Guides Python SDK development in Apache Beam, including environment setup, testing, building, and running pipelines. Use when working with Python code in sdks/python/.
Install
npx skillscat add apache/beam/python-development Install via the SkillsCat registry.
SKILL.md
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-devInstall 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 uninstallRunning 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_progressIntegration 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.gzBuild Wheel (faster installation)
./gradlew :sdks:python:bdistPy311linux # For Python 3.11 on LinuxBuild 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:customTo 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/tempCommon Issues
NameError when running DoFn
Global imports, functions, and variables in the main pipeline module are not serialized by default. Use:
--save_main_sessionSpecifying 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 :checkSetupCode 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