RDFLib developers guide


This document describes the process and conventions to follow when developing RDFLib code.

  • Please be as Pythonic as possible (PEP 8).

  • Code should be formatted using black and we use Black v22.6.0, with the black config in pyproject.toml.

  • Code should also pass flake8 linting and mypy type checking.

  • You must supply tests for new code.

If you add a new cool feature, consider also adding an example in ./examples

Pull Requests Guidelines

Contributions to RDFLib are made through pull requests (PRs).

In general, maintainers will only merge PRs if the following conditions are met:

  • The PR has been sufficiently reviewed.

    Each PR should be reviewed and approved by at least two people other than the author of the PR before it is merged and PRs will be processed faster if they are easier to review and approve of.

    Reviews are open to everyone, but the weight assigned to any particular review is at the discretion of maintainers.

  • Changes that have a runtime impact are covered by unit tests.

    There should either be existing tests that cover the changed code and behaviour, or the PR should include tests. For more information about what is considered adequate testing see the Tests section.

  • Documentation that covers something that changed has been updated.

  • Type checks and unit tests that are part of our continuous integration workflow pass.

In addition to these conditions, PRs that are easier to review and approve will be processed quicker. The primary factors that determine this is the scope and size of a PR. If there are few changes and the scope is limited then there is less that a reviewer has to understand and less that they can disagree with. It is thus important to try and split up your changes into multiple independent PRs if possible. No PR is too small.

For PRs that introduce breaking changes, it is even more critical that they are limited in size and scope, as they will likely have to be kept up to date with the main branch of this project for some time before they are merged.

It is also critical that your PR is understandable both in what it does and why it does it, and how the change will impact the users of this project, for this reason it is essential that your PR’s description explains the nature of the PR, what the PR intends to do, why this is desirable, and how this will affect the users of this project.

Please note that while we would like all PRs to follow the guidelines given here, we will not reject a PR just because it does not.


Any new functionality being added to RDFLib must have unit tests and should have doc tests supplied.

Typically, you should add your functionality and new tests to a branch of RDFlib and and run all tests locally and see them pass. There are currently close to 4,000 tests with a few extra expected failures and skipped tests. We won’t allow Pull Requests that break any of the existing tests.

Tests that you add should show how your new feature or bug fix is doing what you say it is doing: if you remove your enhancement, your new tests should fail!

Finally, please consider adding simple and more complex tests. It’s good to see the basic functionality of your feature tests and then also any tricky bits or edge cases.

Testing framework

RDFLib uses the pytest testing framework.

Running tests

To run RDFLib’s test suite with pytest:

$ pip install -r requirements.txt -r requirements.dev.txt
$ pytest

Specific tests can be run by file name. For example:

$ pytest test/test_graph.py

For more extensive tests, including tests for the berkleydb backend, install the requirements from requirements.dev-extra.txt before executing the tests.

$ pip install -r requirements.txt -r requirements.dev.txt
$ pip install -r requirements.dev-extra.txt
$ pytest

Writing tests

New tests should be written for pytest instead of for python’s built-in unittest module as pytest provides advanced features such as parameterization and more flexibility in writing expected failure tests than unittest.

A primer on how to write tests for pytest can be found here.

The existing tests that use unittest work well with pytest, but they should ideally be updated to the pytest test-style when they are touched.

Test should go into the test/ directory, either into an existing test file with a name that is applicable to the test being written, or into a new test file with a name that is descriptive of the tests placed in it. Test files should be named test_*.py so that pytest can discover them.

Running static checks

Check formatting with black, making sure you use our black.toml config file:

python -m black --config black.toml --check ./rdflib

Check style and conventions with flake8:

python -m flake8 rdflib

We also provide a flakeheaven baseline that ignores existing flake8 errors and only reports on newly introduced flake8 errors:

python -m flakeheaven

Check types with mypy:

python -m mypy --show-error-context --show-error-codes rdflib

pre-commit and pre-commit ci

We have pre-commit configured with black for formatting code.

Some useful commands for using pre-commit:

# Install pre-commit.
pip install --user --upgrade pre-commit

# Install pre-commit hooks, this will run pre-commit
# every time you make a git commit.
pre-commit install

# Run pre-commit on changed files.
pre-commit run

# Run pre-commit on all files.
pre-commit run --all-files

There is also two tox environments for pre-commit:

# run pre-commit on changed files.
tox -e precommit

# run pre-commit on all files.
tox -e precommitall

There is no hard requirement for pull requests to be processed with pre-commit (or the underlying processors), however doing this makes for a less noisy codebase with cleaner history.

We have enabled https://pre-commit.ci/ and this can be used to automatically fix pull requests by commenting pre-commit.ci autofix on a pull request.

Using tox

RDFLib has a tox config file that makes it easier to run validation on all supported python versions.

# Install tox.
pip install tox

# List the tox environments that run by default.
tox -e

# Run the default environments.

# List all tox environments, including ones that don't run by default.
tox -a

# Run a specific environment.
tox -e py37 # default environment with py37
tox -e py39-extra # extra tests with py39

# Override the test command.
# the below command will run `pytest test/test_translate_algebra.py`
# instead of the default pytest command.
tox -e py37,py39 -- pytest test/test_translate_algebra.py

go-task and Taskfile.yml

A Taskfile.yml is provided for go-task with various commands that facilitate development.

Instructions for installing go-task can be seen in the go-task installation guide.

Some useful commands for working with the task in the taskfile is given below:

# List available tasks.
task -l

# Install pip dependencies
task install:pip-deps

# Run basic validation
task validate

# Install a venv and run validation inside venv
task venv:install
task WITH_VENV=1 validate

# Fix all auto-fixable validation errors (i.e. run black and isort) using venv
task WITH_VENV=1 validate:fix

# Build docs inside venv
task WITH_VENV=1 docs:build

# Run live-preview on the docs
task docs:live-server

# Run the py310 tox environment
task tox -- -e py310

The Taskfile usage documentation provides more information on how to work with taskfiles.

Development container

To simplify the process of getting a working development environment to develop rdflib in we provide a Development Container (devcontainer) that is configured in Docker Compose. This container can be used directly to run various commands, or it can be used with editors that support Development Containers.


The devcontainer is intended to run with a rootless docker daemon so it can edit files owned by the invoking user without an invovled configuration process.

Using a rootless docker daemon also has general security benefits.

To use the development container directly:

# Build the devcontainer docker image.
docker-compose build

# Run the validate task inside the devtools container.
docker-compose run --rm devcontainer task validate

# Run extensive tests inside the devtools container.
docker-compose run --rm devcontainer task EXTENSIVE=true test

# To get a shell into the devcontainer docker image.
docker-compose run --rm devcontainer bash

The devcontainer also works with Podman Compose.

Details on how to use the development container with VSCode can found in the Developing inside a Container page. With the VSCode development container CLI installed the following command can be used to open the repository inside the development container:

# Inside the repository base directory
cd ./rdflib/

# Build the development container.
devcontainer build .

# Open the code inside the development container.
devcontainer open .

Writing documentation

We use sphinx for generating HTML docs, see Writing RDFLib Documentation.

Continuous Integration

We used GitHub Actions for CI, see:

If you make a pull-request to RDFLib on GitHub, GitHub Actions will automatically test your code and we will only merge code passing all tests.

Please do not commit tests you know will fail, even if you’re just pointing out a bug. If you commit such tests, flag them as expecting to fail.


RDFlib 6.0.0 release and later only support Python 3.7 and newer.

RDFLib 5.0.0 maintained compatibility with Python versions 2.7, 3.4, 3.5, 3.6, 3.7.


Set to-be-released version number in rdflib/__init__.py and README.md. Check date in LICENSE.

Add CHANGELOG.md entry.

Commit this change. It’s preferable make the release tag via https://github.com/RDFLib/rdflib/releases/new :: Our Tag versions aren’t started with ‘v’, so just use a plain 5.0.0 like version. Release title is like “RDFLib 5.0.0”, the description a copy of your CHANGELOG.md entry. This gives us a nice release page like this:: https://github.com/RDFLib/rdflib/releases/tag/4.2.2

If for whatever reason you don’t want to take this approach, the old one is:

Tagging the release commit with::

  git tag -am 'tagged version' X.X.X

When pushing, remember to do::

  git push --tags

No matter how you create the release tag, remember to upload tarball to pypi with:

rm -r dist/X.X.X[.-]*  # delete all previous builds for this release, just in case

rm -r build
python setup.py sdist
python setup.py bdist_wheel
ls dist

# upload with twine
# WARNING: once uploaded can never be modified, only deleted!
twine upload dist/rdflib-X.X.X[.-]*

Set new dev version number in the above locations, i.e. next release -dev: 5.0.1-dev and commit again.

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