python-development
Python Development in Apache Beam
Project Structure
Key Directories
sdks/python/- Python SDK rootapache_beam/- Main Beam packagetransforms/- Core transforms (ParDo, GroupByKey, etc.)io/- I/O connectorsml/- Beam ML code (RunInference, etc.)runners/- Runner implementations and wrappersrunners/worker/- SDK worker harness
container/- Docker container configurationtest-suites/- Test configurationsscripts/- Utility scripts
Configuration Files
setup.py- Package configurationpyproject.toml- Build configurationtox.ini- Test automationpytest.ini- Pytest configuration.pylintrc- Linting rules.isort.cfg- Import sortingmypy.ini- Type checking
Environment Setup
Using pyenv (Recommended)
# Install Python
pyenv install 3.X # Use supported version from gradle.properties
# Create virtual environment
pyenv virtualenv 3.X beam-dev
pyenv activate beam-dev
Install in Editable Mode
cd sdks/python
pip install -e .[gcp,test]
Enable Pre-commit Hooks
pip install pre-commit
pre-commit install
# To disable
pre-commit uninstall
Running Tests
Unit Tests (filename: *_test.py)
# Run all tests in a file
pytest -v apache_beam/io/textio_test.py
# Run tests in a class
pytest -v apache_beam/io/textio_test.py::TextSourceTest
# Run a specific test
pytest -v apache_beam/io/textio_test.py::TextSourceTest::test_progress
Integration Tests (filename: *_it_test.py)
On Direct Runner
python -m pytest -o log_cli=True -o log_level=Info \
apache_beam/ml/inference/pytorch_inference_it_test.py::PyTorchInference \
--test-pipeline-options='--runner=TestDirectRunner'
On Dataflow Runner
# First build SDK tarball
pip install build && python -m build --sdist
# Run integration test
python -m pytest -o log_cli=True -o log_level=Info \
apache_beam/ml/inference/pytorch_inference_it_test.py::PyTorchInference \
--test-pipeline-options='--runner=TestDataflowRunner --project=<project>
--temp_location=gs://<bucket>/tmp
--sdk_location=dist/apache-beam-2.XX.0.dev0.tar.gz
--region=us-central1'
Building Python SDK
Build Source Distribution
cd sdks/python
pip install build && python -m build --sdist
# Output: sdks/python/dist/apache-beam-X.XX.0.dev0.tar.gz
Build Wheel (faster installation)
./gradlew :sdks:python:bdistPy311linux # For Python 3.11 on Linux
Build and Push SDK Container Image
./gradlew :sdks:python:container:py311:docker \
-Pdocker-repository-root=gcr.io/your-project/your-name \
-Pdocker-tag=custom \
-Ppush-containers
# Container image will be pushed to: gcr.io/your-project/your-name/beam_python3.11_sdk:custom
To use this container image, supply it via --sdk_container_image.
Running Pipelines with Modified Code
# Install modified SDK
pip install /path/to/apache-beam.tar.gz[gcp]
# Run pipeline
python my_pipeline.py \
--runner=DataflowRunner \
--sdk_location=/path/to/apache-beam.tar.gz \
--project=my_project \
--region=us-central1 \
--temp_location=gs://my-bucket/temp
Common Issues
NameError when running DoFn
Global imports, functions, and variables in the main pipeline module are not serialized by default. Use:
--save_main_session
Specifying Additional Dependencies
Use --requirements_file=requirements.txt or custom containers.
Test Markers
@pytest.mark.it_postcommit- Include in PostCommit test suite
Gradle Commands for Python
# Run WordCount
./gradlew :sdks:python:wordCount
# Check environment
./gradlew :checkSetup
Code Quality Tools
# Linting
pylint apache_beam/
# Type checking
mypy apache_beam/
# Formatting (via yapf)
yapf -i apache_beam/file.py
# Import sorting
isort apache_beam/file.py
More from apache/beam
gradle-build
Guides understanding and using the Gradle build system in Apache Beam. Use when building projects, understanding dependencies, or troubleshooting build issues.
48java-development
Guides Java SDK development in Apache Beam, including building, testing, running examples, and understanding the project structure. Use when working with Java code in sdks/java/, runners/, or examples/java/.
27license-compliance
Ensures all new files include proper Apache 2.0 license headers. Use when creating any new file in the Apache Beam repository.
24ci-cd
Guides understanding and working with Apache Beam's CI/CD system using GitHub Actions. Use when debugging CI failures, understanding test workflows, or modifying CI configuration.
23contributing
Guides the contribution workflow for Apache Beam, including creating PRs, issue management, code review process, and release cycles. Use when contributing code, creating PRs, or understanding the contribution process.
23beam-concepts
Explains core Apache Beam programming model concepts including PCollections, PTransforms, Pipelines, and Runners. Use when learning Beam fundamentals or explaining pipeline concepts.
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