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CONTRIBUTING.md

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Contributing

Development

Add Poetry plugins

poetry self add poetry-dotenv-plugin
poetry self add poetry-bumpversion

Install dependencies

poetry install --all-extras

Add Pre-commit

poetry run pre-commit install

Tests

Setup

  • Add .env based on .env.template

Run

  • Run all

    poetry run pytest -s -v --log-cli-level=INFO

  • Run a specific test

    poetry run pytest -s -v --log-cli-level=INFO tests/test_core_sdk.py::test_flush

  • E2E tests involving OpenAI and Serp API are usually skipped, remove skip decorators in tests/test_langchain.py to run them.

Update openapi spec

  1. Generate Fern Python SDK in langfuse and copy the files generated in generated/python into the langfuse/api folder in this repo.
  2. Execute the linter by running poetry run ruff format .
  3. Rebuild and deploy the package to PyPi.

Publish release

Release script

Make sure you have your PyPi API token setup in your poetry config. If not, you can set it up by running:

poetry config pypi-token.pypi $your-api-token

Run the release script:

poetry run release

Manual steps (for prepatch versions)

  1. poetry version patch
    • poetry version prepatch for pre-release versions
  2. poetry install
  3. poetry build
  4. git commit -am "chore: release v{version}"
  5. git push
  6. git tag v{version}
  7. git push --tags
  8. poetry publish
  9. Create a release on GitHub with the changelog

SDK Reference

Note: The generated SDK reference is currently work in progress.

The SDK reference is generated via pdoc. You need to have all extra dependencies installed to generate the reference.

poetry install --all-extras

To update the reference, run the following command:

poetry run pdoc -o docs/ --docformat google --logo "https://langfuse.com/langfuse_logo.svg" langfuse

To run the reference locally, you can use the following command:

poetry run pdoc --docformat google --logo "https://langfuse.com/langfuse_logo.svg" langfuse

Credits

Thanks to the PostHog team for the awesome work on posthog-python. This project is based on it as it was the best starting point to build an async Python SDK.