25b06c8398f113dab64c18ed1adda01d",
"sha256:d896919306dd0aa22d0132f62a1b78d11aaf4c9fc5b3410d3c666b818191630a",
"sha256:ffde2fbfad571af120fcbfbbc61c72469e72f550d676c3342492a9dfdefb8f12"
],
"version": "==1.4.0"
},
"typing-extensions": {
"hashes": [
"sha256:2ed632b30bb54fc3941c382decfd0ee4148f5c591651c9272473fea2c6397d95",
"sha256:b1edbbf0652660e32ae780ac9433f4231e7339c7f9a8057d0f042fcbcea49b87",
"sha256:d8179012ec2c620d3791ca6fe2bf7979d979acdbef1fca0bc56b37411db682ed"
],
"version": "==3.7.4"
},
"wcwidth": {
"hashes": [
"sha256:3df37372226d6e63e1b1e1eda15c594bca98a22d33a23832a90998faa96bc65e",
"sha256:f4ebe71925af7b40a864553f761ed559b43544f8f71746c2d756c7fe788ade7c"
],
"version": "==0.1.7"
},
"zipp": {
"hashes": [
"sha256:3718b1cbcd963c7d4c5511a8240812904164b7f381b647143a89d3b98f9bcd8e",
"sha256:f06903e9f1f43b12d371004b4ac7b06ab39a44adc747266928ae6debfa7b3335"
],
"version": "==0.6.0"
}
}
}

382
README.md
View File

@ -1,10 +1,8 @@
# Better Protobuf / gRPC Support for Python
![](https://github.com/danielgtaylor/python-betterproto/actions/workflows/ci.yml/badge.svg)
![](https://github.com/danielgtaylor/python-betterproto/workflows/CI/badge.svg)
> :octocat: If you're reading this on github, please be aware that it might mention unreleased features! See the latest released README on [pypi](https://pypi.org/project/betterproto/).
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:
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. The following are supported:
- Protobuf 3 & gRPC code generation
- Both binary & JSON serialization is built-in
@ -12,10 +10,8 @@ This project aims to provide an improved experience when using Protobuf / gRPC i
- Enums
- Dataclasses
- `async`/`await`
- Timezone-aware `datetime` and `timedelta` objects
- Relative imports
- Mypy type checking
- [Pydantic Models](https://docs.pydantic.dev/) generation (see #generating-pydantic-models)
This project is heavily inspired by, and borrows functionality from:
@ -38,31 +34,22 @@ This project exists because I am unhappy with the state of the official Google p
- Much code looks like C++ or Java ported 1:1 to Python
- Capitalized function names like `HasField()` and `SerializeToString()`
- Uses `SerializeToString()` rather than the built-in `__bytes__()`
- Special wrapped types don't use Python's `None`
- Timestamp/duration types don't use Python's built-in `datetime` module
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.
## Installation
## Installation & Getting Started
First, install the package. Note that the `[compiler]` feature flag tells it to install extra dependencies only needed by the `protoc` plugin:
```sh
# Install both the library and compiler
pip install "betterproto[compiler]"
$ pip install betterproto[compiler]
# Install just the library (to use the generated code output)
pip install betterproto
$ pip install betterproto
```
*Betterproto* is under active development. To install the latest beta version, use `pip install --pre betterproto`.
## Getting Started
### Compiling proto files
Given you installed the compiler and have a proto file, e.g `example.proto`:
Now, given you installed the compiler and have a proto file, e.g `example.proto`:
```protobuf
syntax = "proto3";
@ -75,25 +62,17 @@ message Greeting {
}
```
You can run the following to invoke protoc directly:
You can run the following:
```sh
mkdir lib
protoc -I . --python_betterproto_out=lib example.proto
$ protoc -I . --python_betterproto_out=. example.proto
```
or run the following to invoke protoc via grpcio-tools:
This will generate `hello.py` which looks like:
```sh
pip install grpcio-tools
python -m grpc_tools.protoc -I . --python_betterproto_out=lib example.proto
```
This will generate `lib/hello/__init__.py` which looks like:
```python
```py
# Generated by the protocol buffer compiler. DO NOT EDIT!
# sources: example.proto
# sources: hello.proto
# plugin: python-betterproto
from dataclasses import dataclass
@ -101,7 +80,7 @@ import betterproto
@dataclass
class Greeting(betterproto.Message):
class Hello(betterproto.Message):
"""Greeting represents a message you can tell a user."""
message: str = betterproto.string_field(1)
@ -109,23 +88,23 @@ class Greeting(betterproto.Message):
Now you can use it!
```python
>>> from lib.hello import Greeting
>>> test = Greeting()
```py
>>> from hello import Hello
>>> test = Hello()
>>> test
Greeting(message='')
Hello(message='')
>>> test.message = "Hey!"
>>> test
Greeting(message="Hey!")
Hello(message="Hey!")
>>> serialized = bytes(test)
>>> serialized
b'\n\x04Hey!'
>>> another = Greeting().parse(serialized)
>>> another = Hello().parse(serialized)
>>> another
Greeting(message="Hey!")
Hello(message="Hey!")
>>> another.to_dict()
{"message": "Hey!"}
@ -137,7 +116,7 @@ Greeting(message="Hey!")
The generated Protobuf `Message` classes are compatible with [grpclib](https://github.com/vmagamedov/grpclib) so 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:
Given an example like:
```protobuf
syntax = "proto3";
@ -164,75 +143,22 @@ service Echo {
}
```
Generate echo proto file:
You can use it like so (enable async in the interactive shell first):
```
python -m grpc_tools.protoc -I . --python_betterproto_out=. echo.proto
```
```py
>>> import echo
>>> from grpclib.client import Channel
A client can be implemented as follows:
```python
import asyncio
import echo
>>> channel = Channel(host="127.0.0.1", port=1234)
>>> service = echo.EchoStub(channel)
>>> await service.echo(value="hello", extra_times=1)
EchoResponse(values=["hello", "hello"])
from grpclib.client import Channel
async def main():
channel = Channel(host="127.0.0.1", port=50051)
service = echo.EchoStub(channel)
response = await service.echo(echo.EchoRequest(value="hello", extra_times=1))
>>> async for response in service.echo_stream(value="hello", extra_times=1)
print(response)
async for response in service.echo_stream(echo.EchoRequest(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 output
```python
EchoResponse(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:
```python
import asyncio
from echo import EchoBase, EchoRequest, EchoResponse, EchoStreamResponse
from grpclib.server import Server
from typing import AsyncIterator
class EchoService(EchoBase):
async def echo(self, echo_request: "EchoRequest") -> "EchoResponse":
return EchoResponse([echo_request.value for _ in range(echo_request.extra_times)])
async def echo_stream(self, echo_request: "EchoRequest") -> AsyncIterator["EchoStreamResponse"]:
for _ in range(echo_request.extra_times):
yield EchoStreamResponse(echo_request.value)
async def main():
server = Server([EchoService()])
await server.start("127.0.0.1", 50051)
await server.wait_closed()
if __name__ == '__main__':
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
EchoStreamResponse(value="hello")
EchoStreamResponse(value="hello")
```
### JSON
@ -242,12 +168,6 @@ Both serializing and parsing are supported to/from JSON and Python dictionaries
- Dicts: `Message().to_dict()`, `Message().from_dict(...)`
- JSON: `Message().to_json()`, `Message().from_json(...)`
For compatibility the default is to convert field names to `camelCase`. You can control this behavior by passing a casing value, e.g:
```python
MyMessage().to_dict(casing=betterproto.Casing.SNAKE)
```
### Determining if a message was sent
Sometimes 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.
@ -278,22 +198,7 @@ message Test {
}
```
On Python 3.10 and later, you can use a `match` statement to access the provided one-of field, which supports type-checking:
```py
test = Test()
match test:
case Test(on=value):
print(value) # value: bool
case Test(count=value):
print(value) # value: int
case Test(name=value):
print(value) # value: str
case _:
print("No value provided")
```
You can also use `betterproto.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 and `None` if unset.
You can use `betterproto.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 and `None` if unset.
```py
>>> test = Test()
@ -308,11 +213,17 @@ You can also use `betterproto.which_one_of(message, group_name)` to determine wh
>>> test.count = 57
>>> betterproto.which_one_of(test, "foo")
["count", 57]
>>> test.on
False
# Default (zero) values also work.
>>> test.name = ""
>>> betterproto.which_one_of(test, "foo")
["name", ""]
>>> test.count
0
>>> test.on
False
```
Again this is a little different than the official Google code generator:
@ -327,210 +238,36 @@ Again this is a little different than the official Google code generator:
["foo", "foo's value"]
```
### Well-Known Google Types
Google 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 Message | Python Type | Default |
| --------------------------- | ---------------------------------------- | ---------------------- |
| `google.protobuf.duration` | [`datetime.timedelta`][td] | `0` |
| `google.protobuf.timestamp` | Timezone-aware [`datetime.datetime`][dt] | `1970-01-01T00:00:00Z` |
| `google.protobuf.*Value` | `Optional[...]` | `None` |
| `google.protobuf.*` | `betterproto.lib.google.protobuf.*` | `None` |
[td]: https://docs.python.org/3/library/datetime.html#timedelta-objects
[dt]: https://docs.python.org/3/library/datetime.html#datetime.datetime
For the wrapper types, the Python type corresponds to the wrapped type, e.g. `google.protobuf.BoolValue` becomes `Optional[bool]` while `google.protobuf.Int32Value` becomes `Optional[int]`. All of the optional values default to `None`, so don't forget to check for that possible state. Given:
```protobuf
syntax = "proto3";
import "google/protobuf/duration.proto";
import "google/protobuf/timestamp.proto";
import "google/protobuf/wrappers.proto";
message Test {
google.protobuf.BoolValue maybe = 1;
google.protobuf.Timestamp ts = 2;
google.protobuf.Duration duration = 3;
}
```
You can do stuff like:
```py
>>> t = Test().from_dict({"maybe": True, "ts": "2019-01-01T12:00:00Z", "duration": "1.200s"})
>>> t
Test(maybe=True, ts=datetime.datetime(2019, 1, 1, 12, 0, tzinfo=datetime.timezone.utc), duration=datetime.timedelta(seconds=1, microseconds=200000))
>>> t.ts - t.duration
datetime.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'}
```
## Generating Pydantic Models
You can use python-betterproto to generate pydantic based models, using
pydantic dataclasses. This means the results of the protobuf unmarshalling will
be typed checked. The usage is the same, but you need to add a custom option
when calling the protobuf compiler:
```
protoc -I . --python_betterproto_opt=pydantic_dataclasses --python_betterproto_out=lib example.proto
```
With the important change being `--python_betterproto_opt=pydantic_dataclasses`. This will
swap the dataclass implementation from the builtin python dataclass to the
pydantic dataclass. You must have pydantic as a dependency in your project for
this to work.
## Configuration typing imports
By default typing types will be imported directly from typing. This sometimes can lead to issues in generation if types that are being generated conflict with the name. In this case you can configure the way types are imported from 3 different options:
### Direct
```
protoc -I . --python_betterproto_opt=typing.direct --python_betterproto_out=lib example.proto
```
this configuration is the default, and will import types as follows:
```
from typing import (
List,
Optional,
Union
)
...
value: List[str] = []
value2: Optional[str] = None
value3: Union[str, int] = 1
```
### Root
```
protoc -I . --python_betterproto_opt=typing.root --python_betterproto_out=lib example.proto
```
this configuration loads the root typing module, and then access the types off of it directly:
```
import typing
...
value: typing.List[str] = []
value2: typing.Optional[str] = None
value3: typing.Union[str, int] = 1
```
### 310
```
protoc -I . --python_betterproto_opt=typing.310 --python_betterproto_out=lib example.proto
```
this configuration avoid loading typing all together if possible and uses the python 3.10 pattern:
```
...
value: list[str] = []
value2: str | None = None
value3: str | int = 1
```
## Development
- _Join us on [Discord](https://discord.gg/DEVteTupPb)!_
- _See how you can help &rarr; [Contributing](.github/CONTRIBUTING.md)_
### Requirements
- Python (3.7 or higher)
- [poetry](https://python-poetry.org/docs/#installation)
*Needed to install dependencies in a virtual environment*
- [poethepoet](https://github.com/nat-n/poethepoet) for running development tasks as defined in pyproject.toml
- Can be installed to your host environment via `pip install poethepoet` then executed as simple `poe`
- or run from the poetry venv as `poetry run poe`
### Setup
First, make sure you have Python 3.7+ and `pipenv` installed, along with the official [Protobuf Compiler](https://github.com/protocolbuffers/protobuf/releases) for your platform. Then:
```sh
# Get set up with the virtual env & dependencies
poetry install -E compiler
$ pipenv install --dev
# Activate the poetry environment
poetry shell
# Link the local package
$ pipenv shell
$ pip install -e .
```
### Code style
This project enforces [black](https://github.com/psf/black) python code formatting.
Before committing changes run:
```sh
poe format
```
To avoid merge conflicts later, non-black formatted python code will fail in CI.
### Tests
There are two types of tests:
1. Standard tests
2. Custom tests
1. Manually-written tests for some behavior of the library
2. Proto files and JSON inputs for automated tests
#### Standard tests
Adding a standard test case is easy.
- Create a new directory `betterproto/tests/inputs/<name>`
- add `<name>.proto` with a message called `Test`
- add `<name>.json` with some test data (optional)
It will be picked up automatically when you run the tests.
- See also: [Standard Tests Development Guide](tests/README.md)
#### Custom tests
Custom tests are found in `tests/test_*.py` and are run with pytest.
#### Running
For #2, you can add a new `*.proto` file into the `betterproto/tests` directory along with a sample `*.json` input and it will get automatically picked up.
Here's how to run the tests.
```sh
# Generate assets from sample .proto files required by the tests
poe generate
# Generate assets from sample .proto files
$ pipenv run generate
# Run the tests
poe test
```
To run tests as they are run in CI (with tox) run:
```sh
poe full-test
```
### (Re)compiling Google Well-known Types
Betterproto includes compiled versions for Google's well-known types at [src/betterproto/lib/google](src/betterproto/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 to `google.protobuf`, since they are pre-compiled. To force compilation of `google.protobuf`, use the option `--custom_opt=INCLUDE_GOOGLE`.
Assuming your `google.protobuf` source files (included with all releases of `protoc`) are located in `/usr/local/include`, you can regenerate them as follows:
```sh
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/*.proto
$ pipenv run tests
```
### TODO
@ -547,9 +284,6 @@ protoc \
- [x] Refs to nested types
- [x] Imports in proto files
- [x] Well-known Google types
- [ ] Support as request input
- [ ] Support as response output
- [ ] Automatically wrap/unwrap responses
- [x] OneOf support
- [x] Basic support on the wire
- [x] Check which was set from the group
@ -561,22 +295,18 @@ protoc \
- [x] Bytes as base64
- [ ] Any support
- [x] Enum strings
- [x] Well known types support (timestamp, duration, wrappers)
- [x] Support different casing (orig vs. camel vs. others?)
- [x] Async service stubs
- [ ] Well known types support (timestamp, duration, wrappers)
- [ ] Support different casing (orig vs. camel vs. others?)
- [ ] Async service stubs
- [x] Unary-unary
- [x] Server streaming response
- [x] Client streaming request
- [x] Renaming messages and fields to conform to Python name standards
- [x] Renaming clashes with language keywords
- [ ] Client streaming request
- [ ] Renaming messages and fields to conform to Python name standards
- [ ] Renaming clashes with language keywords and standard library top-level packages
- [x] Python package
- [x] Automate running tests
- [ ] Cleanup!
## Community
Join us on [Discord](https://discord.gg/DEVteTupPb)!
## License
Copyright © 2019 Daniel G. Taylor

157
asv.conf.json
View File

@ -1,157 +0,0 @@
{
// The version of the config file format. Do not change, unless
// you know what you are doing.
"version": 1,
// The name of the project being benchmarked
"project": "python-betterproto",
// The project's homepage
"project_url": "https://github.com/danielgtaylor/python-betterproto",
// The URL or local path of the source code repository for the
// project being benchmarked
"repo": ".",
// The Python project's subdirectory in your repo. If missing or
// the empty string, the project is assumed to be located at the root
// of the repository.
// "repo_subdir": "",
// Customizable commands for building, installing, and
// uninstalling the project. See asv.conf.json documentation.
//
"install_command": ["python -m pip install ."],
"uninstall_command": ["return-code=any python -m pip uninstall -y {project}"],
"build_command": ["python -m pip wheel -w {build_cache_dir} {build_dir}"],
// List of branches to benchmark. If not provided, defaults to "master"
// (for git) or "default" (for mercurial).
// "branches": ["master"], // for git
// "branches": ["default"], // for mercurial
// The DVCS being used. If not set, it will be automatically
// determined from "repo" by looking at the protocol in the URL
// (if remote), or by looking for special directories, such as
// ".git" (if local).
// "dvcs": "git",
// The tool to use to create environments. May be "conda",
// "virtualenv" or other value depending on the plugins in use.
// If missing or the empty string, the tool will be automatically
// determined by looking for tools on the PATH environment
// variable.
"environment_type": "virtualenv",
// timeout in seconds for installing any dependencies in environment
// defaults to 10 min
//"install_timeout": 600,
// the base URL to show a commit for the project.
// "show_commit_url": "http://github.com/owner/project/commit/",
// The Pythons you'd like to test against. If not provided, defaults
// to the current version of Python used to run `asv`.
// "pythons": ["2.7", "3.6"],
// The list of conda channel names to be searched for benchmark
// dependency packages in the specified order
// "conda_channels": ["conda-forge", "defaults"],
// The matrix of dependencies to test. Each key is the name of a
// package (in PyPI) and the values are version numbers. An empty
// list or empty string indicates to just test against the default
// (latest) version. null indicates that the package is to not be
// installed. If the package to be tested is only available from
// PyPi, and the 'environment_type' is conda, then you can preface
// the package name by 'pip+', and the package will be installed via
// pip (with all the conda available packages installed first,
// followed by the pip installed packages).
//
// "matrix": {
// "numpy": ["1.6", "1.7"],
// "six": ["", null], // test with and without six installed
// "pip+emcee": [""], // emcee is only available for install with pip.
// },
// Combinations of libraries/python versions can be excluded/included
// from the set to test. Each entry is a dictionary containing additional
// key-value pairs to include/exclude.
//
// An exclude entry excludes entries where all values match. The
// values are regexps that should match the whole string.
//
// An include entry adds an environment. Only the packages listed
// are installed. The 'python' key is required. The exclude rules
// do not apply to includes.
//
// In addition to package names, the following keys are available:
//
// - python
// Python version, as in the *pythons* variable above.
// - environment_type
// Environment type, as above.
// - sys_platform
// Platform, as in sys.platform. Possible values for the common
// cases: 'linux2', 'win32', 'cygwin', 'darwin'.
//
// "exclude": [
// {"python": "3.2", "sys_platform": "win32"}, // skip py3.2 on windows
// {"environment_type": "conda", "six": null}, // don't run without six on conda
// ],
//
// "include": [
// // additional env for python2.7
// {"python": "2.7", "numpy": "1.8"},
// // additional env if run on windows+conda
// {"platform": "win32", "environment_type": "conda", "python": "2.7", "libpython": ""},
// ],
// The directory (relative to the current directory) that benchmarks are
// stored in. If not provided, defaults to "benchmarks"
// "benchmark_dir": "benchmarks",
// The directory (relative to the current directory) to cache the Python
// environments in. If not provided, defaults to "env"
"env_dir": ".asv/env",
// The directory (relative to the current directory) that raw benchmark
// results are stored in. If not provided, defaults to "results".
"results_dir": ".asv/results",
// The directory (relative to the current directory) that the html tree
// should be written to. If not provided, defaults to "html".
"html_dir": ".asv/html",
// The number of characters to retain in the commit hashes.
// "hash_length": 8,
// `asv` will cache results of the recent builds in each
// environment, making them faster to install next time. This is
// the number of builds to keep, per environment.
// "build_cache_size": 2,
// The commits after which the regression search in `asv publish`
// should start looking for regressions. Dictionary whose keys are
// regexps matching to benchmark names, and values corresponding to
// the commit (exclusive) after which to start looking for
// regressions. The default is to start from the first commit
// with results. If the commit is `null`, regression detection is
// skipped for the matching benchmark.
//
// "regressions_first_commits": {
// "some_benchmark": "352cdf", // Consider regressions only after this commit
// "another_benchmark": null, // Skip regression detection altogether
// },
// The thresholds for relative change in results, after which `asv
// publish` starts reporting regressions. Dictionary of the same
// form as in ``regressions_first_commits``, with values
// indicating the thresholds. If multiple entries match, the
// maximum is taken. If no entry matches, the default is 5%.
//
// "regressions_thresholds": {
// "some_benchmark": 0.01, // Threshold of 1%
// "another_benchmark": 0.5, // Threshold of 50%
// },
}

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from dataclasses import dataclass
from typing import List
import betterproto
@dataclass
class TestMessage(betterproto.Message):
foo: int = betterproto.uint32_field(1)
bar: str = betterproto.string_field(2)
baz: float = betterproto.float_field(3)
@dataclass
class TestNestedChildMessage(betterproto.Message):
str_key: str = betterproto.string_field(1)
bytes_key: bytes = betterproto.bytes_field(2)
bool_key: bool = betterproto.bool_field(3)
float_key: float = betterproto.float_field(4)
int_key: int = betterproto.uint64_field(5)
@dataclass
class TestNestedMessage(betterproto.Message):
foo: TestNestedChildMessage = betterproto.message_field(1)
bar: TestNestedChildMessage = betterproto.message_field(2)
baz: TestNestedChildMessage = betterproto.message_field(3)
@dataclass
class TestRepeatedMessage(betterproto.Message):
foo_repeat: List[str] = betterproto.string_field(1)
bar_repeat: List[int] = betterproto.int64_field(2)
baz_repeat: List[bool] = betterproto.bool_field(3)
class BenchMessage:
"""Test creation and usage a proto message."""
def setup(self):
self.cls = TestMessage
self.instance = TestMessage()
self.instance_filled = TestMessage(0, "test", 0.0)
self.instance_filled_bytes = bytes(self.instance_filled)
self.instance_filled_nested = TestNestedMessage(
TestNestedChildMessage("foo", bytearray(b"test1"), True, 0.1234, 500),
TestNestedChildMessage("bar", bytearray(b"test2"), True, 3.1415, 302),
TestNestedChildMessage("baz", bytearray(b"test3"), False, 1e5, 300),
)
self.instance_filled_nested_bytes = bytes(self.instance_filled_nested)
self.instance_filled_repeated = TestRepeatedMessage(
[f"test{i}" for i in range(1_000)],
[(i - 500) ** 3 for i in range(1_000)],
[i % 2 == 0 for i in range(1_000)],
)
self.instance_filled_repeated_bytes = bytes(self.instance_filled_repeated)
def time_overhead(self):
"""Overhead in class definition."""
@dataclass
class Message(betterproto.Message):
foo: int = betterproto.uint32_field(1)
bar: str = betterproto.string_field(2)
baz: float = betterproto.float_field(3)
def time_instantiation(self):
"""Time instantiation"""
self.cls()
def time_attribute_access(self):
"""Time to access an attribute"""
self.instance.foo
self.instance.bar
self.instance.baz
def time_init_with_values(self):
"""Time to set an attribute"""
self.cls(0, "test", 0.0)
def time_attribute_setting(self):
"""Time to set attributes"""
self.instance.foo = 0
self.instance.bar = "test"
self.instance.baz = 0.0
def time_serialize(self):
"""Time serializing a message to wire."""
bytes(self.instance_filled)
def time_deserialize(self):
"""Time deserialize a message."""
TestMessage().parse(self.instance_filled_bytes)
def time_serialize_nested(self):
"""Time serializing a nested message to wire."""
bytes(self.instance_filled_nested)
def time_deserialize_nested(self):
"""Time deserialize a nested message."""
TestNestedMessage().parse(self.instance_filled_nested_bytes)
def time_serialize_repeated(self):
"""Time serializing a repeated message to wire."""
bytes(self.instance_filled_repeated)
def time_deserialize_repeated(self):
"""Time deserialize a repeated message."""
TestRepeatedMessage().parse(self.instance_filled_repeated_bytes)
class MemSuite:
def setup(self):
self.cls = TestMessage
def mem_instance(self):
return self.cls()

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betterproto/__init__.py Normal file
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@ -0,0 +1,775 @@
import dataclasses
import enum
import inspect
import json
import struct
from abc import ABC
from base64 import b64encode, b64decode
from typing import (
Any,
AsyncGenerator,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
SupportsBytes,
Tuple,
Type,
TypeVar,
Union,
get_type_hints,
)
import grpclib.client
import grpclib.const
# Proto 3 data types
TYPE_ENUM = "enum"
TYPE_BOOL = "bool"
TYPE_INT32 = "int32"
TYPE_INT64 = "int64"
TYPE_UINT32 = "uint32"
TYPE_UINT64 = "uint64"
TYPE_SINT32 = "sint32"
TYPE_SINT64 = "sint64"
TYPE_FLOAT = "float"
TYPE_DOUBLE = "double"
TYPE_FIXED32 = "fixed32"
TYPE_SFIXED32 = "sfixed32"
TYPE_FIXED64 = "fixed64"
TYPE_SFIXED64 = "sfixed64"
TYPE_STRING = "string"
TYPE_BYTES = "bytes"
TYPE_MESSAGE = "message"
TYPE_MAP = "map"
# Fields that use a fixed amount of space (4 or 8 bytes)
FIXED_TYPES = [
TYPE_FLOAT,
TYPE_DOUBLE,
TYPE_FIXED32,
TYPE_SFIXED32,
TYPE_FIXED64,
TYPE_SFIXED64,
]
# Fields that are numerical 64-bit types
INT_64_TYPES = [TYPE_INT64, TYPE_UINT64, TYPE_SINT64, TYPE_FIXED64, TYPE_SFIXED64]
# Fields that are efficiently packed when
PACKED_TYPES = [
TYPE_ENUM,
TYPE_BOOL,
TYPE_INT32,
TYPE_INT64,
TYPE_UINT32,
TYPE_UINT64,
TYPE_SINT32,
TYPE_SINT64,
TYPE_FLOAT,
TYPE_DOUBLE,
TYPE_FIXED32,
TYPE_SFIXED32,
TYPE_FIXED64,
TYPE_SFIXED64,
]
# Wire types
# https://developers.google.com/protocol-buffers/docs/encoding#structure
WIRE_VARINT = 0
WIRE_FIXED_64 = 1
WIRE_LEN_DELIM = 2
WIRE_FIXED_32 = 5
# Mappings of which Proto 3 types correspond to which wire types.
WIRE_VARINT_TYPES = [
TYPE_ENUM,
TYPE_BOOL,
TYPE_INT32,
TYPE_INT64,
TYPE_UINT32,
TYPE_UINT64,
TYPE_SINT32,
TYPE_SINT64,
]
WIRE_FIXED_32_TYPES = [TYPE_FLOAT, TYPE_FIXED32, TYPE_SFIXED32]
WIRE_FIXED_64_TYPES = [TYPE_DOUBLE, TYPE_FIXED64, TYPE_SFIXED64]
WIRE_LEN_DELIM_TYPES = [TYPE_STRING, TYPE_BYTES, TYPE_MESSAGE, TYPE_MAP]
class _PLACEHOLDER:
pass
PLACEHOLDER: Any = _PLACEHOLDER()
def get_default(proto_type: str) -> Any:
"""Get the default (zero value) for a given type."""
return {
TYPE_BOOL: False,
TYPE_FLOAT: 0.0,
TYPE_DOUBLE: 0.0,
TYPE_STRING: "",
TYPE_BYTES: b"",
TYPE_MAP: {},
}.get(proto_type, 0)
@dataclasses.dataclass(frozen=True)
class FieldMetadata:
"""Stores internal metadata used for parsing & serialization."""
# Protobuf field number
number: int
# Protobuf type name
proto_type: str
# Map information if the proto_type is a map
map_types: Optional[Tuple[str, str]]
# Groups several "one-of" fields together
group: Optional[str]
@staticmethod
def get(field: dataclasses.Field) -> "FieldMetadata":
"""Returns the field metadata for a dataclass field."""
return field.metadata["betterproto"]
def dataclass_field(
number: int,
proto_type: str,
*,
map_types: Optional[Tuple[str, str]] = None,
group: Optional[str] = None,
) -> dataclasses.Field:
"""Creates a dataclass field with attached protobuf metadata."""
return dataclasses.field(
default=PLACEHOLDER,
metadata={"betterproto": FieldMetadata(number, proto_type, map_types, group)},
)
# Note: the fields below return `Any` to prevent type errors in the generated
# data classes since the types won't match with `Field` and they get swapped
# out at runtime. The generated dataclass variables are still typed correctly.
def enum_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_ENUM, group=group)
def bool_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_BOOL, group=group)
def int32_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_INT32, group=group)
def int64_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_INT64, group=group)
def uint32_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_UINT32, group=group)
def uint64_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_UINT64, group=group)
def sint32_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_SINT32, group=group)
def sint64_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_SINT64, group=group)
def float_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_FLOAT, group=group)
def double_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_DOUBLE, group=group)
def fixed32_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_FIXED32, group=group)
def fixed64_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_FIXED64, group=group)
def sfixed32_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_SFIXED32, group=group)
def sfixed64_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_SFIXED64, group=group)
def string_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_STRING, group=group)
def bytes_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_BYTES, group=group)
def message_field(number: int, group: Optional[str] = None) -> Any:
return dataclass_field(number, TYPE_MESSAGE, group=group)
def map_field(
number: int, key_type: str, value_type: str, group: Optional[str] = None
) -> Any:
return dataclass_field(
number, TYPE_MAP, map_types=(key_type, value_type), group=group
)
class Enum(int, enum.Enum):
"""Protocol buffers enumeration base class. Acts like `enum.IntEnum`."""
@classmethod
def from_string(cls, name: str) -> int:
"""Return the value which corresponds to the string name."""
try:
return cls.__members__[name]
except KeyError as e:
raise ValueError(f"Unknown value {name} for enum {cls.__name__}") from e
def _pack_fmt(proto_type: str) -> str:
"""Returns a little-endian format string for reading/writing binary."""
return {
TYPE_DOUBLE: "<d",
TYPE_FLOAT: "<f",
TYPE_FIXED32: "<I",
TYPE_FIXED64: "<Q",
TYPE_SFIXED32: "<i",
TYPE_SFIXED64: "<q",
}[proto_type]
def encode_varint(value: int) -> bytes:
"""Encodes a single varint value for serialization."""
b: List[int] = []
if value < 0:
value += 1 << 64
bits = value & 0x7F
value >>= 7
while value:
b.append(0x80 | bits)
bits = value & 0x7F
value >>= 7
return bytes(b + [bits])
def _preprocess_single(proto_type: str, value: Any) -> bytes:
"""Adjusts values before serialization."""
if proto_type in [
TYPE_ENUM,
TYPE_BOOL,
TYPE_INT32,
TYPE_INT64,
TYPE_UINT32,
TYPE_UINT64,
]:
return encode_varint(value)
elif proto_type in [TYPE_SINT32, TYPE_SINT64]:
# Handle zig-zag encoding.
if value >= 0:
value = value << 1
else:
value = (value << 1) ^ (~0)
return encode_varint(value)
elif proto_type in FIXED_TYPES:
return struct.pack(_pack_fmt(proto_type), value)
elif proto_type == TYPE_STRING:
return value.encode("utf-8")
elif proto_type == TYPE_MESSAGE:
return bytes(value)
return value
def _serialize_single(
field_number: int, proto_type: str, value: Any, *, serialize_empty: bool = False
) -> bytes:
"""Serializes a single field and value."""
value = _preprocess_single(proto_type, value)
output = b""
if proto_type in WIRE_VARINT_TYPES:
key = encode_varint(field_number << 3)
output += key + value
elif proto_type in WIRE_FIXED_32_TYPES:
key = encode_varint((field_number << 3) | 5)
output += key + value
elif proto_type in WIRE_FIXED_64_TYPES:
key = encode_varint((field_number << 3) | 1)
output += key + value
elif proto_type in WIRE_LEN_DELIM_TYPES:
if len(value) or serialize_empty:
key = encode_varint((field_number << 3) | 2)
output += key + encode_varint(len(value)) + value
else:
raise NotImplementedError(proto_type)
return output
def decode_varint(buffer: bytes, pos: int, signed: bool = False) -> Tuple[int, int]:
"""
Decode a single varint value from a byte buffer. Returns the value and the
new position in the buffer.
"""
result = 0
shift = 0
while 1:
b = buffer[pos]
result |= (b & 0x7F) << shift
pos += 1
if not (b & 0x80):
return (result, pos)
shift += 7
if shift >= 64:
raise ValueError("Too many bytes when decoding varint.")
@dataclasses.dataclass(frozen=True)
class ParsedField:
number: int
wire_type: int
value: Any
raw: bytes
def parse_fields(value: bytes) -> Generator[ParsedField, None, None]:
i = 0
while i < len(value):
start = i
num_wire, i = decode_varint(value, i)
# print(num_wire, i)
number = num_wire >> 3
wire_type = num_wire & 0x7
decoded: Any = None
if wire_type == 0:
decoded, i = decode_varint(value, i)
elif wire_type == 1:
decoded, i = value[i : i + 8], i + 8
elif wire_type == 2:
length, i = decode_varint(value, i)
decoded = value[i : i + length]
i += length
elif wire_type == 5:
decoded, i = value[i : i + 4], i + 4
# print(ParsedField(number=number, wire_type=wire_type, value=decoded))
yield ParsedField(
number=number, wire_type=wire_type, value=decoded, raw=value[start:i]
)
# Bound type variable to allow methods to return `self` of subclasses
T = TypeVar("T", bound="Message")
class Message(ABC):
"""
A protobuf message base class. Generated code will inherit from this and
register the message fields which get used by the serializers and parsers
to go between Python, binary and JSON protobuf message representations.
"""
def __post_init__(self) -> None:
# Set a default value for each field in the class after `__init__` has
# already been run.
group_map = {"fields": {}, "groups": {}}
for field in dataclasses.fields(self):
meta = FieldMetadata.get(field)
if meta.group:
group_map["fields"][field.name] = meta.group
if meta.group not in group_map["groups"]:
group_map["groups"][meta.group] = {"current": None, "fields": set()}
group_map["groups"][meta.group]["fields"].add(field)
if getattr(self, field.name) != PLACEHOLDER:
# Skip anything not set to the sentinel value
if meta.group:
# This was set, so make it the selected value of the one-of.
group_map["groups"][meta.group]["current"] = field
continue
setattr(self, field.name, self._get_field_default(field, meta))
# Now that all the defaults are set, reset it!
self.__dict__["_serialized_on_wire"] = False
self.__dict__["_unknown_fields"] = b""
self.__dict__["_group_map"] = group_map
def __setattr__(self, attr: str, value: Any) -> None:
if attr != "_serialized_on_wire":
# Track when a field has been set.
self.__dict__["_serialized_on_wire"] = True
if attr in getattr(self, "_group_map", {}).get("fields", {}):
group = self._group_map["fields"][attr]
for field in self._group_map["groups"][group]["fields"]:
if field.name == attr:
self._group_map["groups"][group]["current"] = field
else:
super().__setattr__(
field.name,
self._get_field_default(field, FieldMetadata.get(field)),
)
super().__setattr__(attr, value)
def __bytes__(self) -> bytes:
"""
Get the binary encoded Protobuf representation of this instance.
"""
output = b""
for field in dataclasses.fields(self):
meta = FieldMetadata.get(field)
value = getattr(self, field.name)
# Being selected in a a group means this field is the one that is
# currently set in a `oneof` group, so it must be serialized even
# if the value is the default zero value.
selected_in_group = False
if meta.group and self._group_map["groups"][meta.group]["current"] == field:
selected_in_group = True
if isinstance(value, list):
if not len(value) and not selected_in_group:
# Empty values are not serialized
continue
if meta.proto_type in PACKED_TYPES:
# Packed lists look like a length-delimited field. First,
# preprocess/encode each value into a buffer and then
# treat it like a field of raw bytes.
buf = b""
for item in value:
buf += _preprocess_single(meta.proto_type, item)
output += _serialize_single(meta.number, TYPE_BYTES, buf)
else:
for item in value:
output += _serialize_single(meta.number, meta.proto_type, item)
elif isinstance(value, dict):
if not len(value) and not selected_in_group:
# Empty values are not serialized
continue
for k, v in value.items():
assert meta.map_types
sk = _serialize_single(1, meta.map_types[0], k)
sv = _serialize_single(2, meta.map_types[1], v)
output += _serialize_single(meta.number, meta.proto_type, sk + sv)
else:
if value == get_default(meta.proto_type) and not selected_in_group:
# Default (zero) values are not serialized
continue
serialize_empty = False
if isinstance(value, Message) and value._serialized_on_wire:
serialize_empty = True
output += _serialize_single(
meta.number, meta.proto_type, value, serialize_empty=serialize_empty
)
return output + self._unknown_fields
# For compatibility with other libraries
SerializeToString = __bytes__
def _cls_for(self, field: dataclasses.Field, index: int = 0) -> Type:
"""Get the message class for a field from the type hints."""
module = inspect.getmodule(self.__class__)
type_hints = get_type_hints(self.__class__, vars(module))
cls = type_hints[field.name]
if hasattr(cls, "__args__") and index >= 0:
cls = type_hints[field.name].__args__[index]
return cls
def _get_field_default(self, field: dataclasses.Field, meta: FieldMetadata) -> Any:
t = self._cls_for(field, index=-1)
value: Any = 0
if meta.proto_type == TYPE_MAP:
# Maps cannot be repeated, so we check these first.
value = {}
elif hasattr(t, "__args__") and len(t.__args__) == 1:
# Anything else with type args is a list.
value = []
elif meta.proto_type == TYPE_MESSAGE:
# Message means creating an instance of the right type.
value = t()
else:
value = get_default(meta.proto_type)
return value
def _postprocess_single(
self, wire_type: int, meta: FieldMetadata, field: dataclasses.Field, value: Any
) -> Any:
"""Adjusts values after parsing."""
if wire_type == WIRE_VARINT:
if meta.proto_type in [TYPE_INT32, TYPE_INT64]:
bits = int(meta.proto_type[3:])
value = value & ((1 << bits) - 1)
signbit = 1 << (bits - 1)
value = int((value ^ signbit) - signbit)
elif meta.proto_type in [TYPE_SINT32, TYPE_SINT64]:
# Undo zig-zag encoding
value = (value >> 1) ^ (-(value & 1))
elif wire_type in [WIRE_FIXED_32, WIRE_FIXED_64]:
fmt = _pack_fmt(meta.proto_type)
value = struct.unpack(fmt, value)[0]
elif wire_type == WIRE_LEN_DELIM:
if meta.proto_type == TYPE_STRING:
value = value.decode("utf-8")
elif meta.proto_type == TYPE_MESSAGE:
cls = self._cls_for(field)
value = cls().parse(value)
value._serialized_on_wire = True
elif meta.proto_type == TYPE_MAP:
# TODO: This is slow, use a cache to make it faster since each
# key/value pair will recreate the class.
assert meta.map_types
kt = self._cls_for(field, index=0)
vt = self._cls_for(field, index=1)
Entry = dataclasses.make_dataclass(
"Entry",
[
("key", kt, dataclass_field(1, meta.map_types[0])),
("value", vt, dataclass_field(2, meta.map_types[1])),
],
bases=(Message,),
)
value = Entry().parse(value)
return value
def parse(self: T, data: bytes) -> T:
"""
Parse the binary encoded Protobuf into this message instance. This
returns the instance itself and is therefore assignable and chainable.
"""
fields = {f.metadata["betterproto"].number: f for f in dataclasses.fields(self)}
for parsed in parse_fields(data):
if parsed.number in fields:
field = fields[parsed.number]
meta = FieldMetadata.get(field)
value: Any
if (
parsed.wire_type == WIRE_LEN_DELIM
and meta.proto_type in PACKED_TYPES
):
# This is a packed repeated field.
pos = 0
value = []
while pos < len(parsed.value):
if meta.proto_type in ["float", "fixed32", "sfixed32"]:
decoded, pos = parsed.value[pos : pos + 4], pos + 4
wire_type = WIRE_FIXED_32
elif meta.proto_type in ["double", "fixed64", "sfixed64"]:
decoded, pos = parsed.value[pos : pos + 8], pos + 8
wire_type = WIRE_FIXED_64
else:
decoded, pos = decode_varint(parsed.value, pos)
wire_type = WIRE_VARINT
decoded = self._postprocess_single(
wire_type, meta, field, decoded
)
value.append(decoded)
else:
value = self._postprocess_single(
parsed.wire_type, meta, field, parsed.value
)
current = getattr(self, field.name)
if meta.proto_type == TYPE_MAP:
# Value represents a single key/value pair entry in the map.
current[value.key] = value.value
elif isinstance(current, list) and not isinstance(value, list):
current.append(value)
else:
setattr(self, field.name, value)
else:
self._unknown_fields += parsed.raw
return self
# For compatibility with other libraries.
@classmethod
def FromString(cls: Type[T], data: bytes) -> T:
return cls().parse(data)
def to_dict(self) -> dict:
"""
Returns a dict representation of this message instance which can be
used to serialize to e.g. JSON.
"""
output: Dict[str, Any] = {}
for field in dataclasses.fields(self):
meta = FieldMetadata.get(field)
v = getattr(self, field.name)
if meta.proto_type == "message":
if isinstance(v, list):
# Convert each item.
v = [i.to_dict() for i in v]
output[field.name] = v
elif v._serialized_on_wire:
output[field.name] = v.to_dict()
elif meta.proto_type == "map":
for k in v:
if hasattr(v[k], "to_dict"):
v[k] = v[k].to_dict()
if v:
output[field.name] = v
elif v != get_default(meta.proto_type):
if meta.proto_type in INT_64_TYPES:
if isinstance(v, list):
output[field.name] = [str(n) for n in v]
else:
output[field.name] = str(v)
elif meta.proto_type == TYPE_BYTES:
if isinstance(v, list):
output[field.name] = [b64encode(b).decode("utf8") for b in v]
else:
output[field.name] = b64encode(v).decode("utf8")
elif meta.proto_type == TYPE_ENUM:
enum_values = list(self._cls_for(field))
if isinstance(v, list):
output[field.name] = [enum_values[e].name for e in v]
else:
output[field.name] = enum_values[v].name
else:
output[field.name] = v
return output
def from_dict(self: T, value: dict) -> T:
"""
Parse the key/value pairs in `value` into this message instance. This
returns the instance itself and is therefore assignable and chainable.
"""
self._serialized_on_wire = True
for field in dataclasses.fields(self):
meta = FieldMetadata.get(field)
if field.name in value and value[field.name] is not None:
if meta.proto_type == "message":
v = getattr(self, field.name)
# print(v, value[field.name])
if isinstance(v, list):
cls = self._cls_for(field)
for i in range(len(value[field.name])):
v.append(cls().from_dict(value[field.name][i]))
else:
v.from_dict(value[field.name])
elif meta.map_types and meta.map_types[1] == TYPE_MESSAGE:
v = getattr(self, field.name)
cls = self._cls_for(field, index=1)
for k in value[field.name]:
v[k] = cls().from_dict(value[field.name][k])
else:
v = value[field.name]
if meta.proto_type in INT_64_TYPES:
if isinstance(value[field.name], list):
v = [int(n) for n in value[field.name]]
else:
v = int(value[field.name])
elif meta.proto_type == TYPE_BYTES:
if isinstance(value[field.name], list):
v = [b64decode(n) for n in value[field.name]]
else:
v = b64decode(value[field.name])
elif meta.proto_type == TYPE_ENUM:
enum_cls = self._cls_for(field)
if isinstance(v, list):
v = [enum_cls.from_string(e) for e in v]
elif isinstance(v, str):
v = enum_cls.from_string(v)
if v is not None:
setattr(self, field.name, v)
return self
def to_json(self, indent: Union[None, int, str] = None) -> str:
"""Returns the encoded JSON representation of this message instance."""
return json.dumps(self.to_dict(), indent=indent)
def from_json(self: T, value: Union[str, bytes]) -> T:
"""
Parse the key/value pairs in `value` into this message instance. This
returns the instance itself and is therefore assignable and chainable.
"""
return self.from_dict(json.loads(value))
def serialized_on_wire(message: Message) -> bool:
"""
True if this message was or should be serialized on the wire. This can
be used to detect presence (e.g. optional wrapper message) and is used
internally during parsing/serialization.
"""
return message._serialized_on_wire
def which_one_of(message: Message, group_name: str) -> Tuple[str, Any]:
"""Return the name and value of a message's one-of field group."""
field = message._group_map["groups"].get(group_name, {}).get("current")
if not field:
return ("", None)
return (field.name, getattr(message, field.name))
class ServiceStub(ABC):
"""
Base class for async gRPC service stubs.
"""
def __init__(self, channel: grpclib.client.Channel) -> None:
self.channel = channel
async def _unary_unary(
self, route: str, request_type: Type, response_type: Type[T], request: Any
) -> T:
"""Make a unary request and return the response."""
async with self.channel.request(
route, grpclib.const.Cardinality.UNARY_UNARY, request_type, response_type
) as stream:
await stream.send_message(request, end=True)
response = await stream.recv_message()
assert response is not None
return response
async def _unary_stream(
self, route: str, request_type: Type, response_type: Type[T], request: Any
) -> AsyncGenerator[T, None]:
"""Make a unary request and return the stream response iterator."""
async with self.channel.request(
route, grpclib.const.Cardinality.UNARY_STREAM, request_type, response_type
) as stream:
await stream.send_message(request, end=True)
async for message in stream:
yield message

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betterproto/__pycache__/__init__.cpython-37.pyc Normal file
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#!/usr/bin/env python
import itertools
import json
import os.path
import re
import sys
import textwrap
from typing import Any, List, Tuple
try:
import jinja2
except ImportError:
print(
"Unable to import `jinja2`. Did you install the compiler feature with `pip install betterproto[compiler]`?"
)
raise SystemExit(1)
from google.protobuf.compiler import plugin_pb2 as plugin
from google.protobuf.descriptor_pb2 import (
DescriptorProto,
EnumDescriptorProto,
FieldDescriptorProto,
FileDescriptorProto,
ServiceDescriptorProto,
)
def snake_case(value: str) -> str:
return (
re.sub(r"(?<=[a-z])[A-Z]|[A-Z](?=[^A-Z])", r"_\g<0>", value).lower().strip("_")
)
def get_ref_type(package: str, imports: set, type_name: str) -> str:
"""
Return a Python type name for a proto type reference. Adds the import if
necessary.
"""
type_name = type_name.lstrip(".")
if type_name.startswith(package):
# This is the current package, which has nested types flattened.
type_name = f'"{type_name.lstrip(package).lstrip(".").replace(".", "")}"'
if "." in type_name:
# This is imported from another package. No need
# to use a forward ref and we need to add the import.
parts = type_name.split(".")
imports.add(f"from .{'.'.join(parts[:-2])} import {parts[-2]}")
type_name = f"{parts[-2]}.{parts[-1]}"
return type_name
def py_type(
package: str,
imports: set,
message: DescriptorProto,
descriptor: FieldDescriptorProto,
) -> str:
if descriptor.type in [1, 2, 6, 7, 15, 16]:
return "float"
elif descriptor.type in [3, 4, 5, 13, 17, 18]:
return "int"
elif descriptor.type == 8:
return "bool"
elif descriptor.type == 9:
return "str"
elif descriptor.type in [11, 14]:
# Type referencing another defined Message or a named enum
return get_ref_type(package, imports, descriptor.type_name)
elif descriptor.type == 12:
return "bytes"
else:
raise NotImplementedError(f"Unknown type {descriptor.type}")
def get_py_zero(type_num: int) -> str:
zero = 0
if type_num in []:
zero = 0.0
elif type_num == 8:
zero = "False"
elif type_num == 9:
zero = '""'
elif type_num == 11:
zero = "None"
elif type_num == 12:
zero = 'b""'
return zero
def traverse(proto_file):
def _traverse(path, items):
for i, item in enumerate(items):
yield item, path + [i]
if isinstance(item, DescriptorProto):
for enum in item.enum_type:
enum.name = item.name + enum.name
yield enum, path + [i, 4]
if item.nested_type:
for n, p in _traverse(path + [i, 3], item.nested_type):
# Adjust the name since we flatten the heirarchy.
n.name = item.name + n.name
yield n, p
return itertools.chain(
_traverse([5], proto_file.enum_type), _traverse([4], proto_file.message_type)
)
def get_comment(proto_file, path: List[int]) -> str:
for sci in proto_file.source_code_info.location:
# print(list(sci.path), path, file=sys.stderr)
if list(sci.path) == path and sci.leading_comments:
lines = textwrap.wrap(
sci.leading_comments.strip().replace("\n", ""), width=75
)
if path[-2] == 2 and path[-4] != 6:
# This is a field
return " # " + " # ".join(lines)
else:
# This is a message, enum, service, or method
if len(lines) == 1 and len(lines[0]) < 70:
lines[0] = lines[0].strip('"')
return f' """{lines[0]}"""'
else:
joined = "\n ".join(lines)
return f' """\n {joined}\n """'
return ""
def generate_code(request, response):
env = jinja2.Environment(
trim_blocks=True,
lstrip_blocks=True,
loader=jinja2.FileSystemLoader("%s/templates/" % os.path.dirname(__file__)),
)
template = env.get_template("template.py")
output_map = {}
for proto_file in request.proto_file:
out = proto_file.package
if not out:
out = os.path.splitext(proto_file.name)[0].replace(os.path.sep, ".")
if out not in output_map:
output_map[out] = {"package": proto_file.package, "files": []}
output_map[out]["files"].append(proto_file)
# TODO: Figure out how to handle gRPC request/response messages and add
# processing below for Service.
for filename, options in output_map.items():
package = options["package"]
# print(package, filename, file=sys.stderr)
output = {
"package": package,
"files": [f.name for f in options["files"]],
"imports": set(),
"typing_imports": set(),
"messages": [],
"enums": [],
"services": [],
}
type_mapping = {}
for proto_file in options["files"]:
# print(proto_file.message_type, file=sys.stderr)
# print(proto_file.service, file=sys.stderr)
# print(proto_file.source_code_info, file=sys.stderr)
for item, path in traverse(proto_file):
# print(item, file=sys.stderr)
# print(path, file=sys.stderr)
data = {"name": item.name}
if isinstance(item, DescriptorProto):
# print(item, file=sys.stderr)
if item.options.map_entry:
# Skip generated map entry messages since we just use dicts
continue
data.update(
{
"type": "Message",
"comment": get_comment(proto_file, path),
"properties": [],
}
)
for i, f in enumerate(item.field):
t = py_type(package, output["imports"], item, f)
zero = get_py_zero(f.type)
repeated = False
packed = False
field_type = f.Type.Name(f.type).lower()[5:]
map_types = None
if f.type == 11:
# This might be a map...
message_type = f.type_name.split(".").pop().lower()
# message_type = py_type(package)
map_entry = f"{f.name.replace('_', '').lower()}entry"
if message_type == map_entry:
for nested in item.nested_type:
if (
nested.name.replace("_", "").lower()
== map_entry
):
if nested.options.map_entry:
# print("Found a map!", file=sys.stderr)
k = py_type(
package,
output["imports"],
item,
nested.field[0],
)
v = py_type(
package,
output["imports"],
item,
nested.field[1],
)
t = f"Dict[{k}, {v}]"
field_type = "map"
map_types = (
f.Type.Name(nested.field[0].type),
f.Type.Name(nested.field[1].type),
)
output["typing_imports"].add("Dict")
if f.label == 3 and field_type != "map":
# Repeated field
repeated = True
t = f"List[{t}]"
zero = "[]"
output["typing_imports"].add("List")
if f.type in [1, 2, 3, 4, 5, 6, 7, 8, 13, 15, 16, 17, 18]:
packed = True
one_of = ""
if f.HasField("oneof_index"):
one_of = item.oneof_decl[f.oneof_index].name
data["properties"].append(
{
"name": f.name,
"number": f.number,
"comment": get_comment(proto_file, path + [2, i]),
"proto_type": int(f.type),
"field_type": field_type,
"map_types": map_types,
"type": t,
"zero": zero,
"repeated": repeated,
"packed": packed,
"one_of": one_of,
}
)
# print(f, file=sys.stderr)
output["messages"].append(data)
elif isinstance(item, EnumDescriptorProto):
# print(item.name, path, file=sys.stderr)
data.update(
{
"type": "Enum",
"comment": get_comment(proto_file, path),
"entries": [
{
"name": v.name,
"value": v.number,
"comment": get_comment(proto_file, path + [2, i]),
}
for i, v in enumerate(item.value)
],
}
)
output["enums"].append(data)
for i, service in enumerate(proto_file.service):
# print(service, file=sys.stderr)
data = {
"name": service.name,
"comment": get_comment(proto_file, [6, i]),
"methods": [],
}
for j, method in enumerate(service.method):
if method.client_streaming:
raise NotImplementedError("Client streaming not yet supported")
input_message = None
input_type = get_ref_type(
package, output["imports"], method.input_type
).strip('"')
for msg in output["messages"]:
if msg["name"] == input_type:
input_message = msg
for field in msg["properties"]:
if field["zero"] == "None":
output["typing_imports"].add("Optional")
break
data["methods"].append(
{
"name": method.name,
"py_name": snake_case(method.name),
"comment": get_comment(proto_file, [6, i, 2, j]),
"route": f"/{package}.{service.name}/{method.name}",
"input": get_ref_type(
package, output["imports"], method.input_type
).strip('"'),
"input_message": input_message,
"output": get_ref_type(
package, output["imports"], method.output_type
).strip('"'),
"client_streaming": method.client_streaming,
"server_streaming": method.server_streaming,
}
)
if method.server_streaming:
output["typing_imports"].add("AsyncGenerator")
output["services"].append(data)
output["imports"] = sorted(output["imports"])
output["typing_imports"] = sorted(output["typing_imports"])
# Fill response
f = response.file.add()
# print(filename, file=sys.stderr)
f.name = filename.replace(".", os.path.sep) + ".py"
# f.content = json.dumps(output, indent=2)
f.content = template.render(description=output).rstrip("\n") + "\n"
inits = set([""])
for f in response.file:
# Ensure output paths exist
# print(f.name, file=sys.stderr)
dirnames = os.path.dirname(f.name)
if dirnames:
os.makedirs(dirnames, exist_ok=True)
base = ""
for part in dirnames.split(os.path.sep):
base = os.path.join(base, part)
inits.add(base)
for base in inits:
init = response.file.add()
init.name = os.path.join(base, "__init__.py")
init.content = b""
def main():
"""The plugin's main entry point."""
# Read request message from stdin
data = sys.stdin.buffer.read()
# Parse request
request = plugin.CodeGeneratorRequest()
request.ParseFromString(data)
# Create response
response = plugin.CodeGeneratorResponse()
# Generate code
generate_code(request, response)
# Serialise response message
output = response.SerializeToString()
# Write to stdout
sys.stdout.buffer.write(output)
if __name__ == "__main__":
main()

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betterproto/templates/template.py Normal file
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@ -0,0 +1,95 @@
# Generated by the protocol buffer compiler. DO NOT EDIT!
# sources: {{ ', '.join(description.files) }}
# plugin: python-betterproto
from dataclasses import dataclass
{% if description.typing_imports %}
from typing import {% for i in description.typing_imports %}{{ i }}{% if not loop.last %}, {% endif %}{% endfor %}
{% endif %}
import betterproto
{% if description.services %}
import grpclib
{% endif %}
{% for i in description.imports %}
{{ i }}
{% endfor %}
{% if description.enums %}{% for enum in description.enums %}
class {{ enum.name }}(betterproto.Enum):
{% if enum.comment %}
{{ enum.comment }}
{% endif %}
{% for entry in enum.entries %}
{% if entry.comment %}
{{ entry.comment }}
{% endif %}
{{ entry.name }} = {{ entry.value }}
{% endfor %}
{% endfor %}
{% endif %}
{% for message in description.messages %}
@dataclass
class {{ message.name }}(betterproto.Message):
{% if message.comment %}
{{ message.comment }}
{% endif %}
{% for field in message.properties %}
{% if field.comment %}
{{ field.comment }}
{% endif %}
{{ field.name }}: {{ field.type }} = betterproto.{{ field.field_type }}_field({{ field.number }}{% if field.field_type == 'map'%}, betterproto.{{ field.map_types[0] }}, betterproto.{{ field.map_types[1] }}{% endif %}{% if field.one_of %}, group="{{ field.one_of }}"{% endif %})
{% endfor %}
{% if not message.properties %}
pass
{% endif %}
{% endfor %}
{% for service in description.services %}
class {{ service.name }}Stub(betterproto.ServiceStub):
{% if service.comment %}
{{ service.comment }}
{% endif %}
{% for method in service.methods %}
async def {{ method.py_name }}(self{% if method.input_message and method.input_message.properties %}, *, {% for field in method.input_message.properties %}{{ field.name }}: {% if field.zero == "None" %}Optional[{{ field.type }}]{% else %}{{ field.type }}{% endif %} = {{ field.zero }}{% if not loop.last %}, {% endif %}{% endfor %}{% endif %}) -> {% if method.server_streaming %}AsyncGenerator[{{ method.output }}, None]{% else %}{{ method.output }}{% endif %}:
{% if method.comment %}
{{ method.comment }}
{% endif %}
request = {{ method.input }}()
{% for field in method.input_message.properties %}
{% if field.field_type == 'message' %}
if {{ field.name }} is not None:
request.{{ field.name }} = {{ field.name }}
{% else %}
request.{{ field.name }} = {{ field.name }}
{% endif %}
{% endfor %}
{% if method.server_streaming %}
async for response in self._unary_stream(
"{{ method.route }}",
{{ method.input }},
{{ method.output }},
request,
):
yield response
{% else %}
return await self._unary_unary(
"{{ method.route }}",
{{ method.input }},
{{ method.output }},
request,
)
{% endif %}
{% endfor %}
{% endfor %}

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tests/inputs/bytes/bytes.json → betterproto/tests/bytes.json
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2
tests/inputs/bytes/bytes.proto → betterproto/tests/bytes.proto
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@ -1,7 +1,5 @@
syntax = "proto3";
package bytes;
message Test {
bytes data = 1;
}

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tests/inputs/double/double-negative.json → betterproto/tests/double-negative.json
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tests/inputs/double/double.json → betterproto/tests/double.json
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tests/inputs/double/double.proto → betterproto/tests/double.proto
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syntax = "proto3";
package double;
message Test {
double count = 1;
}

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betterproto/tests/enums.json Normal file
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{
"greeting": "HEY"
}

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betterproto/tests/enums.proto Normal file
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syntax = "proto3";
// Enum for the different greeting types
enum Greeting {
HI = 0;
HEY = 1;
// Formal greeting
HELLO = 2;
}
message Test {
// Greeting enum example
Greeting greeting = 1;
}

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#!/usr/bin/env python
import os
# Force pure-python implementation instead of C++, otherwise imports
# break things because we can't properly reset the symbol database.
os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python"
import importlib
import json
import subprocess
import sys
from typing import Generator, Tuple
from google.protobuf import symbol_database
from google.protobuf.descriptor_pool import DescriptorPool
from google.protobuf.json_format import MessageToJson, Parse
root = os.path.dirname(os.path.realpath(__file__))
def get_files(end: str) -> Generator[str, None, None]:
for r, dirs, files in os.walk(root):
for filename in [f for f in files if f.endswith(end)]:
yield os.path.join(r, filename)
def get_base(filename: str) -> str:
return os.path.splitext(os.path.basename(filename))[0]
def ensure_ext(filename: str, ext: str) -> str:
if not filename.endswith(ext):
return filename + ext
return filename
if __name__ == "__main__":
os.chdir(root)
if len(sys.argv) > 1:
proto_files = [ensure_ext(f, ".proto") for f in sys.argv[1:]]
bases = {get_base(f) for f in proto_files}
json_files = [
f for f in get_files(".json") if get_base(f).split("-")[0] in bases
]
else:
proto_files = get_files(".proto")
json_files = get_files(".json")
for filename in proto_files:
print(f"Generating code for {os.path.basename(filename)}")
subprocess.run(
f"protoc --python_out=. {os.path.basename(filename)}", shell=True
)
subprocess.run(
f"protoc --plugin=protoc-gen-custom=../plugin.py --custom_out=. {os.path.basename(filename)}",
shell=True,
)
for filename in json_files:
# Reset the internal symbol database so we can import the `Test` message
# multiple times. Ugh.
sym = symbol_database.Default()
sym.pool = DescriptorPool()
parts = get_base(filename).split("-")
out = filename.replace(".json", ".bin")
print(f"Using {parts[0]}_pb2 to generate {os.path.basename(out)}")
imported = importlib.import_module(f"{parts[0]}_pb2")
input_json = open(filename).read()
parsed = Parse(input_json, imported.Test())
serialized = parsed.SerializeToString()
serialized_json = MessageToJson(parsed, preserving_proto_field_name=True)
s_loaded = json.loads(serialized_json)
in_loaded = json.loads(input_json)
if s_loaded != in_loaded:
raise AssertionError("Expected JSON to be equal:", s_loaded, in_loaded)
open(out, "wb").write(serialized)

3
betterproto/tests/int32-negative.json Normal file
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@ -0,0 +1,3 @@
{
"count": -150
}

3
betterproto/tests/int32.json Normal file
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@ -0,0 +1,3 @@
{
"count": 150
}

5
tests/inputs/int32/int32.proto → betterproto/tests/int32.proto
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@ -1,10 +1,7 @@
syntax = "proto3";
package int32;
// Some documentation about the Test message.
message Test {
// Some documentation about the count.
int32 positive = 1;
int32 negative = 2;
int32 count = 1;
}

0
tests/inputs/map/map.json → betterproto/tests/map.json
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2
tests/inputs/map/map.proto → betterproto/tests/map.proto
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@ -1,7 +1,5 @@
syntax = "proto3";
package map;
message Test {
map<string, int32> counts = 1;
}

0
tests/inputs/mapmessage/mapmessage.json → betterproto/tests/mapmessage.json
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2
tests/inputs/mapmessage/mapmessage.proto → betterproto/tests/mapmessage.proto
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@ -1,7 +1,5 @@
syntax = "proto3";
package mapmessage;
message Test {
map<string, Nested> items = 1;
}

3
tests/inputs/nested/nested.json → betterproto/tests/nested.json
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@ -2,6 +2,5 @@
"nested": {
"count": 150
},
"sibling": {},
"msg": "THIS"
"sibling": {}
}

14
tests/inputs/nested/nested.proto → betterproto/tests/nested.proto
View File

@ -1,26 +1,18 @@
syntax = "proto3";
package nested;
// A test message with a nested message inside of it.
message Test {
// This is the nested type.
message Nested {
// Stores a simple counter.
int32 count = 1;
}
// This is the nested enum.
enum Msg {
NONE = 0;
THIS = 1;
// Stores a simple counter.
int32 count = 1;
}
Nested nested = 1;
Sibling sibling = 2;
Sibling sibling2 = 3;
Msg msg = 4;
}
message Sibling {
int32 foo = 1;
}
}

3
betterproto/tests/oneof-name.json Normal file
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@ -0,0 +1,3 @@
{
"name": "foo"
}

3
betterproto/tests/oneof.json Normal file
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@ -0,0 +1,3 @@
{
"count": 1
}

8
betterproto/tests/oneof.proto Normal file
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@ -0,0 +1,8 @@
syntax = "proto3";
message Test {
oneof foo {
int32 count = 1;
string name = 2;
}
}

0
tests/inputs/ref/ref.json → betterproto/tests/ref.json
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0
tests/inputs/ref/ref.proto → betterproto/tests/ref.proto
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0
tests/inputs/repeated/repeated.json → betterproto/tests/repeated.json
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2
tests/inputs/repeated/repeated.proto → betterproto/tests/repeated.proto
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@ -1,7 +1,5 @@
syntax = "proto3";
package repeated;
message Test {
repeated string names = 1;
}

0
tests/inputs/repeatedmessage/repeatedmessage.json → betterproto/tests/repeatedmessage.json
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0
tests/inputs/ref/repeatedmessage.proto → betterproto/tests/repeatedmessage.proto
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0
tests/inputs/repeatedpacked/repeatedpacked.json → betterproto/tests/repeatedpacked.json
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2
tests/inputs/repeatedpacked/repeatedpacked.proto → betterproto/tests/repeatedpacked.proto
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@ -1,7 +1,5 @@
syntax = "proto3";
package repeatedpacked;
message Test {
repeated int32 counts = 1;
repeated sint64 signed = 2;

4
betterproto/tests/signed-negative.json Normal file
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@ -0,0 +1,4 @@
{
"signed_32": -150,
"signed_64": "-150"
}

4
betterproto/tests/signed.json Normal file
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@ -0,0 +1,4 @@
{
"signed_32": 150,
"signed_64": "150"
}

6
betterproto/tests/signed.proto Normal file
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@ -0,0 +1,6 @@
syntax = "proto3";
message Test {
sint32 signed_32 = 1;
sint64 signed_64 = 2;
}

117
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@ -0,0 +1,117 @@
import betterproto
from dataclasses import dataclass
def test_has_field():
@dataclass
class Bar(betterproto.Message):
baz: int = betterproto.int32_field(1)
@dataclass
class Foo(betterproto.Message):
bar: Bar = betterproto.message_field(1)
# Unset by default
foo = Foo()
assert betterproto.serialized_on_wire(foo.bar) == False
# Serialized after setting something
foo.bar.baz = 1
assert betterproto.serialized_on_wire(foo.bar) == True
# Still has it after setting the default value
foo.bar.baz = 0
assert betterproto.serialized_on_wire(foo.bar) == True
# Manual override (don't do this)
foo.bar._serialized_on_wire = False
assert betterproto.serialized_on_wire(foo.bar) == False
# Can manually set it but defaults to false
foo.bar = Bar()
assert betterproto.serialized_on_wire(foo.bar) == False
def test_enum_as_int_json():
class TestEnum(betterproto.Enum):
ZERO = 0
ONE = 1
@dataclass
class Foo(betterproto.Message):
bar: TestEnum = betterproto.enum_field(1)
# JSON strings are supported, but ints should still be supported too.
foo = Foo().from_dict({"bar": 1})
assert foo.bar == TestEnum.ONE
# Plain-ol'-ints should serialize properly too.
foo.bar = 1
assert foo.to_dict() == {"bar": "ONE"}
def test_unknown_fields():
@dataclass
class Newer(betterproto.Message):
foo: bool = betterproto.bool_field(1)
bar: int = betterproto.int32_field(2)
baz: str = betterproto.string_field(3)
@dataclass
class Older(betterproto.Message):
foo: bool = betterproto.bool_field(1)
newer = Newer(foo=True, bar=1, baz="Hello")
serialized_newer = bytes(newer)
# Unknown fields in `Newer` should round trip with `Older`
round_trip = bytes(Older().parse(serialized_newer))
assert serialized_newer == round_trip
new_again = Newer().parse(round_trip)
assert newer == new_again
def test_oneof_support():
@dataclass
class Sub(betterproto.Message):
val: int = betterproto.int32_field(1)
@dataclass
class Foo(betterproto.Message):
bar: int = betterproto.int32_field(1, group="group1")
baz: str = betterproto.string_field(2, group="group1")
sub: Sub = betterproto.message_field(3, group="group2")
abc: str = betterproto.string_field(4, group="group2")
foo = Foo()
assert betterproto.which_one_of(foo, "group1")[0] == ""
foo.bar = 1
foo.baz = "test"
# Other oneof fields should now be unset
assert foo.bar == 0
assert betterproto.which_one_of(foo, "group1")[0] == "baz"
foo.sub.val = 1
assert betterproto.serialized_on_wire(foo.sub)
foo.abc = "test"
# Group 1 shouldn't be touched, group 2 should have reset
assert foo.sub.val == 0
assert betterproto.serialized_on_wire(foo.sub) == False
assert betterproto.which_one_of(foo, "group2")[0] == "abc"
# Zero value should always serialize for one-of
foo = Foo(bar=0)
assert betterproto.which_one_of(foo, "group1")[0] == "bar"
assert bytes(foo) == b"\x08\x00"
# Round trip should also work
foo2 = Foo().parse(bytes(foo))
assert betterproto.which_one_of(foo2, "group1")[0] == "bar"
assert foo.bar == 0
assert betterproto.which_one_of(foo2, "group2")[0] == ""

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@ -0,0 +1,32 @@
import importlib
import json
import pytest
from .generate import get_base, get_files
inputs = get_files(".bin")
@pytest.mark.parametrize("filename", inputs)
def test_sample(filename: str) -> None:
module = get_base(filename).split("-")[0]
imported = importlib.import_module(f"betterproto.tests.{module}")
data_binary = open(filename, "rb").read()
data_dict = json.loads(open(filename.replace(".bin", ".json")).read())
t1 = imported.Test().parse(data_binary)
t2 = imported.Test().from_dict(data_dict)
print(t1)
print(t2)
# Equality should automagically work for dataclasses!
assert t1 == t2
# Generally this can't be relied on, but here we are aiming to match the
# existing Python implementation and aren't doing anything tricky.
# https://developers.google.com/protocol-buffers/docs/encoding#implications
assert bytes(t1) == data_binary
assert bytes(t2) == data_binary
assert t1.to_dict() == data_dict
assert t2.to_dict() == data_dict

31
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@ -1,31 +0,0 @@
.. currentmodule:: betterproto
API reference
=============
The following document outlines betterproto's api. **None** of these classes should be
extended by the user manually.
Message
--------
.. autoclass:: betterproto.Message
:members:
:special-members: __bytes__, __bool__
.. autofunction:: betterproto.serialized_on_wire
.. autofunction:: betterproto.which_one_of
Enumerations
-------------
.. autoclass:: betterproto.Enum()
:members:
.. autoclass:: betterproto.Casing()
:members:

60
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@ -1,60 +0,0 @@
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
import pathlib
import toml
# -- Project information -----------------------------------------------------
project = "betterproto"
copyright = "2019 Daniel G. Taylor"
author = "danielgtaylor"
pyproject = toml.load(open(pathlib.Path(__file__).parent.parent / "pyproject.toml"))
# The full version, including alpha/beta/rc tags.
release = pyproject["tool"]["poetry"]["version"]
# -- General configuration ---------------------------------------------------
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
"sphinx.ext.autodoc",
"sphinx.ext.intersphinx",
"sphinx.ext.napoleon",
]
autodoc_member_order = "bysource"
autodoc_typehints = "none"
extlinks = {
"issue": ("https://github.com/danielgtaylor/python-betterproto/issues/%s", "GH-"),
}
# Links used for cross-referencing stuff in other documentation
intersphinx_mapping = {
"py": ("https://docs.python.org/3", None),
}
# -- Options for HTML output -------------------------------------------------
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = "friendly"
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = "sphinx_rtd_theme"

33
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@ -1,33 +0,0 @@
Welcome to betterproto's documentation!
=======================================
betterproto is a protobuf compiler and interpreter. It improves the experience of using
Protobuf and gRPC in Python, by generating readable, understandable, and idiomatic
Python code, using modern language features.
Features:
~~~~~~~~~
- Generated messages are both binary & JSON serializable
- Messages use relevant python types, e.g. ``Enum``, ``datetime`` and ``timedelta``
objects
- ``async``/``await`` support for gRPC Clients and Servers
- Generates modern, readable, idiomatic python code
Contents:
~~~~~~~~~
.. toctree::
:maxdepth: 2
quick-start
api
migrating
If you still can't find what you're looking for, try in one of the following pages:
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

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@ -1,159 +0,0 @@
Migrating Guide
===============
Google's protocolbuffers
------------------------
betterproto has a mostly 1 to 1 drop in replacement for Google's protocolbuffers (after
regenerating your protobufs of course) although there are some minor differences.
.. note::
betterproto implements the same basic methods including:
- :meth:`betterproto.Message.FromString`
- :meth:`betterproto.Message.SerializeToString`
for compatibility purposes, however it is important to note that these are
effectively aliases for :meth:`betterproto.Message.parse` and
:meth:`betterproto.Message.__bytes__` respectively.
Determining if a message was sent
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Sometimes 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.
Use ``betterproto.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 generated ``Message`` class to prevent name clashes. Note that it only
supports Proto 3 and thus can only be used to check if ``Message`` fields are set.
You cannot check if a scalar was sent on the wire.
.. code-block:: python
# Old way (official Google Protobuf package)
>>> mymessage.HasField('myfield')
True
# New way (this project)
>>> betterproto.serialized_on_wire(mymessage.myfield)
True
One-of Support
~~~~~~~~~~~~~~
Protobuf supports grouping fields in a oneof clause. Only one of the fields in the group
may be set at a given time. For example, given the proto:
.. code-block:: proto
syntax = "proto3";
message Test {
oneof foo {
bool on = 1;
int32 count = 2;
string name = 3;
}
}
You can use ``betterproto.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 and
``None`` if unset. Again this is a little different than the official Google code
generator:
.. code-block:: python
# 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 Types
~~~~~~~~~~~~~~~~~~~~~~~
Google 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 Message`` | ``Python Type`` | ``Default`` |
+===============================+=================================================+==========================+
| ``google.protobuf.duration`` | :class:`datetime.timedelta` | ``0`` |
+-------------------------------+-------------------------------------------------+--------------------------+
| ``google.protobuf.timestamp`` | ``Timezone-aware`` :class:`datetime.datetime` | ``1970-01-01T00:00:00Z`` |
+-------------------------------+-------------------------------------------------+--------------------------+
| ``google.protobuf.*Value`` | ``Optional[...]``/``None`` | ``None`` |
+-------------------------------+-------------------------------------------------+--------------------------+
| ``google.protobuf.*`` | ``betterproto.lib.std.google.protobuf.*`` | ``None`` |
+-------------------------------+-------------------------------------------------+--------------------------+
| ``google.protobuf.*`` | ``betterproto.lib.pydantic.google.protobuf.*`` | ``None`` |
+-------------------------------+-------------------------------------------------+--------------------------+
For the wrapper types, the Python type corresponds to the wrapped type, e.g.
``google.protobuf.BoolValue`` becomes ``Optional[bool]`` while
``google.protobuf.Int32Value`` becomes ``Optional[int]``. All of the optional values
default to None, so don't forget to check for that possible state.
Given:
.. code-block:: proto
syntax = "proto3";
import "google/protobuf/duration.proto";
import "google/protobuf/timestamp.proto";
import "google/protobuf/wrappers.proto";
message Test {
google.protobuf.BoolValue maybe = 1;
google.protobuf.Timestamp ts = 2;
google.protobuf.Duration duration = 3;
}
You can use it as such:
.. code-block:: python
>>> t = Test().from_dict({"maybe": True, "ts": "2019-01-01T12:00:00Z", "duration": "1.200s"})
>>> t
Test(maybe=True, ts=datetime.datetime(2019, 1, 1, 12, 0, tzinfo=datetime.timezone.utc), duration=datetime.timedelta(seconds=1, microseconds=200000))
>>> t.ts - t.duration
datetime.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'}
[1.2.5] to [2.0.0b1]
--------------------
Updated package structures
~~~~~~~~~~~~~~~~~~~~~~~~~~
Generated code now strictly follows the *package structure* of the ``.proto`` files.
Consequently ``.proto`` files without a package will be combined in a single
``__init__.py`` file. To avoid overwriting existing ``__init__.py`` files, its best
to compile into a dedicated subdirectory.
Upgrading:
- Remove your previously compiled ``.py`` files.
- Create a new *empty* directory, e.g. ``generated`` or ``lib/generated/proto`` etc.
- Regenerate your python files into this directory
- Update import statements, e.g. ``import ExampleMessage from generated``

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@ -1,222 +0,0 @@
Getting Started
===============
Installation
++++++++++++
Installation from PyPI is as simple as running:
.. code-block:: sh
python3 -m pip install -U betterproto
If you are using Windows, then the following should be used instead:
.. code-block:: sh
py -3 -m pip install -U betterproto
To include the protoc plugin, install betterproto[compiler] instead of betterproto,
e.g.
.. code-block:: sh
python3 -m pip install -U "betterproto[compiler]"
Compiling proto files
+++++++++++++++++++++
Given you installed the compiler and have a proto file, e.g ``example.proto``:
.. code-block:: proto
syntax = "proto3";
package hello;
// Greeting represents a message you can tell a user.
message Greeting {
string message = 1;
}
To compile the proto you would run the following:
You can run the following to invoke protoc directly:
.. code-block:: sh
mkdir hello
protoc -I . --python_betterproto_out=lib example.proto
or run the following to invoke protoc via grpcio-tools:
.. code-block:: sh
pip install grpcio-tools
python -m grpc_tools.protoc -I . --python_betterproto_out=lib example.proto
This will generate ``lib/__init__.py`` which looks like:
.. code-block:: python
# Generated by the protocol buffer compiler. DO NOT EDIT!
# sources: example.proto
# plugin: python-betterproto
from dataclasses import dataclass
import betterproto
@dataclass
class Greeting(betterproto.Message):
"""Greeting represents a message you can tell a user."""
message: str = betterproto.string_field(1)
Then to use it:
.. code-block:: python
>>> from lib import Greeting
>>> test = Greeting()
>>> test
Greeting(message='')
>>> test.message = "Hey!"
>>> test
Greeting(message="Hey!")
>>> bytes(test)
b'\n\x04Hey!'
>>> Greeting().parse(serialized)
Greeting(message="Hey!")
Async gRPC Support
++++++++++++++++++
The generated code includes `grpclib <https://grpclib.readthedocs.io/en/latest>`_ based
stub (client and server) classes for rpc services declared in the input proto files.
It is enabled by default.
Given a service definition similar to the one below:
.. code-block:: proto
syntax = "proto3";
package echo;
message EchoRequest {
string value = 1;
// Number of extra times to echo
uint32 extra_times = 2;
}
message EchoResponse {
repeated string values = 1;
}
message EchoStreamResponse {
string value = 1;
}
service Echo {
rpc Echo(EchoRequest) returns (EchoResponse);
rpc EchoStream(EchoRequest) returns (stream EchoStreamResponse);
}
The generated client can be used like so:
.. code-block:: python
import asyncio
from grpclib.client import Channel
import echo
async def main():
channel = Channel(host="127.0.0.1", port=50051)
service = echo.EchoStub(channel)
response = await service.echo(value="hello", extra_times=1)
print(response)
async for response in service.echo_stream(value="hello", extra_times=1):
print(response)
# don't forget to close the channel when you're done!
channel.close()
asyncio.run(main()) # python 3.7 only
# outputs
EchoResponse(values=['hello', 'hello'])
EchoStreamResponse(value='hello')
EchoStreamResponse(value='hello')
The server-facing stubs 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:
.. code-block:: python
from echo import EchoBase
from grpclib.server import Server
from typing import AsyncIterator
class EchoService(EchoBase):
async def echo(self, value: str, extra_times: int) -> "EchoResponse":
return value
async def echo_stream(
self, value: str, extra_times: int
) -> AsyncIterator["EchoStreamResponse"]:
for _ in range(extra_times):
yield value
async def start_server():
HOST = "127.0.0.1"
PORT = 1337
server = Server([EchoService()])
await server.start(HOST, PORT)
await server.serve_forever()
JSON
++++
Message objects include :meth:`betterproto.Message.to_json` and
:meth:`betterproto.Message.from_json` methods for JSON (de)serialisation, and
:meth:`betterproto.Message.to_dict`, :meth:`betterproto.Message.from_dict` for
converting back and forth from JSON serializable dicts.
For compatibility the default is to convert field names to
:attr:`betterproto.Casing.CAMEL`. You can control this behavior by passing a
different casing value, e.g:
.. code-block:: python
@dataclass
class MyMessage(betterproto.Message):
a_long_field_name: str = betterproto.string_field(1)
>>> test = MyMessage(a_long_field_name="Hello World!")
>>> test.to_dict(betterproto.Casing.SNAKE)
{"a_long_field_name": "Hello World!"}
>>> test.to_dict(betterproto.Casing.CAMEL)
{"aLongFieldName": "Hello World!"}
>>> test.to_json(indent=2)
'{\n "aLongFieldName": "Hello World!"\n}'
>>> test.from_dict({"aLongFieldName": "Goodbye World!"})
>>> test.a_long_field_name
"Goodbye World!"

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176
pyproject.toml
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@ -1,169 +1,9 @@
[project]
name = "betterproto"
version = "2.0.0b7"
description = "A better Protobuf / gRPC generator & library"
authors = [
{name = "Daniel G. Taylor", email = "danielgtaylor@gmail.com"}
]
readme = "README.md"
repository = "https://github.com/danielgtaylor/python-betterproto"
keywords = ["protobuf", "gRPC"]
license = "MIT"
packages = [
{ include = "betterproto", from = "src" }
]
requires-python = ">=3.9,<4.0"
dynamic = ["dependencies"]
[tool.black]
target-version = ['py37']
[tool.poetry.dependencies]
# The Ruff version is pinned. To update it, also update it in .pre-commit-config.yaml
ruff = { version = "~0.9.1", optional = true }
grpclib = "^0.4.1"
jinja2 = { version = ">=3.0.3", optional = true }
python-dateutil = "^2.8"
typing-extensions = "^4.7.1"
betterproto-rust-codec = { version = "0.1.1", optional = true }
[tool.poetry.group.dev.dependencies]
asv = "^0.6.4"
bpython = "^0.24"
jinja2 = ">=3.0.3"
mypy = "^1.11.2"
sphinx = "7.4.7"
sphinx-rtd-theme = "3.0.2"
pre-commit = "^4.0.1"
grpcio-tools = "^1.54.2"
tox = "^4.0.0"
[tool.poetry.group.test.dependencies]
poethepoet = ">=0.9.0"
pytest = "^7.4.4"
pytest-asyncio = "^0.23.8"
pytest-cov = "^6.0.0"
pytest-mock = "^3.1.1"
pydantic = ">=2.0,<3"
protobuf = "^5"
cachelib = "^0.13.0"
tomlkit = ">=0.7.0"
[project.scripts]
protoc-gen-python_betterproto = "betterproto.plugin:main"
[project.optional-dependencies]
compiler = ["ruff", "jinja2"]
rust-codec = ["betterproto-rust-codec"]
[tool.ruff]
extend-exclude = ["tests/output_*"]
target-version = "py38"
[tool.ruff.lint.isort]
combine-as-imports = true
lines-after-imports = 2
# Dev workflow tasks
[tool.poe.tasks.generate]
script = "tests.generate:main"
help = "Generate test cases (do this once before running test)"
[tool.poe.tasks.test]
cmd = "pytest"
help = "Run tests"
[tool.poe.tasks.types]
cmd = "mypy src --ignore-missing-imports"
help = "Check types with mypy"
[tool.poe.tasks.format]
sequence = ["_format", "_sort-imports"]
help = "Format the source code, and sort the imports"
[tool.poe.tasks.check]
sequence = ["_check-format", "_check-imports"]
help = "Check that the source code is formatted and the imports sorted"
[tool.poe.tasks._format]
cmd = "ruff format src tests"
help = "Format the source code without sorting the imports"
[tool.poe.tasks._sort-imports]
cmd = "ruff check --select I --fix src tests"
help = "Sort the imports"
[tool.poe.tasks._check-format]
cmd = "ruff format --diff src tests"
help = "Check that the source code is formatted"
[tool.poe.tasks._check-imports]
cmd = "ruff check --select I src tests"
help = "Check that the imports are sorted"
[tool.poe.tasks.docs]
cmd = "sphinx-build docs docs/build"
help = "Build the sphinx docs"
[tool.poe.tasks.bench]
shell = "asv run master^! && asv run HEAD^! && asv compare master HEAD"
help = "Benchmark current commit vs. master branch"
[tool.poe.tasks.clean]
cmd = """
rm -rf .asv .coverage .mypy_cache .pytest_cache
dist betterproto.egg-info **/__pycache__
testsoutput_*
"""
help = "Clean out generated files from the workspace"
[tool.poe.tasks.generate_lib]
cmd = """
protoc
--plugin=protoc-gen-custom=src/betterproto/plugin/main.py
--custom_opt=INCLUDE_GOOGLE
--custom_out=src/betterproto/lib/std
-I C:\\work\\include
C:\\work\\include\\google\\protobuf\\**\\*.proto
"""
help = "Regenerate the types in betterproto.lib.std.google"
# CI tasks
[tool.poe.tasks.full-test]
shell = "poe generate && tox"
help = "Run tests with multiple pythons"
[tool.doc8]
paths = ["docs"]
max_line_length = 88
[tool.doc8.ignore_path_errors]
"docs/migrating.rst" = [
"D001", # contains table which is longer than 88 characters long
]
[tool.coverage.run]
omit = ["betterproto/tests/*"]
[tool.tox]
legacy_tox_ini = """
[tox]
requires =
tox>=4.2
tox-poetry-installer[poetry]==1.0.0b1
env_list =
py311
py38
py37
[testenv]
commands =
pytest {posargs: --cov betterproto}
poetry_dep_groups =
test
require_locked_deps = true
require_poetry = true
"""
[build-system]
requires = ["poetry-core>=2.0.0,<3"]
build-backend = "poetry.core.masonry.api"
[tool.isort]
multi_line_output = 3
include_trailing_comma = true
force_grid_wrap = 0
use_parentheses = true
line_length = 88

5
pytest.ini
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@ -1,5 +0,0 @@
[pytest]
python_files = test_*.py
python_classes =
norecursedirs = **/output_*
addopts = -p no:warnings

22
setup.py Normal file
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@ -0,0 +1,22 @@
from setuptools import setup, find_packages
setup(
name="betterproto",
version="1.0",
description="A better Protobuf / gRPC generator & library",
url="http://github.com/danielgtaylor/python-betterproto",
author="Daniel G. Taylor",
author_email="danielgtaylor@gmail.com",
license="MIT",
entry_points={
"console_scripts": ["protoc-gen-python_betterproto=betterproto.plugin:main"]
},
packages=find_packages(
exclude=["tests", "*.tests", "*.tests.*", "output", "output.*"]
),
package_data={"betterproto": ["py.typed", "templates/template.py"]},
python_requires=">=3.7",
install_requires=["grpclib"],
extras_require={"compiler": ["jinja2", "protobuf"]},
zip_safe=False,
)

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src/betterproto/__init__.py
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src/betterproto/_types.py
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@ -1,14 +0,0 @@
from typing import (
TYPE_CHECKING,
TypeVar,
)
if TYPE_CHECKING:
from grpclib._typing import IProtoMessage
from . import Message
# Bound type variable to allow methods to return `self` of subclasses
T = TypeVar("T", bound="Message")
ST = TypeVar("ST", bound="IProtoMessage")

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src/betterproto/_version.py
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try:
from importlib import metadata
except ImportError: # for Python<3.8
import importlib_metadata as metadata # type: ignore
__version__ = metadata.version("betterproto")

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src/betterproto/casing.py
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@ -1,143 +0,0 @@
import keyword
import re
# Word delimiters and symbols that will not be preserved when re-casing.
# language=PythonRegExp
SYMBOLS = "[^a-zA-Z0-9]*"
# Optionally capitalized word.
# language=PythonRegExp
WORD = "[A-Z]*[a-z]*[0-9]*"
# Uppercase word, not followed by lowercase letters.
# language=PythonRegExp
WORD_UPPER = "[A-Z]+(?![a-z])[0-9]*"
def safe_snake_case(value: str) -> str:
"""Snake case a value taking into account Python keywords."""
value = snake_case(value)
value = sanitize_name(value)
return value
def snake_case(value: str, strict: bool = True) -> str:
"""
Join words with an underscore into lowercase and remove symbols.
Parameters
-----------
value: :class:`str`
The value to convert.
strict: :class:`bool`
Whether or not to force single underscores.
Returns
--------
:class:`str`
The value in snake_case.
"""
def substitute_word(symbols: str, word: str, is_start: bool) -> str:
if not word:
return ""
if strict:
delimiter_count = 0 if is_start else 1 # Single underscore if strict.
elif is_start:
delimiter_count = len(symbols)
elif word.isupper() or word.islower():
delimiter_count = max(
1, len(symbols)
) # Preserve all delimiters if not strict.
else:
delimiter_count = len(symbols) + 1 # Extra underscore for leading capital.
return ("_" * delimiter_count) + word.lower()
snake = re.sub(
f"(^)?({SYMBOLS})({WORD_UPPER}|{WORD})",
lambda groups: substitute_word(groups[2], groups[3], groups[1] is not None),
value,
)
return snake
def pascal_case(value: str, strict: bool = True) -> str:
"""
Capitalize each word and remove symbols.
Parameters
-----------
value: :class:`str`
The value to convert.
strict: :class:`bool`
Whether or not to output only alphanumeric characters.
Returns
--------
:class:`str`
The value in PascalCase.
"""
def substitute_word(symbols, word):
if strict:
return word.capitalize() # Remove all delimiters
if word.islower():
delimiter_length = len(symbols[:-1]) # Lose one delimiter
else:
delimiter_length = len(symbols) # Preserve all delimiters
return ("_" * delimiter_length) + word.capitalize()
return re.sub(
f"({SYMBOLS})({WORD_UPPER}|{WORD})",
lambda groups: substitute_word(groups[1], groups[2]),
value,
)
def camel_case(value: str, strict: bool = True) -> str:
"""
Capitalize all words except first and remove symbols.
Parameters
-----------
value: :class:`str`
The value to convert.
strict: :class:`bool`
Whether or not to output only alphanumeric characters.
Returns
--------
:class:`str`
The value in camelCase.
"""
return lowercase_first(pascal_case(value, strict=strict))
def lowercase_first(value: str) -> str:
"""
Lower cases the first character of the value.
Parameters
----------
value: :class:`str`
The value to lower case.
Returns
-------
:class:`str`
The lower cased string.
"""
return value[0:1].lower() + value[1:]
def sanitize_name(value: str) -> str:
# https://www.python.org/dev/peps/pep-0008/#descriptive-naming-styles
if keyword.iskeyword(value):
return f"{value}_"
if not value.isidentifier():
return f"_{value}"
return value

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src/betterproto/compile/__init__.py
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183
src/betterproto/compile/importing.py
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@ -1,183 +0,0 @@
from __future__ import annotations
import os
import re
from typing import (
TYPE_CHECKING,
Dict,
List,
Set,
Tuple,
Type,
)
from ..casing import safe_snake_case
from ..lib.google import protobuf as google_protobuf
from .naming import pythonize_class_name
if TYPE_CHECKING:
from ..plugin.typing_compiler import TypingCompiler
WRAPPER_TYPES: Dict[str, Type] = {
".google.protobuf.DoubleValue": google_protobuf.DoubleValue,
".google.protobuf.FloatValue": google_protobuf.FloatValue,
".google.protobuf.Int32Value": google_protobuf.Int32Value,
".google.protobuf.Int64Value": google_protobuf.Int64Value,
".google.protobuf.UInt32Value": google_protobuf.UInt32Value,
".google.protobuf.UInt64Value": google_protobuf.UInt64Value,
".google.protobuf.BoolValue": google_protobuf.BoolValue,
".google.protobuf.StringValue": google_protobuf.StringValue,
".google.protobuf.BytesValue": google_protobuf.BytesValue,
}
def parse_source_type_name(field_type_name: str) -> Tuple[str, str]:
"""
Split full source type name into package and type name.
E.g. 'root.package.Message' -> ('root.package', 'Message')
'root.Message.SomeEnum' -> ('root', 'Message.SomeEnum')
"""
package_match = re.match(r"^\.?([^A-Z]+)\.(.+)", field_type_name)
if package_match:
package = package_match.group(1)
name = package_match.group(2)
else:
package = ""
name = field_type_name.lstrip(".")
return package, name
def get_type_reference(
*,
package: str,
imports: set,
source_type: str,
typing_compiler: TypingCompiler,
unwrap: bool = True,
pydantic: bool = False,
) -> str:
"""
Return a Python type name for a proto type reference. Adds the import if
necessary. Unwraps well known type if required.
"""
if unwrap:
if source_type in WRAPPER_TYPES:
wrapped_type = type(WRAPPER_TYPES[source_type]().value)
return typing_compiler.optional(wrapped_type.__name__)
if source_type == ".google.protobuf.Duration":
return "timedelta"
elif source_type == ".google.protobuf.Timestamp":
return "datetime"
source_package, source_type = parse_source_type_name(source_type)
current_package: List[str] = package.split(".") if package else []
py_package: List[str] = source_package.split(".") if source_package else []
py_type: str = pythonize_class_name(source_type)
compiling_google_protobuf = current_package == ["google", "protobuf"]
importing_google_protobuf = py_package == ["google", "protobuf"]
if importing_google_protobuf and not compiling_google_protobuf:
py_package = (
["betterproto", "lib"] + (["pydantic"] if pydantic else []) + py_package
)
if py_package[:1] == ["betterproto"]:
return reference_absolute(imports, py_package, py_type)
if py_package == current_package:
return reference_sibling(py_type)
if py_package[: len(current_package)] == current_package:
return reference_descendent(current_package, imports, py_package, py_type)
if current_package[: len(py_package)] == py_package:
return reference_ancestor(current_package, imports, py_package, py_type)
return reference_cousin(current_package, imports, py_package, py_type)
def reference_absolute(imports: Set[str], py_package: List[str], py_type: str) -> str:
"""
Returns a reference to a python type located in the root, i.e. sys.path.
"""
string_import = ".".join(py_package)
string_alias = safe_snake_case(string_import)
imports.add(f"import {string_import} as {string_alias}")
return f'"{string_alias}.{py_type}"'
def reference_sibling(py_type: str) -> str:
"""
Returns a reference to a python type within the same package as the current package.
"""
return f'"{py_type}"'
def reference_descendent(
current_package: List[str], imports: Set[str], py_package: List[str], py_type: str
) -> str:
"""
Returns a reference to a python type in a package that is a descendent of the
current package, and adds the required import that is aliased to avoid name
conflicts.
"""
importing_descendent = py_package[len(current_package) :]
string_from = ".".join(importing_descendent[:-1])
string_import = importing_descendent[-1]
if string_from:
string_alias = "_".join(importing_descendent)
imports.add(f"from .{string_from} import {string_import} as {string_alias}")
return f'"{string_alias}.{py_type}"'
else:
imports.add(f"from . import {string_import}")
return f'"{string_import}.{py_type}"'
def reference_ancestor(
current_package: List[str], imports: Set[str], py_package: List[str], py_type: str
) -> str:
"""
Returns a reference to a python type in a package which is an ancestor to the
current package, and adds the required import that is aliased (if possible) to avoid
name conflicts.
Adds trailing __ to avoid name mangling (python.org/dev/peps/pep-0008/#id34).
"""
distance_up = len(current_package) - len(py_package)
if py_package:
string_import = py_package[-1]
string_alias = f"_{'_' * distance_up}{string_import}__"
string_from = f"..{'.' * distance_up}"
imports.add(f"from {string_from} import {string_import} as {string_alias}")
return f'"{string_alias}.{py_type}"'
else:
string_alias = f"{'_' * distance_up}{py_type}__"
imports.add(f"from .{'.' * distance_up} import {py_type} as {string_alias}")
return f'"{string_alias}"'
def reference_cousin(
current_package: List[str], imports: Set[str], py_package: List[str], py_type: str
) -> str:
"""
Returns a reference to a python type in a package that is not descendent, ancestor
or sibling, and adds the required import that is aliased to avoid name conflicts.
"""
shared_ancestry = os.path.commonprefix([current_package, py_package]) # type: ignore
distance_up = len(current_package) - len(shared_ancestry)
string_from = f".{'.' * distance_up}" + ".".join(
py_package[len(shared_ancestry) : -1]
)
string_import = py_package[-1]
# Add trailing __ to avoid name mangling (python.org/dev/peps/pep-0008/#id34)
string_alias = (
f"{'_' * distance_up}"
+ safe_snake_case(".".join(py_package[len(shared_ancestry) :]))
+ "__"
)
imports.add(f"from {string_from} import {string_import} as {string_alias}")
return f'"{string_alias}.{py_type}"'

21
src/betterproto/compile/naming.py
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@ -1,21 +0,0 @@
from betterproto import casing
def pythonize_class_name(name: str) -> str:
return casing.pascal_case(name)
def pythonize_field_name(name: str) -> str:
return casing.safe_snake_case(name)
def pythonize_method_name(name: str) -> str:
return casing.safe_snake_case(name)
def pythonize_enum_member_name(name: str, enum_name: str) -> str:
enum_name = casing.snake_case(enum_name).upper()
find = name.find(enum_name)
if find != -1:
name = name[find + len(enum_name) :].strip("_")
return casing.sanitize_name(name)

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src/betterproto/enum.py
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@ -1,197 +0,0 @@
from __future__ import annotations
from enum import (
EnumMeta,
IntEnum,
)
from types import MappingProxyType
from typing import (
TYPE_CHECKING,
Any,
Dict,
Optional,
Tuple,
)
if TYPE_CHECKING:
from collections.abc import (
Generator,
Mapping,
)
from typing_extensions import (
Never,
Self,
)
def _is_descriptor(obj: object) -> bool:
return (
hasattr(obj, "__get__") or hasattr(obj, "__set__") or hasattr(obj, "__delete__")
)
class EnumType(EnumMeta if TYPE_CHECKING else type):
_value_map_: Mapping[int, Enum]
_member_map_: Mapping[str, Enum]
def __new__(
mcs, name: str, bases: Tuple[type, ...], namespace: Dict[str, Any]
) -> Self:
value_map = {}
member_map = {}
new_mcs = type(
f"{name}Type",
tuple(
dict.fromkeys(
[base.__class__ for base in bases if base.__class__ is not type]
+ [EnumType, type]
)
), # reorder the bases so EnumType and type are last to avoid conflicts
{"_value_map_": value_map, "_member_map_": member_map},
)
members = {
name: value
for name, value in namespace.items()
if not _is_descriptor(value) and not name.startswith("__")
}
cls = type.__new__(
new_mcs,
name,
bases,
{key: value for key, value in namespace.items() if key not in members},
)
# this allows us to disallow member access from other members as
# members become proper class variables
for name, value in members.items():
member = value_map.get(value)
if member is None:
member = cls.__new__(cls, name=name, value=value) # type: ignore
value_map[value] = member
member_map[name] = member
type.__setattr__(new_mcs, name, member)
return cls
if not TYPE_CHECKING:
def __call__(cls, value: int) -> Enum:
try:
return cls._value_map_[value]
except (KeyError, TypeError):
raise ValueError(f"{value!r} is not a valid {cls.__name__}") from None
def __iter__(cls) -> Generator[Enum, None, None]:
yield from cls._member_map_.values()
def __reversed__(cls) -> Generator[Enum, None, None]:
yield from reversed(cls._member_map_.values())
def __getitem__(cls, key: str) -> Enum:
return cls._member_map_[key]
@property
def __members__(cls) -> MappingProxyType[str, Enum]:
return MappingProxyType(cls._member_map_)
def __repr__(cls) -> str:
return f"<enum {cls.__name__!r}>"
def __len__(cls) -> int:
return len(cls._member_map_)
def __setattr__(cls, name: str, value: Any) -> Never:
raise AttributeError(f"{cls.__name__}: cannot reassign Enum members.")
def __delattr__(cls, name: str) -> Never:
raise AttributeError(f"{cls.__name__}: cannot delete Enum members.")
def __contains__(cls, member: object) -> bool:
return isinstance(member, cls) and member.name in cls._member_map_
class Enum(IntEnum if TYPE_CHECKING else int, metaclass=EnumType):
"""
The base class for protobuf enumerations, all generated enumerations will
inherit from this. Emulates `enum.IntEnum`.
"""
name: Optional[str]
value: int
if not TYPE_CHECKING:
def __new__(cls, *, name: Optional[str], value: int) -> Self:
self = super().__new__(cls, value)
super().__setattr__(self, "name", name)
super().__setattr__(self, "value", value)
return self
def __getnewargs_ex__(self) -> Tuple[Tuple[()], Dict[str, Any]]:
return (), {"name": self.name, "value": self.value}
def __str__(self) -> str:
return self.name or "None"
def __repr__(self) -> str:
return f"{self.__class__.__name__}.{self.name}"
def __setattr__(self, key: str, value: Any) -> Never:
raise AttributeError(
f"{self.__class__.__name__} Cannot reassign a member's attributes."
)
def __delattr__(self, item: Any) -> Never:
raise AttributeError(
f"{self.__class__.__name__} Cannot delete a member's attributes."
)
def __copy__(self) -> Self:
return self
def __deepcopy__(self, memo: Any) -> Self:
return self
@classmethod
def try_value(cls, value: int = 0) -> Self:
"""Return the value which corresponds to the value.
Parameters
-----------
value: :class:`int`
The value of the enum member to get.
Returns
-------
:class:`Enum`
The corresponding member or a new instance of the enum if
``value`` isn't actually a member.
"""
try:
return cls._value_map_[value]
except (KeyError, TypeError):
return cls.__new__(cls, name=None, value=value)
@classmethod
def from_string(cls, name: str) -> Self:
"""Return the value which corresponds to the string name.
Parameters
-----------
name: :class:`str`
The name of the enum member to get.
Raises
-------
:exc:`ValueError`
The member was not found in the Enum.
"""
try:
return cls._member_map_[name]
except KeyError as e:
raise ValueError(f"Unknown value {name} for enum {cls.__name__}") from e

0
src/betterproto/grpc/__init__.py
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177
src/betterproto/grpc/grpclib_client.py
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@ -1,177 +0,0 @@
import asyncio
from abc import ABC
from typing import (
TYPE_CHECKING,
AsyncIterable,
AsyncIterator,
Collection,
Iterable,
Mapping,
Optional,
Tuple,
Type,
Union,
)
import grpclib.const
if TYPE_CHECKING:
from grpclib.client import Channel
from grpclib.metadata import Deadline
from .._types import (
ST,
IProtoMessage,
Message,
T,
)
Value = Union[str, bytes]
MetadataLike = Union[Mapping[str, Value], Collection[Tuple[str, Value]]]
MessageSource = Union[Iterable["IProtoMessage"], AsyncIterable["IProtoMessage"]]
class ServiceStub(ABC):
"""
Base class for async gRPC clients.
"""
def __init__(
self,
channel: "Channel",
*,
timeout: Optional[float] = None,
deadline: Optional["Deadline"] = None,
metadata: Optional[MetadataLike] = None,
) -> None:
self.channel = channel
self.timeout = timeout
self.deadline = deadline
self.metadata = metadata
def __resolve_request_kwargs(
self,
timeout: Optional[float],
deadline: Optional["Deadline"],
metadata: Optional[MetadataLike],
):
return {
"timeout": self.timeout if timeout is None else timeout,
"deadline": self.deadline if deadline is None else deadline,
"metadata": self.metadata if metadata is None else metadata,
}
async def _unary_unary(
self,
route: str,
request: "IProtoMessage",
response_type: Type["T"],
*,
timeout: Optional[float] = None,
deadline: Optional["Deadline"] = None,
metadata: Optional[MetadataLike] = None,
) -> "T":
"""Make a unary request and return the response."""
async with self.channel.request(
route,
grpclib.const.Cardinality.UNARY_UNARY,
type(request),
response_type,
**self.__resolve_request_kwargs(timeout, deadline, metadata),
) as stream:
await stream.send_message(request, end=True)
response = await stream.recv_message()
assert response is not None
return response
async def _unary_stream(
self,
route: str,
request: "IProtoMessage",
response_type: Type["T"],
*,
timeout: Optional[float] = None,
deadline: Optional["Deadline"] = None,
metadata: Optional[MetadataLike] = None,
) -> AsyncIterator["T"]:
"""Make a unary request and return the stream response iterator."""
async with self.channel.request(
route,
grpclib.const.Cardinality.UNARY_STREAM,
type(request),
response_type,
**self.__resolve_request_kwargs(timeout, deadline, metadata),
) as stream:
await stream.send_message(request, end=True)
async for message in stream:
yield message
async def _stream_unary(
self,
route: str,
request_iterator: MessageSource,
request_type: Type["IProtoMessage"],
response_type: Type["T"],
*,
timeout: Optional[float] = None,
deadline: Optional["Deadline"] = None,
metadata: Optional[MetadataLike] = None,
) -> "T":
"""Make a stream request and return the response."""
async with self.channel.request(
route,
grpclib.const.Cardinality.STREAM_UNARY,
request_type,
response_type,
**self.__resolve_request_kwargs(timeout, deadline, metadata),
) as stream:
await stream.send_request()
await self._send_messages(stream, request_iterator)
response = await stream.recv_message()
assert response is not None
return response
async def _stream_stream(
self,
route: str,
request_iterator: MessageSource,
request_type: Type["IProtoMessage"],
response_type: Type["T"],
*,
timeout: Optional[float] = None,
deadline: Optional["Deadline"] = None,
metadata: Optional[MetadataLike] = None,
) -> AsyncIterator["T"]:
"""
Make a stream request and return an AsyncIterator to iterate over response
messages.
"""
async with self.channel.request(
route,
grpclib.const.Cardinality.STREAM_STREAM,
request_type,
response_type,
**self.__resolve_request_kwargs(timeout, deadline, metadata),
) as stream:
await stream.send_request()
sending_task = asyncio.ensure_future(
self._send_messages(stream, request_iterator)
)
try:
async for response in stream:
yield response
except:
sending_task.cancel()
raise
@staticmethod
async def _send_messages(stream, messages: MessageSource):
if isinstance(messages, AsyncIterable):
async for message in messages:
await stream.send_message(message)
else:
for message in messages:
await stream.send_message(message)
await stream.end()

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src/betterproto/grpc/grpclib_server.py
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@ -1,33 +0,0 @@
from abc import ABC
from collections.abc import AsyncIterable
from typing import (
Any,
Callable,
Dict,
)
import grpclib
import grpclib.server
class ServiceBase(ABC):
"""
Base class for async gRPC servers.
"""
async def _call_rpc_handler_server_stream(
self,
handler: Callable,
stream: grpclib.server.Stream,
request: Any,
) -> None:
response_iter = handler(request)
# check if response is actually an AsyncIterator
# this might be false if the method just returns without
# yielding at least once
# in that case, we just interpret it as an empty iterator
if isinstance(response_iter, AsyncIterable):
async for response_message in response_iter:
await stream.send_message(response_message)
else:
response_iter.close()

0
src/betterproto/grpc/util/__init__.py
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193
src/betterproto/grpc/util/async_channel.py
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@ -1,193 +0,0 @@
import asyncio
from typing import (
AsyncIterable,
AsyncIterator,
Iterable,
Optional,
TypeVar,
Union,
)
T = TypeVar("T")
class ChannelClosed(Exception):
"""
An exception raised on an attempt to send through a closed channel
"""
class ChannelDone(Exception):
"""
An exception raised on an attempt to send receive from a channel that is both closed
and empty.
"""
class AsyncChannel(AsyncIterable[T]):
"""
A buffered async channel for sending items between coroutines with FIFO ordering.
This makes decoupled bidirectional steaming gRPC requests easy if used like:
.. code-block:: python
client = GeneratedStub(grpclib_chan)
request_channel = await AsyncChannel()
# We can start be sending all the requests we already have
await request_channel.send_from([RequestObject(...), RequestObject(...)])
async for response in client.rpc_call(request_channel):
# The response iterator will remain active until the connection is closed
...
# More items can be sent at any time
await request_channel.send(RequestObject(...))
...
# The channel must be closed to complete the gRPC connection
request_channel.close()
Items can be sent through the channel by either:
- providing an iterable to the send_from method
- passing them to the send method one at a time
Items can be received from the channel by either:
- iterating over the channel with a for loop to get all items
- calling the receive method to get one item at a time
If the channel is empty then receivers will wait until either an item appears or the
channel is closed.
Once the channel is closed then subsequent attempt to send through the channel will
fail with a ChannelClosed exception.
When th channel is closed and empty then it is done, and further attempts to receive
from it will fail with a ChannelDone exception
If multiple coroutines receive from the channel concurrently, each item sent will be
received by only one of the receivers.
:param source:
An optional iterable will items that should be sent through the channel
immediately.
:param buffer_limit:
Limit the number of items that can be buffered in the channel, A value less than
1 implies no limit. If the channel is full then attempts to send more items will
result in the sender waiting until an item is received from the channel.
:param close:
If set to True then the channel will automatically close after exhausting source
or immediately if no source is provided.
"""
def __init__(self, *, buffer_limit: int = 0, close: bool = False):
self._queue: asyncio.Queue[T] = asyncio.Queue(buffer_limit)
self._closed = False
self._waiting_receivers: int = 0
# Track whether flush has been invoked so it can only happen once
self._flushed = False
def __aiter__(self) -> AsyncIterator[T]:
return self
async def __anext__(self) -> T:
if self.done():
raise StopAsyncIteration
self._waiting_receivers += 1
try:
result = await self._queue.get()
if result is self.__flush:
raise StopAsyncIteration
return result
finally:
self._waiting_receivers -= 1
self._queue.task_done()
def closed(self) -> bool:
"""
Returns True if this channel is closed and no-longer accepting new items
"""
return self._closed
def done(self) -> bool:
"""
Check if this channel is done.
:return: True if this channel is closed and and has been drained of items in
which case any further attempts to receive an item from this channel will raise
a ChannelDone exception.
"""
# After close the channel is not yet done until there is at least one waiting
# receiver per enqueued item.
return self._closed and self._queue.qsize() <= self._waiting_receivers
async def send_from(
self, source: Union[Iterable[T], AsyncIterable[T]], close: bool = False
) -> "AsyncChannel[T]":
"""
Iterates the given [Async]Iterable and sends all the resulting items.
If close is set to True then subsequent send calls will be rejected with a
ChannelClosed exception.
:param source: an iterable of items to send
:param close:
if True then the channel will be closed after the source has been exhausted
"""
if self._closed:
raise ChannelClosed("Cannot send through a closed channel")
if isinstance(source, AsyncIterable):
async for item in source:
await self._queue.put(item)
else:
for item in source:
await self._queue.put(item)
if close:
# Complete the closing process
self.close()
return self
async def send(self, item: T) -> "AsyncChannel[T]":
"""
Send a single item over this channel.
:param item: The item to send
"""
if self._closed:
raise ChannelClosed("Cannot send through a closed channel")
await self._queue.put(item)
return self
async def receive(self) -> Optional[T]:
"""
Returns the next item from this channel when it becomes available,
or None if the channel is closed before another item is sent.
:return: An item from the channel
"""
if self.done():
raise ChannelDone("Cannot receive from a closed channel")
self._waiting_receivers += 1
try:
result = await self._queue.get()
if result is self.__flush:
return None
return result
finally:
self._waiting_receivers -= 1
self._queue.task_done()
def close(self):
"""
Close this channel to new items
"""
self._closed = True
asyncio.ensure_future(self._flush_queue())
async def _flush_queue(self):
"""
To be called after the channel is closed. Pushes a number of self.__flush
objects to the queue to ensure no waiting consumers get deadlocked.
"""
if not self._flushed:
self._flushed = True
deadlocked_receivers = max(0, self._waiting_receivers - self._queue.qsize())
for _ in range(deadlocked_receivers):
await self._queue.put(self.__flush)
# A special signal object for flushing the queue when the channel is closed
__flush = object()

0
src/betterproto/lib/__init__.py
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0
src/betterproto/lib/google/__init__.py
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1
src/betterproto/lib/google/protobuf/__init__.py
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from betterproto.lib.std.google.protobuf import *

1
src/betterproto/lib/google/protobuf/compiler/__init__.py
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@ -1 +0,0 @@
from betterproto.lib.std.google.protobuf.compiler import *

0
src/betterproto/lib/pydantic/__init__.py
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0
src/betterproto/lib/pydantic/google/__init__.py
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src/betterproto/lib/pydantic/google/protobuf/__init__.py
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# Generated by the protocol buffer compiler. DO NOT EDIT!
# sources: google/protobuf/compiler/plugin.proto
# plugin: python-betterproto
# This file has been @generated
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from dataclasses import dataclass
else:
from pydantic.dataclasses import dataclass
from typing import List
import betterproto
import betterproto.lib.pydantic.google.protobuf as betterproto_lib_pydantic_google_protobuf
class CodeGeneratorResponseFeature(betterproto.Enum):
"""Sync with code_generator.h."""
FEATURE_NONE = 0
FEATURE_PROTO3_OPTIONAL = 1
FEATURE_SUPPORTS_EDITIONS = 2
@dataclass(eq=False, repr=False)
class Version(betterproto.Message):
"""The version number of protocol compiler."""
major: int = betterproto.int32_field(1)
minor: int = betterproto.int32_field(2)
patch: int = betterproto.int32_field(3)
suffix: str = betterproto.string_field(4)
"""
A suffix for alpha, beta or rc release, e.g., "alpha-1", "rc2". It should
be empty for mainline stable releases.
"""
@dataclass(eq=False, repr=False)
class CodeGeneratorRequest(betterproto.Message):
"""An encoded CodeGeneratorRequest is written to the plugin's stdin."""
file_to_generate: List[str] = betterproto.string_field(1)
"""
The .proto files that were explicitly listed on the command-line. The
code generator should generate code only for these files. Each file's
descriptor will be included in proto_file, below.
"""
parameter: str = betterproto.string_field(2)
"""The generator parameter passed on the command-line."""
proto_file: List["betterproto_lib_pydantic_google_protobuf.FileDescriptorProto"] = (
betterproto.message_field(15)
)
"""
FileDescriptorProtos for all files in files_to_generate and everything
they import. The files will appear in topological order, so each file
appears before any file that imports it.
Note: the files listed in files_to_generate will include runtime-retention
options only, but all other files will include source-retention options.
The source_file_descriptors field below is available in case you need
source-retention options for files_to_generate.
protoc guarantees that all proto_files will be written after
the fields above, even though this is not technically guaranteed by the
protobuf wire format. This theoretically could allow a plugin to stream
in the FileDescriptorProtos and handle them one by one rather than read
the entire set into memory at once. However, as of this writing, this
is not similarly optimized on protoc's end -- it will store all fields in
memory at once before sending them to the plugin.
Type names of fields and extensions in the FileDescriptorProto are always
fully qualified.
"""
source_file_descriptors: List[
"betterproto_lib_pydantic_google_protobuf.FileDescriptorProto"
] = betterproto.message_field(17)
"""
File descriptors with all options, including source-retention options.
These descriptors are only provided for the files listed in
files_to_generate.
"""
compiler_version: "Version" = betterproto.message_field(3)
"""The version number of protocol compiler."""
@dataclass(eq=False, repr=False)
class CodeGeneratorResponse(betterproto.Message):
"""The plugin writes an encoded CodeGeneratorResponse to stdout."""
error: str = betterproto.string_field(1)
"""
Error message. If non-empty, code generation failed. The plugin process
should exit with status code zero even if it reports an error in this way.
This should be used to indicate errors in .proto files which prevent the
code generator from generating correct code. Errors which indicate a
problem in protoc itself -- such as the input CodeGeneratorRequest being
unparseable -- should be reported by writing a message to stderr and
exiting with a non-zero status code.
"""
supported_features: int = betterproto.uint64_field(2)
"""
A bitmask of supported features that the code generator supports.
This is a bitwise "or" of values from the Feature enum.
"""
minimum_edition: int = betterproto.int32_field(3)
"""
The minimum edition this plugin supports. This will be treated as an
Edition enum, but we want to allow unknown values. It should be specified
according the edition enum value, *not* the edition number. Only takes
effect for plugins that have FEATURE_SUPPORTS_EDITIONS set.
"""
maximum_edition: int = betterproto.int32_field(4)
"""
The maximum edition this plugin supports. This will be treated as an
Edition enum, but we want to allow unknown values. It should be specified
according the edition enum value, *not* the edition number. Only takes
effect for plugins that have FEATURE_SUPPORTS_EDITIONS set.
"""
file: List["CodeGeneratorResponseFile"] = betterproto.message_field(15)
@dataclass(eq=False, repr=False)
class CodeGeneratorResponseFile(betterproto.Message):
"""Represents a single generated file."""
name: str = betterproto.string_field(1)
"""
The file name, relative to the output directory. The name must not
contain "." or ".." components and must be relative, not be absolute (so,
the file cannot lie outside the output directory). "/" must be used as
the path separator, not "\".
If the name is omitted, the content will be appended to the previous
file. This allows the generator to break large files into small chunks,
and allows the generated text to be streamed back to protoc so that large
files need not reside completely in memory at one time. Note that as of
this writing protoc does not optimize for this -- it will read the entire
CodeGeneratorResponse before writing files to disk.
"""
insertion_point: str = betterproto.string_field(2)
"""
If non-empty, indicates that the named file should already exist, and the
content here is to be inserted into that file at a defined insertion
point. This feature allows a code generator to extend the output
produced by another code generator. The original generator may provide
insertion points by placing special annotations in the file that look
like:
@@protoc_insertion_point(NAME)
The annotation can have arbitrary text before and after it on the line,
which allows it to be placed in a comment. NAME should be replaced with
an identifier naming the point -- this is what other generators will use
as the insertion_point. Code inserted at this point will be placed
immediately above the line containing the insertion point (thus multiple
insertions to the same point will come out in the order they were added).
The double-@ is intended to make it unlikely that the generated code
could contain things that look like insertion points by accident.
For example, the C++ code generator places the following line in the
.pb.h files that it generates:
// @@protoc_insertion_point(namespace_scope)
This line appears within the scope of the file's package namespace, but
outside of any particular class. Another plugin can then specify the
insertion_point "namespace_scope" to generate additional classes or
other declarations that should be placed in this scope.
Note that if the line containing the insertion point begins with
whitespace, the same whitespace will be added to every line of the
inserted text. This is useful for languages like Python, where
indentation matters. In these languages, the insertion point comment
should be indented the same amount as any inserted code will need to be
in order to work correctly in that context.
The code generator that generates the initial file and the one which
inserts into it must both run as part of a single invocation of protoc.
Code generators are executed in the order in which they appear on the
command line.
If |insertion_point| is present, |name| must also be present.
"""
content: str = betterproto.string_field(15)
"""The file contents."""
generated_code_info: "betterproto_lib_pydantic_google_protobuf.GeneratedCodeInfo" = betterproto.message_field(
16
)
"""
Information describing the file content being inserted. If an insertion
point is used, this information will be appropriately offset and inserted
into the code generation metadata for the generated files.
"""
CodeGeneratorRequest.__pydantic_model__.update_forward_refs() # type: ignore
CodeGeneratorResponse.__pydantic_model__.update_forward_refs() # type: ignore
CodeGeneratorResponseFile.__pydantic_model__.update_forward_refs() # type: ignore

0
src/betterproto/lib/std/__init__.py
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src/betterproto/lib/std/google/__init__.py
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src/betterproto/lib/std/google/protobuf/compiler/__init__.py
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# Generated by the protocol buffer compiler. DO NOT EDIT!
# sources: google/protobuf/compiler/plugin.proto
# plugin: python-betterproto
# This file has been @generated
from dataclasses import dataclass
from typing import List
import betterproto
import betterproto.lib.google.protobuf as betterproto_lib_google_protobuf
class CodeGeneratorResponseFeature(betterproto.Enum):
"""Sync with code_generator.h."""
FEATURE_NONE = 0
FEATURE_PROTO3_OPTIONAL = 1
FEATURE_SUPPORTS_EDITIONS = 2
@dataclass(eq=False, repr=False)
class Version(betterproto.Message):
"""The version number of protocol compiler."""
major: int = betterproto.int32_field(1)
minor: int = betterproto.int32_field(2)
patch: int = betterproto.int32_field(3)
suffix: str = betterproto.string_field(4)
"""
A suffix for alpha, beta or rc release, e.g., "alpha-1", "rc2". It should
be empty for mainline stable releases.
"""
@dataclass(eq=False, repr=False)
class CodeGeneratorRequest(betterproto.Message):
"""An encoded CodeGeneratorRequest is written to the plugin's stdin."""
file_to_generate: List[str] = betterproto.string_field(1)
"""
The .proto files that were explicitly listed on the command-line. The
code generator should generate code only for these files. Each file's
descriptor will be included in proto_file, below.
"""
parameter: str = betterproto.string_field(2)
"""The generator parameter passed on the command-line."""
proto_file: List["betterproto_lib_google_protobuf.FileDescriptorProto"] = (
betterproto.message_field(15)
)
"""
FileDescriptorProtos for all files in files_to_generate and everything
they import. The files will appear in topological order, so each file
appears before any file that imports it.
Note: the files listed in files_to_generate will include runtime-retention
options only, but all other files will include source-retention options.
The source_file_descriptors field below is available in case you need
source-retention options for files_to_generate.
protoc guarantees that all proto_files will be written after
the fields above, even though this is not technically guaranteed by the
protobuf wire format. This theoretically could allow a plugin to stream
in the FileDescriptorProtos and handle them one by one rather than read
the entire set into memory at once. However, as of this writing, this
is not similarly optimized on protoc's end -- it will store all fields in
memory at once before sending them to the plugin.
Type names of fields and extensions in the FileDescriptorProto are always
fully qualified.
"""
source_file_descriptors: List[
"betterproto_lib_google_protobuf.FileDescriptorProto"
] = betterproto.message_field(17)
"""
File descriptors with all options, including source-retention options.
These descriptors are only provided for the files listed in
files_to_generate.
"""
compiler_version: "Version" = betterproto.message_field(3)
"""The version number of protocol compiler."""
@dataclass(eq=False, repr=False)
class CodeGeneratorResponse(betterproto.Message):
"""The plugin writes an encoded CodeGeneratorResponse to stdout."""
error: str = betterproto.string_field(1)
"""
Error message. If non-empty, code generation failed. The plugin process
should exit with status code zero even if it reports an error in this way.
This should be used to indicate errors in .proto files which prevent the
code generator from generating correct code. Errors which indicate a
problem in protoc itself -- such as the input CodeGeneratorRequest being
unparseable -- should be reported by writing a message to stderr and
exiting with a non-zero status code.
"""
supported_features: int = betterproto.uint64_field(2)
"""
A bitmask of supported features that the code generator supports.
This is a bitwise "or" of values from the Feature enum.
"""
minimum_edition: int = betterproto.int32_field(3)
"""
The minimum edition this plugin supports. This will be treated as an
Edition enum, but we want to allow unknown values. It should be specified
according the edition enum value, *not* the edition number. Only takes
effect for plugins that have FEATURE_SUPPORTS_EDITIONS set.
"""
maximum_edition: int = betterproto.int32_field(4)
"""
The maximum edition this plugin supports. This will be treated as an
Edition enum, but we want to allow unknown values. It should be specified
according the edition enum value, *not* the edition number. Only takes
effect for plugins that have FEATURE_SUPPORTS_EDITIONS set.
"""
file: List["CodeGeneratorResponseFile"] = betterproto.message_field(15)
@dataclass(eq=False, repr=False)
class CodeGeneratorResponseFile(betterproto.Message):
"""Represents a single generated file."""
name: str = betterproto.string_field(1)
"""
The file name, relative to the output directory. The name must not
contain "." or ".." components and must be relative, not be absolute (so,
the file cannot lie outside the output directory). "/" must be used as
the path separator, not "\".
If the name is omitted, the content will be appended to the previous
file. This allows the generator to break large files into small chunks,
and allows the generated text to be streamed back to protoc so that large
files need not reside completely in memory at one time. Note that as of
this writing protoc does not optimize for this -- it will read the entire
CodeGeneratorResponse before writing files to disk.
"""
insertion_point: str = betterproto.string_field(2)
"""
If non-empty, indicates that the named file should already exist, and the
content here is to be inserted into that file at a defined insertion
point. This feature allows a code generator to extend the output
produced by another code generator. The original generator may provide
insertion points by placing special annotations in the file that look
like:
@@protoc_insertion_point(NAME)
The annotation can have arbitrary text before and after it on the line,
which allows it to be placed in a comment. NAME should be replaced with
an identifier naming the point -- this is what other generators will use
as the insertion_point. Code inserted at this point will be placed
immediately above the line containing the insertion point (thus multiple
insertions to the same point will come out in the order they were added).
The double-@ is intended to make it unlikely that the generated code
could contain things that look like insertion points by accident.
For example, the C++ code generator places the following line in the
.pb.h files that it generates:
// @@protoc_insertion_point(namespace_scope)
This line appears within the scope of the file's package namespace, but
outside of any particular class. Another plugin can then specify the
insertion_point "namespace_scope" to generate additional classes or
other declarations that should be placed in this scope.
Note that if the line containing the insertion point begins with
whitespace, the same whitespace will be added to every line of the
inserted text. This is useful for languages like Python, where
indentation matters. In these languages, the insertion point comment
should be indented the same amount as any inserted code will need to be
in order to work correctly in that context.
The code generator that generates the initial file and the one which
inserts into it must both run as part of a single invocation of protoc.
Code generators are executed in the order in which they appear on the
command line.
If |insertion_point| is present, |name| must also be present.
"""
content: str = betterproto.string_field(15)
"""The file contents."""
generated_code_info: "betterproto_lib_google_protobuf.GeneratedCodeInfo" = (
betterproto.message_field(16)
)
"""
Information describing the file content being inserted. If an insertion
point is used, this information will be appropriately offset and inserted
into the code generation metadata for the generated files.
"""

1
src/betterproto/plugin/__init__.py
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from .main import main

4
src/betterproto/plugin/__main__.py
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from .main import main
main()

64
src/betterproto/plugin/compiler.py
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@ -1,64 +0,0 @@
import os.path
import subprocess
import sys
from .module_validation import ModuleValidator
try:
# betterproto[compiler] specific dependencies
import jinja2
except ImportError as err:
print(
"\033[31m"
f"Unable to import `{err.name}` from betterproto plugin! "
"Please ensure that you've installed betterproto as "
'`pip install "betterproto[compiler]"` so that compiler dependencies '
"are included."
"\033[0m"
)
raise SystemExit(1)
from .models import OutputTemplate
def outputfile_compiler(output_file: OutputTemplate) -> str:
templates_folder = os.path.abspath(
os.path.join(os.path.dirname(__file__), "..", "templates")
)
env = jinja2.Environment(
trim_blocks=True,
lstrip_blocks=True,
loader=jinja2.FileSystemLoader(templates_folder),
undefined=jinja2.StrictUndefined,
)
# Load the body first so we have a compleate list of imports needed.
body_template = env.get_template("template.py.j2")
header_template = env.get_template("header.py.j2")
code = body_template.render(output_file=output_file)
code = header_template.render(output_file=output_file) + code
# Sort imports, delete unused ones
code = subprocess.check_output(
["ruff", "check", "--select", "I,F401", "--fix", "--silent", "-"],
input=code,
encoding="utf-8",
)
# Format the code
code = subprocess.check_output(
["ruff", "format", "-"], input=code, encoding="utf-8"
)
# Validate the generated code.
validator = ModuleValidator(iter(code.splitlines()))
if not validator.validate():
message_builder = ["[WARNING]: Generated code has collisions in the module:"]
for collision, lines in validator.collisions.items():
message_builder.append(f' "{collision}" on lines:')
for num, line in lines:
message_builder.append(f" {num}:{line}")
print("\n".join(message_builder), file=sys.stderr)
return code

52
src/betterproto/plugin/main.py
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@ -1,52 +0,0 @@
#!/usr/bin/env python
import os
import sys
from betterproto.lib.google.protobuf.compiler import (
CodeGeneratorRequest,
CodeGeneratorResponse,
)
from betterproto.plugin.models import monkey_patch_oneof_index
from betterproto.plugin.parser import generate_code
def main() -> None:
"""The plugin's main entry point."""
# Read request message from stdin
data = sys.stdin.buffer.read()
# Apply Work around for proto2/3 difference in protoc messages
monkey_patch_oneof_index()
# Parse request
request = CodeGeneratorRequest()
request.parse(data)
dump_file = os.getenv("BETTERPROTO_DUMP")
if dump_file:
dump_request(dump_file, request)
# Generate code
response = generate_code(request)
# Serialise response message
output = response.SerializeToString()
# Write to stdout
sys.stdout.buffer.write(output)
def dump_request(dump_file: str, request: CodeGeneratorRequest) -> None:
"""
For developers: Supports running plugin.py standalone so its possible to debug it.
Run protoc (or generate.py) with BETTERPROTO_DUMP="yourfile.bin" to write the request to a file.
Then run plugin.py from your IDE in debugging mode, and redirect stdin to the file.
"""
with open(str(dump_file), "wb") as fh:
sys.stderr.write(f"\033[31mWriting input from protoc to: {dump_file}\033[0m\n")
fh.write(request.SerializeToString())
if __name__ == "__main__":
main()

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src/betterproto/plugin/models.py
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@ -1,787 +0,0 @@
"""Plugin model dataclasses.
These classes are meant to be an intermediate representation
of protobuf objects. They are used to organize the data collected during parsing.
The general intention is to create a doubly-linked tree-like structure
with the following types of references:
- Downwards references: from message -> fields, from output package -> messages
or from service -> service methods
- Upwards references: from field -> message, message -> package.
- Input/output message references: from a service method to it's corresponding
input/output messages, which may even be in another package.
There are convenience methods to allow climbing up and down this tree, for
example to retrieve the list of all messages that are in the same package as
the current message.
Most of these classes take as inputs:
- proto_obj: A reference to it's corresponding protobuf object as
presented by the protoc plugin.
- parent: a reference to the parent object in the tree.
With this information, the class is able to expose attributes,
such as a pythonized name, that will be calculated from proto_obj.
The instantiation should also attach a reference to the new object
into the corresponding place within it's parent object. For example,
instantiating field `A` with parent message `B` should add a
reference to `A` to `B`'s `fields` attribute.
"""
import builtins
import re
from dataclasses import (
dataclass,
field,
)
from typing import (
Dict,
Iterable,
Iterator,
List,
Optional,
Set,
Type,
Union,
)
import betterproto
from betterproto.compile.naming import (
pythonize_class_name,
pythonize_field_name,
pythonize_method_name,
)
from betterproto.lib.google.protobuf import (
DescriptorProto,
EnumDescriptorProto,
Field,
FieldDescriptorProto,
FieldDescriptorProtoLabel,
FieldDescriptorProtoType,
FileDescriptorProto,
MethodDescriptorProto,
)
from betterproto.lib.google.protobuf.compiler import CodeGeneratorRequest
from .. import which_one_of
from ..compile.importing import (
get_type_reference,
parse_source_type_name,
)
from ..compile.naming import (
pythonize_class_name,
pythonize_enum_member_name,
pythonize_field_name,
pythonize_method_name,
)
from .typing_compiler import (
DirectImportTypingCompiler,
TypingCompiler,
)
# Create a unique placeholder to deal with
# https://stackoverflow.com/questions/51575931/class-inheritance-in-python-3-7-dataclasses
PLACEHOLDER = object()
# Organize proto types into categories
PROTO_FLOAT_TYPES = (
FieldDescriptorProtoType.TYPE_DOUBLE, # 1
FieldDescriptorProtoType.TYPE_FLOAT, # 2
)
PROTO_INT_TYPES = (
FieldDescriptorProtoType.TYPE_INT64, # 3
FieldDescriptorProtoType.TYPE_UINT64, # 4
FieldDescriptorProtoType.TYPE_INT32, # 5
FieldDescriptorProtoType.TYPE_FIXED64, # 6
FieldDescriptorProtoType.TYPE_FIXED32, # 7
FieldDescriptorProtoType.TYPE_UINT32, # 13
FieldDescriptorProtoType.TYPE_SFIXED32, # 15
FieldDescriptorProtoType.TYPE_SFIXED64, # 16
FieldDescriptorProtoType.TYPE_SINT32, # 17
FieldDescriptorProtoType.TYPE_SINT64, # 18
)
PROTO_BOOL_TYPES = (FieldDescriptorProtoType.TYPE_BOOL,) # 8
PROTO_STR_TYPES = (FieldDescriptorProtoType.TYPE_STRING,) # 9
PROTO_BYTES_TYPES = (FieldDescriptorProtoType.TYPE_BYTES,) # 12
PROTO_MESSAGE_TYPES = (
FieldDescriptorProtoType.TYPE_MESSAGE, # 11
FieldDescriptorProtoType.TYPE_ENUM, # 14
)
PROTO_MAP_TYPES = (FieldDescriptorProtoType.TYPE_MESSAGE,) # 11
PROTO_PACKED_TYPES = (
FieldDescriptorProtoType.TYPE_DOUBLE, # 1
FieldDescriptorProtoType.TYPE_FLOAT, # 2
FieldDescriptorProtoType.TYPE_INT64, # 3
FieldDescriptorProtoType.TYPE_UINT64, # 4
FieldDescriptorProtoType.TYPE_INT32, # 5
FieldDescriptorProtoType.TYPE_FIXED64, # 6
FieldDescriptorProtoType.TYPE_FIXED32, # 7
FieldDescriptorProtoType.TYPE_BOOL, # 8
FieldDescriptorProtoType.TYPE_UINT32, # 13
FieldDescriptorProtoType.TYPE_SFIXED32, # 15
FieldDescriptorProtoType.TYPE_SFIXED64, # 16
FieldDescriptorProtoType.TYPE_SINT32, # 17
FieldDescriptorProtoType.TYPE_SINT64, # 18
)
def monkey_patch_oneof_index():
"""
The compiler message types are written for proto2, but we read them as proto3.
For this to work in the case of the oneof_index fields, which depend on being able
to tell whether they were set, we have to treat them as oneof fields. This method
monkey patches the generated classes after the fact to force this behaviour.
"""
object.__setattr__(
FieldDescriptorProto.__dataclass_fields__["oneof_index"].metadata[
"betterproto"
],
"group",
"oneof_index",
)
object.__setattr__(
Field.__dataclass_fields__["oneof_index"].metadata["betterproto"],
"group",
"oneof_index",
)
def get_comment(
proto_file: "FileDescriptorProto", path: List[int], indent: int = 4
) -> str:
pad = " " * indent
for sci_loc in proto_file.source_code_info.location:
if list(sci_loc.path) == path:
all_comments = list(sci_loc.leading_detached_comments)
if sci_loc.leading_comments:
all_comments.append(sci_loc.leading_comments)
if sci_loc.trailing_comments:
all_comments.append(sci_loc.trailing_comments)
lines = []
for comment in all_comments:
lines += comment.split("\n")
lines.append("")
# Remove consecutive empty lines
lines = [
line for i, line in enumerate(lines) if line or (i == 0 or lines[i - 1])
]
if lines and not lines[-1]:
lines.pop() # Remove the last empty line
# It is common for one line comments to start with a space, for example: // comment
# We don't add this space to the generated file.
lines = [line[1:] if line and line[0] == " " else line for line in lines]
# This is a field, message, enum, service, or method
if len(lines) == 1 and len(lines[0]) < 79 - indent - 6:
return f'{pad}"""{lines[0]}"""'
else:
joined = f"\n{pad}".join(lines)
return f'{pad}"""\n{pad}{joined}\n{pad}"""'
return ""
class ProtoContentBase:
"""Methods common to MessageCompiler, ServiceCompiler and ServiceMethodCompiler."""
source_file: FileDescriptorProto
typing_compiler: TypingCompiler
path: List[int]
comment_indent: int = 4
parent: Union["betterproto.Message", "OutputTemplate"]
__dataclass_fields__: Dict[str, object]
def __post_init__(self) -> None:
"""Checks that no fake default fields were left as placeholders."""
for field_name, field_val in self.__dataclass_fields__.items():
if field_val is PLACEHOLDER:
raise ValueError(f"`{field_name}` is a required field.")
@property
def output_file(self) -> "OutputTemplate":
current = self
while not isinstance(current, OutputTemplate):
current = current.parent
return current
@property
def request(self) -> "PluginRequestCompiler":
current = self
while not isinstance(current, OutputTemplate):
current = current.parent
return current.parent_request
@property
def comment(self) -> str:
"""Crawl the proto source code and retrieve comments
for this object.
"""
return get_comment(
proto_file=self.source_file, path=self.path, indent=self.comment_indent
)
@dataclass
class PluginRequestCompiler:
plugin_request_obj: CodeGeneratorRequest
output_packages: Dict[str, "OutputTemplate"] = field(default_factory=dict)
@property
def all_messages(self) -> List["MessageCompiler"]:
"""All of the messages in this request.
Returns
-------
List[MessageCompiler]
List of all of the messages in this request.
"""
return [
msg for output in self.output_packages.values() for msg in output.messages
]
@dataclass
class OutputTemplate:
"""Representation of an output .py file.
Each output file corresponds to a .proto input file,
but may need references to other .proto files to be
built.
"""
parent_request: PluginRequestCompiler
package_proto_obj: FileDescriptorProto
input_files: List[str] = field(default_factory=list)
imports_end: Set[str] = field(default_factory=set)
datetime_imports: Set[str] = field(default_factory=set)
pydantic_imports: Set[str] = field(default_factory=set)
builtins_import: bool = False
messages: List["MessageCompiler"] = field(default_factory=list)
enums: List["EnumDefinitionCompiler"] = field(default_factory=list)
services: List["ServiceCompiler"] = field(default_factory=list)
imports_type_checking_only: Set[str] = field(default_factory=set)
pydantic_dataclasses: bool = False
output: bool = True
typing_compiler: TypingCompiler = field(default_factory=DirectImportTypingCompiler)
@property
def package(self) -> str:
"""Name of input package.
Returns
-------
str
Name of input package.
"""
return self.package_proto_obj.package
@property
def input_filenames(self) -> Iterable[str]:
"""Names of the input files used to build this output.
Returns
-------
Iterable[str]
Names of the input files used to build this output.
"""
return sorted(f.name for f in self.input_files)
@property
def python_module_imports(self) -> Set[str]:
imports = set()
has_deprecated = False
if any(m.deprecated for m in self.messages):
has_deprecated = True
if any(x for x in self.messages if any(x.deprecated_fields)):
has_deprecated = True
if any(
any(m.proto_obj.options.deprecated for m in s.methods)
for s in self.services
):
has_deprecated = True
if has_deprecated:
imports.add("warnings")
if self.builtins_import:
imports.add("builtins")
return imports
@dataclass
class MessageCompiler(ProtoContentBase):
"""Representation of a protobuf message."""
source_file: FileDescriptorProto
typing_compiler: TypingCompiler
parent: Union["MessageCompiler", OutputTemplate] = PLACEHOLDER
proto_obj: DescriptorProto = PLACEHOLDER
path: List[int] = PLACEHOLDER
fields: List[Union["FieldCompiler", "MessageCompiler"]] = field(
default_factory=list
)
deprecated: bool = field(default=False, init=False)
builtins_types: Set[str] = field(default_factory=set)
def __post_init__(self) -> None:
# Add message to output file
if isinstance(self.parent, OutputTemplate):
if isinstance(self, EnumDefinitionCompiler):
self.output_file.enums.append(self)
else:
self.output_file.messages.append(self)
self.deprecated = self.proto_obj.options.deprecated
super().__post_init__()
@property
def proto_name(self) -> str:
return self.proto_obj.name
@property
def py_name(self) -> str:
return pythonize_class_name(self.proto_name)
@property
def deprecated_fields(self) -> Iterator[str]:
for f in self.fields:
if f.deprecated:
yield f.py_name
@property
def has_deprecated_fields(self) -> bool:
return any(self.deprecated_fields)
@property
def has_oneof_fields(self) -> bool:
return any(isinstance(field, OneOfFieldCompiler) for field in self.fields)
@property
def has_message_field(self) -> bool:
return any(
(
field.proto_obj.type in PROTO_MESSAGE_TYPES
for field in self.fields
if isinstance(field.proto_obj, FieldDescriptorProto)
)
)
def is_map(
proto_field_obj: FieldDescriptorProto, parent_message: DescriptorProto
) -> bool:
"""True if proto_field_obj is a map, otherwise False."""
if proto_field_obj.type == FieldDescriptorProtoType.TYPE_MESSAGE:
if not hasattr(parent_message, "nested_type"):
return False
# This might be a map...
message_type = proto_field_obj.type_name.split(".").pop().lower()
map_entry = f"{proto_field_obj.name.replace('_', '').lower()}entry"
if message_type == map_entry:
for nested in parent_message.nested_type: # parent message
if (
nested.name.replace("_", "").lower() == map_entry
and nested.options.map_entry
):
return True
return False
def is_oneof(proto_field_obj: FieldDescriptorProto) -> bool:
"""
True if proto_field_obj is a OneOf, otherwise False.
.. warning::
Becuase the message from protoc is defined in proto2, and betterproto works with
proto3, and interpreting the FieldDescriptorProto.oneof_index field requires
distinguishing between default and unset values (which proto3 doesn't support),
we have to hack the generated FieldDescriptorProto class for this to work.
The hack consists of setting group="oneof_index" in the field metadata,
essentially making oneof_index the sole member of a one_of group, which allows
us to tell whether it was set, via the which_one_of interface.
"""
return (
not proto_field_obj.proto3_optional
and which_one_of(proto_field_obj, "oneof_index")[0] == "oneof_index"
)
@dataclass
class FieldCompiler(MessageCompiler):
parent: MessageCompiler = PLACEHOLDER
proto_obj: FieldDescriptorProto = PLACEHOLDER
def __post_init__(self) -> None:
# Add field to message
self.parent.fields.append(self)
# Check for new imports
self.add_imports_to(self.output_file)
super().__post_init__() # call FieldCompiler-> MessageCompiler __post_init__
def get_field_string(self, indent: int = 4) -> str:
"""Construct string representation of this field as a field."""
name = f"{self.py_name}"
annotations = f": {self.annotation}"
field_args = ", ".join(
([""] + self.betterproto_field_args) if self.betterproto_field_args else []
)
betterproto_field_type = (
f"betterproto.{self.field_type}_field({self.proto_obj.number}{field_args})"
)
if self.py_name in dir(builtins):
self.parent.builtins_types.add(self.py_name)
return f"{name}{annotations} = {betterproto_field_type}"
@property
def betterproto_field_args(self) -> List[str]:
args = []
if self.field_wraps:
args.append(f"wraps={self.field_wraps}")
if self.optional:
args.append(f"optional=True")
return args
@property
def datetime_imports(self) -> Set[str]:
imports = set()
annotation = self.annotation
# FIXME: false positives - e.g. `MyDatetimedelta`
if "timedelta" in annotation:
imports.add("timedelta")
if "datetime" in annotation:
imports.add("datetime")
return imports
@property
def pydantic_imports(self) -> Set[str]:
return set()
@property
def use_builtins(self) -> bool:
return self.py_type in self.parent.builtins_types or (
self.py_type == self.py_name and self.py_name in dir(builtins)
)
def add_imports_to(self, output_file: OutputTemplate) -> None:
output_file.datetime_imports.update(self.datetime_imports)
output_file.pydantic_imports.update(self.pydantic_imports)
output_file.builtins_import = output_file.builtins_import or self.use_builtins
@property
def field_wraps(self) -> Optional[str]:
"""Returns betterproto wrapped field type or None."""
match_wrapper = re.match(
r"\.google\.protobuf\.(.+)Value$", self.proto_obj.type_name
)
if match_wrapper:
wrapped_type = "TYPE_" + match_wrapper.group(1).upper()
if hasattr(betterproto, wrapped_type):
return f"betterproto.{wrapped_type}"
return None
@property
def repeated(self) -> bool:
return (
self.proto_obj.label == FieldDescriptorProtoLabel.LABEL_REPEATED
and not is_map(self.proto_obj, self.parent)
)
@property
def optional(self) -> bool:
return self.proto_obj.proto3_optional
@property
def field_type(self) -> str:
"""String representation of proto field type."""
return (
FieldDescriptorProtoType(self.proto_obj.type)
.name.lower()
.replace("type_", "")
)
@property
def packed(self) -> bool:
"""True if the wire representation is a packed format."""
return self.repeated and self.proto_obj.type in PROTO_PACKED_TYPES
@property
def py_name(self) -> str:
"""Pythonized name."""
return pythonize_field_name(self.proto_name)
@property
def proto_name(self) -> str:
"""Original protobuf name."""
return self.proto_obj.name
@property
def py_type(self) -> str:
"""String representation of Python type."""
if self.proto_obj.type in PROTO_FLOAT_TYPES:
return "float"
elif self.proto_obj.type in PROTO_INT_TYPES:
return "int"
elif self.proto_obj.type in PROTO_BOOL_TYPES:
return "bool"
elif self.proto_obj.type in PROTO_STR_TYPES:
return "str"
elif self.proto_obj.type in PROTO_BYTES_TYPES:
return "bytes"
elif self.proto_obj.type in PROTO_MESSAGE_TYPES:
# Type referencing another defined Message or a named enum
return get_type_reference(
package=self.output_file.package,
imports=self.output_file.imports_end,
source_type=self.proto_obj.type_name,
typing_compiler=self.typing_compiler,
pydantic=self.output_file.pydantic_dataclasses,
)
else:
raise NotImplementedError(f"Unknown type {self.proto_obj.type}")
@property
def annotation(self) -> str:
py_type = self.py_type
if self.use_builtins:
py_type = f"builtins.{py_type}"
if self.repeated:
return self.typing_compiler.list(py_type)
if self.optional:
return self.typing_compiler.optional(py_type)
return py_type
@dataclass
class OneOfFieldCompiler(FieldCompiler):
@property
def betterproto_field_args(self) -> List[str]:
args = super().betterproto_field_args
group = self.parent.proto_obj.oneof_decl[self.proto_obj.oneof_index].name
args.append(f'group="{group}"')
return args
@dataclass
class PydanticOneOfFieldCompiler(OneOfFieldCompiler):
@property
def optional(self) -> bool:
# Force the optional to be True. This will allow the pydantic dataclass
# to validate the object correctly by allowing the field to be let empty.
# We add a pydantic validator later to ensure exactly one field is defined.
return True
@property
def pydantic_imports(self) -> Set[str]:
return {"model_validator"}
@dataclass
class MapEntryCompiler(FieldCompiler):
py_k_type: Type = PLACEHOLDER
py_v_type: Type = PLACEHOLDER
proto_k_type: str = PLACEHOLDER
proto_v_type: str = PLACEHOLDER
def __post_init__(self) -> None:
"""Explore nested types and set k_type and v_type if unset."""
map_entry = f"{self.proto_obj.name.replace('_', '').lower()}entry"
for nested in self.parent.proto_obj.nested_type:
if (
nested.name.replace("_", "").lower() == map_entry
and nested.options.map_entry
):
# Get Python types
self.py_k_type = FieldCompiler(
source_file=self.source_file,
parent=self,
proto_obj=nested.field[0], # key
typing_compiler=self.typing_compiler,
).py_type
self.py_v_type = FieldCompiler(
source_file=self.source_file,
parent=self,
proto_obj=nested.field[1], # value
typing_compiler=self.typing_compiler,
).py_type
# Get proto types
self.proto_k_type = FieldDescriptorProtoType(nested.field[0].type).name
self.proto_v_type = FieldDescriptorProtoType(nested.field[1].type).name
super().__post_init__() # call FieldCompiler-> MessageCompiler __post_init__
@property
def betterproto_field_args(self) -> List[str]:
return [f"betterproto.{self.proto_k_type}", f"betterproto.{self.proto_v_type}"]
@property
def field_type(self) -> str:
return "map"
@property
def annotation(self) -> str:
return self.typing_compiler.dict(self.py_k_type, self.py_v_type)
@property
def repeated(self) -> bool:
return False # maps cannot be repeated
@dataclass
class EnumDefinitionCompiler(MessageCompiler):
"""Representation of a proto Enum definition."""
proto_obj: EnumDescriptorProto = PLACEHOLDER
entries: List["EnumDefinitionCompiler.EnumEntry"] = PLACEHOLDER
@dataclass(unsafe_hash=True)
class EnumEntry:
"""Representation of an Enum entry."""
name: str
value: int
comment: str
def __post_init__(self) -> None:
# Get entries/allowed values for this Enum
self.entries = [
self.EnumEntry(
name=pythonize_enum_member_name(
entry_proto_value.name, self.proto_obj.name
),
value=entry_proto_value.number,
comment=get_comment(
proto_file=self.source_file, path=self.path + [2, entry_number]
),
)
for entry_number, entry_proto_value in enumerate(self.proto_obj.value)
]
super().__post_init__() # call MessageCompiler __post_init__
@dataclass
class ServiceCompiler(ProtoContentBase):
source_file: FileDescriptorProto
parent: OutputTemplate = PLACEHOLDER
proto_obj: DescriptorProto = PLACEHOLDER
path: List[int] = PLACEHOLDER
methods: List["ServiceMethodCompiler"] = field(default_factory=list)
def __post_init__(self) -> None:
# Add service to output file
self.output_file.services.append(self)
super().__post_init__() # check for unset fields
@property
def proto_name(self) -> str:
return self.proto_obj.name
@property
def py_name(self) -> str:
return pythonize_class_name(self.proto_name)
@dataclass
class ServiceMethodCompiler(ProtoContentBase):
source_file: FileDescriptorProto
parent: ServiceCompiler
proto_obj: MethodDescriptorProto
path: List[int] = PLACEHOLDER
comment_indent: int = 8
def __post_init__(self) -> None:
# Add method to service
self.parent.methods.append(self)
self.output_file.imports_type_checking_only.add("import grpclib.server")
self.output_file.imports_type_checking_only.add(
"from betterproto.grpc.grpclib_client import MetadataLike"
)
self.output_file.imports_type_checking_only.add(
"from grpclib.metadata import Deadline"
)
super().__post_init__() # check for unset fields
@property
def py_name(self) -> str:
"""Pythonized method name."""
return pythonize_method_name(self.proto_obj.name)
@property
def proto_name(self) -> str:
"""Original protobuf name."""
return self.proto_obj.name
@property
def route(self) -> str:
package_part = (
f"{self.output_file.package}." if self.output_file.package else ""
)
return f"/{package_part}{self.parent.proto_name}/{self.proto_name}"
@property
def py_input_message_type(self) -> str:
"""String representation of the Python type corresponding to the
input message.
Returns
-------
str
String representation of the Python type corresponding to the input message.
"""
return get_type_reference(
package=self.output_file.package,
imports=self.output_file.imports_end,
source_type=self.proto_obj.input_type,
typing_compiler=self.output_file.typing_compiler,
unwrap=False,
pydantic=self.output_file.pydantic_dataclasses,
).strip('"')
@property
def py_input_message_param(self) -> str:
"""Param name corresponding to py_input_message_type.
Returns
-------
str
Param name corresponding to py_input_message_type.
"""
return pythonize_field_name(self.py_input_message_type)
@property
def py_output_message_type(self) -> str:
"""String representation of the Python type corresponding to the
output message.
Returns
-------
str
String representation of the Python type corresponding to the output message.
"""
return get_type_reference(
package=self.output_file.package,
imports=self.output_file.imports_end,
source_type=self.proto_obj.output_type,
typing_compiler=self.output_file.typing_compiler,
unwrap=False,
pydantic=self.output_file.pydantic_dataclasses,
).strip('"')
@property
def client_streaming(self) -> bool:
return self.proto_obj.client_streaming
@property
def server_streaming(self) -> bool:
return self.proto_obj.server_streaming

163
src/betterproto/plugin/module_validation.py
View File

@ -1,163 +0,0 @@
import re
from collections import defaultdict
from dataclasses import (
dataclass,
field,
)
from typing import (
Dict,
Iterator,
List,
Tuple,
)
@dataclass
class ModuleValidator:
line_iterator: Iterator[str]
line_number: int = field(init=False, default=0)
collisions: Dict[str, List[Tuple[int, str]]] = field(
init=False, default_factory=lambda: defaultdict(list)
)
def add_import(self, imp: str, number: int, full_line: str):
"""
Adds an import to be tracked.
"""
self.collisions[imp].append((number, full_line))
def process_import(self, imp: str):
"""
Filters out the import to its actual value.
"""
if " as " in imp:
imp = imp[imp.index(" as ") + 4 :]
imp = imp.strip()
assert " " not in imp, imp
return imp
def evaluate_multiline_import(self, line: str):
"""
Evaluates a multiline import from a starting line
"""
# Filter the first line and remove anything before the import statement.
full_line = line
line = line.split("import", 1)[1]
if "(" in line:
conditional = lambda line: ")" not in line
else:
conditional = lambda line: "\\" in line
# Remove open parenthesis if it exists.
if "(" in line:
line = line[line.index("(") + 1 :]
# Choose the conditional based on how multiline imports are formatted.
while conditional(line):
# Split the line by commas
imports = line.split(",")
for imp in imports:
# Add the import to the namespace
imp = self.process_import(imp)
if imp:
self.add_import(imp, self.line_number, full_line)
# Get the next line
full_line = line = next(self.line_iterator)
# Increment the line number
self.line_number += 1
# validate the last line
if ")" in line:
line = line[: line.index(")")]
imports = line.split(",")
for imp in imports:
imp = self.process_import(imp)
if imp:
self.add_import(imp, self.line_number, full_line)
def evaluate_import(self, line: str):
"""
Extracts an import from a line.
"""
whole_line = line
line = line[line.index("import") + 6 :]
values = line.split(",")
for v in values:
self.add_import(self.process_import(v), self.line_number, whole_line)
def next(self):
"""
Evaluate each line for names in the module.
"""
line = next(self.line_iterator)
# Skip lines with indentation or comments
if (
# Skip indents and whitespace.
line.startswith(" ")
or line == "\n"
or line.startswith("\t")
or
# Skip comments
line.startswith("#")
or
# Skip decorators
line.startswith("@")
):
self.line_number += 1
return
# Skip docstrings.
if line.startswith('"""') or line.startswith("'''"):
quote = line[0] * 3
line = line[3:]
while quote not in line:
line = next(self.line_iterator)
self.line_number += 1
return
# Evaluate Imports.
if line.startswith("from ") or line.startswith("import "):
if "(" in line or "\\" in line:
self.evaluate_multiline_import(line)
else:
self.evaluate_import(line)
# Evaluate Classes.
elif line.startswith("class "):
class_name = re.search(r"class (\w+)", line).group(1)
if class_name:
self.add_import(class_name, self.line_number, line)
# Evaluate Functions.
elif line.startswith("def "):
function_name = re.search(r"def (\w+)", line).group(1)
if function_name:
self.add_import(function_name, self.line_number, line)
# Evaluate direct assignments.
elif "=" in line:
assignment = re.search(r"(\w+)\s*=", line).group(1)
if assignment:
self.add_import(assignment, self.line_number, line)
self.line_number += 1
def validate(self) -> bool:
"""
Run Validation.
"""
try:
while True:
self.next()
except StopIteration:
pass
# Filter collisions for those with more than one value.
self.collisions = {k: v for k, v in self.collisions.items() if len(v) > 1}
# Return True if no collisions are found.
return not bool(self.collisions)

269
src/betterproto/plugin/parser.py
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@ -1,269 +0,0 @@
import pathlib
import sys
from typing import (
Generator,
List,
Set,
Tuple,
Union,
)
from betterproto.lib.google.protobuf import (
DescriptorProto,
EnumDescriptorProto,
FieldDescriptorProto,
FileDescriptorProto,
ServiceDescriptorProto,
)
from betterproto.lib.google.protobuf.compiler import (
CodeGeneratorRequest,
CodeGeneratorResponse,
CodeGeneratorResponseFeature,
CodeGeneratorResponseFile,
)
from .compiler import outputfile_compiler
from .models import (
EnumDefinitionCompiler,
FieldCompiler,
MapEntryCompiler,
MessageCompiler,
OneOfFieldCompiler,
OutputTemplate,
PluginRequestCompiler,
PydanticOneOfFieldCompiler,
ServiceCompiler,
ServiceMethodCompiler,
is_map,
is_oneof,
)
from .typing_compiler import (
DirectImportTypingCompiler,
NoTyping310TypingCompiler,
TypingCompiler,
TypingImportTypingCompiler,
)
def traverse(
proto_file: FileDescriptorProto,
) -> Generator[
Tuple[Union[EnumDescriptorProto, DescriptorProto], List[int]], None, None
]:
# Todo: Keep information about nested hierarchy
def _traverse(
path: List[int],
items: Union[List[EnumDescriptorProto], List[DescriptorProto]],
prefix: str = "",
) -> Generator[
Tuple[Union[EnumDescriptorProto, DescriptorProto], List[int]], None, None
]:
for i, item in enumerate(items):
# Adjust the name since we flatten the hierarchy.
# Todo: don't change the name, but include full name in returned tuple
item.name = next_prefix = f"{prefix}_{item.name}"
yield item, [*path, i]
if isinstance(item, DescriptorProto):
# Get nested types.
yield from _traverse([*path, i, 4], item.enum_type, next_prefix)
yield from _traverse([*path, i, 3], item.nested_type, next_prefix)
yield from _traverse([5], proto_file.enum_type)
yield from _traverse([4], proto_file.message_type)
def generate_code(request: CodeGeneratorRequest) -> CodeGeneratorResponse:
response = CodeGeneratorResponse()
plugin_options = request.parameter.split(",") if request.parameter else []
response.supported_features = CodeGeneratorResponseFeature.FEATURE_PROTO3_OPTIONAL
request_data = PluginRequestCompiler(plugin_request_obj=request)
# Gather output packages
for proto_file in request.proto_file:
output_package_name = proto_file.package
if output_package_name not in request_data.output_packages:
# Create a new output if there is no output for this package
request_data.output_packages[output_package_name] = OutputTemplate(
parent_request=request_data, package_proto_obj=proto_file
)
# Add this input file to the output corresponding to this package
request_data.output_packages[output_package_name].input_files.append(proto_file)
if (
proto_file.package == "google.protobuf"
and "INCLUDE_GOOGLE" not in plugin_options
):
# If not INCLUDE_GOOGLE,
# skip outputting Google's well-known types
request_data.output_packages[output_package_name].output = False
if "pydantic_dataclasses" in plugin_options:
request_data.output_packages[
output_package_name
].pydantic_dataclasses = True
# Gather any typing generation options.
typing_opts = [
opt[len("typing.") :] for opt in plugin_options if opt.startswith("typing.")
]
if len(typing_opts) > 1:
raise ValueError("Multiple typing options provided")
# Set the compiler type.
typing_opt = typing_opts[0] if typing_opts else "direct"
if typing_opt == "direct":
request_data.output_packages[
output_package_name
].typing_compiler = DirectImportTypingCompiler()
elif typing_opt == "root":
request_data.output_packages[
output_package_name
].typing_compiler = TypingImportTypingCompiler()
elif typing_opt == "310":
request_data.output_packages[
output_package_name
].typing_compiler = NoTyping310TypingCompiler()
# Read Messages and Enums
# We need to read Messages before Services in so that we can
# get the references to input/output messages for each service
for output_package_name, output_package in request_data.output_packages.items():
for proto_input_file in output_package.input_files:
for item, path in traverse(proto_input_file):
read_protobuf_type(
source_file=proto_input_file,
item=item,
path=path,
output_package=output_package,
)
# Read Services
for output_package_name, output_package in request_data.output_packages.items():
for proto_input_file in output_package.input_files:
for index, service in enumerate(proto_input_file.service):
read_protobuf_service(proto_input_file, service, index, output_package)
# Generate output files
output_paths: Set[pathlib.Path] = set()
for output_package_name, output_package in request_data.output_packages.items():
if not output_package.output:
continue
# Add files to the response object
output_path = pathlib.Path(*output_package_name.split("."), "__init__.py")
output_paths.add(output_path)
response.file.append(
CodeGeneratorResponseFile(
name=str(output_path),
# Render and then format the output file
content=outputfile_compiler(output_file=output_package),
)
)
# Make each output directory a package with __init__ file
init_files = {
directory.joinpath("__init__.py")
for path in output_paths
for directory in path.parents
if not directory.joinpath("__init__.py").exists()
} - output_paths
for init_file in init_files:
response.file.append(CodeGeneratorResponseFile(name=str(init_file)))
for output_package_name in sorted(output_paths.union(init_files)):
print(f"Writing {output_package_name}", file=sys.stderr)
return response
def _make_one_of_field_compiler(
output_package: OutputTemplate,
source_file: "FileDescriptorProto",
parent: MessageCompiler,
proto_obj: "FieldDescriptorProto",
path: List[int],
) -> FieldCompiler:
pydantic = output_package.pydantic_dataclasses
Cls = PydanticOneOfFieldCompiler if pydantic else OneOfFieldCompiler
return Cls(
source_file=source_file,
parent=parent,
proto_obj=proto_obj,
path=path,
typing_compiler=output_package.typing_compiler,
)
def read_protobuf_type(
item: DescriptorProto,
path: List[int],
source_file: "FileDescriptorProto",
output_package: OutputTemplate,
) -> None:
if isinstance(item, DescriptorProto):
if item.options.map_entry:
# Skip generated map entry messages since we just use dicts
return
# Process Message
message_data = MessageCompiler(
source_file=source_file,
parent=output_package,
proto_obj=item,
path=path,
typing_compiler=output_package.typing_compiler,
)
for index, field in enumerate(item.field):
if is_map(field, item):
MapEntryCompiler(
source_file=source_file,
parent=message_data,
proto_obj=field,
path=path + [2, index],
typing_compiler=output_package.typing_compiler,
)
elif is_oneof(field):
_make_one_of_field_compiler(
output_package, source_file, message_data, field, path + [2, index]
)
else:
FieldCompiler(
source_file=source_file,
parent=message_data,
proto_obj=field,
path=path + [2, index],
typing_compiler=output_package.typing_compiler,
)
elif isinstance(item, EnumDescriptorProto):
# Enum
EnumDefinitionCompiler(
source_file=source_file,
parent=output_package,
proto_obj=item,
path=path,
typing_compiler=output_package.typing_compiler,
)
def read_protobuf_service(
source_file: FileDescriptorProto,
service: ServiceDescriptorProto,
index: int,
output_package: OutputTemplate,
) -> None:
service_data = ServiceCompiler(
source_file=source_file,
parent=output_package,
proto_obj=service,
path=[6, index],
)
for j, method in enumerate(service.method):
ServiceMethodCompiler(
source_file=source_file,
parent=service_data,
proto_obj=method,
path=[6, index, 2, j],
)

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