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# Contributing to PyG
If you are interested in contributing to PyG, your contributions will likely fall into one of the following two categories:
1. You want to implement a new feature:
- In general, we accept any features as long as they fit the scope of this package. If you are unsure about this or need help on the design/implementation of your feature, post about it in an issue.
1. You want to fix a bug:
- Feel free to send a Pull Request (PR) any time you encounter a bug. Please provide a clear and concise description of what the bug was. If you are unsure about if this is a bug at all or how to fix, post about it in an issue.
Once you finish implementing a feature or bug-fix, please send a PR to https://github.com/pyg-team/pytorch_geometric.
Your PR will be merged after one or more rounds of reviews by the [pyg-team](https://github.com/pyg-team).
If your PR isn't merged anytime soon (*e.g.,* due to its large size, complexity or unavailability of reviewers), try moving your contribution to the [`torch_geometric.contrib`](https://pytorch-geometric.readthedocs.io/en/latest/modules/contrib.html) package.
[`torch_geometric.contrib`](https://pytorch-geometric.readthedocs.io/en/latest/modules/contrib.html) has less rigourous review requirements and might lead to your PR getting merged faster.
## Developing PyG
To develop PyG on your machine, here are some tips:
1. Ensure that you are running on one of the two latest PyTorch releases (*e.g.*, `2.8.0`):
```python
import torch
print(torch.__version__)
```
1. *(Optional)* Follow the [installation instructions](https://github.com/pyg-team/pytorch_geometric#installation) to install `pyg-lib`, `torch-scatter`, `torch-sparse`, `torch-cluster` and `torch-spline-conv` (if you haven't already).
Note that this step is optional and only necessary if you develop a feature that uses one of these libraries.
```bash
pip install pyg-lib torch-scatter torch-sparse torch-cluster torch-spline-conv -f https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html
```
where `${TORCH}` should be replaced by your PyTorch version (*e.g.*, `2.8.0`), and `${CUDA}` should be replaced by your CUDA version (*e.g.*, `cpu`, `cu126`, `cu128`, or `cu129`).
1. Uninstall all existing PyG installations.
It is advised to run this command repeatedly to confirm that installations across all locations are properly removed.
```bash
pip uninstall torch-geometric
pip uninstall torch-geometric # run this command twice
```
1. Fork and clone the PyG repository:
```bash
git clone https://github.com/<your_username>/pytorch_geometric
cd pytorch_geometric
```
1. If you already cloned PyG from source, update it:
```bash
git pull
```
1. Install PyG in editable mode:
```bash
pip install -e ".[dev,full]"
```
This mode will symlink the Python files from the current local source tree into the Python install.
Hence, if you modify a Python file, you do not need to re-install PyG again.
1. Ensure that you have a working PyG installation by running the entire test suite with
```bash
pytest
```
In case an error occurs, please first check if all sub-packages ([`pyg-lib`](https://github.com/pyg-team/pyg-lib), [`torch-scatter`](https://github.com/rusty1s/pytorch_scatter), [`torch-sparse`](https://github.com/rusty1s/pytorch_sparse), [`torch-cluster`](https://github.com/rusty1s/pytorch_cluster) and [`torch-spline-conv`](https://github.com/rusty1s/pytorch_spline_conv)) are on its latest reported version.
1. Install pre-commit hooks:
```bash
pre-commit install
```
## Unit Testing
The PyG testing suite is located under `test/`.
Run the entire test suite with
```bash
pytest
```
or test individual files via, *e.g.*, `pytest test/utils/test_convert.py`.
## Continuous Integration
PyG uses [GitHub Actions](https://github.com/pyg-team/pytorch_geometric/actions) in combination with [CodeCov](https://codecov.io/github/pyg-team/pytorch_geometric?branch=master) for continuous integration.
Everytime you send a Pull Request, your commit will be built and checked against the PyG guidelines:
1. Ensure that your code is formatted correctly by testing against the styleguide of [`flake8`](https://github.com/PyCQA/flake8).
We use the [`Flake8-pyproject`](https://pypi.org/project/Flake8-pyproject/) plugin for configuration:
```bash
flake8 .
```
If you do not want to format your code manually, we recommend to use [`yapf`](https://github.com/google/yapf).
1. Ensure that the entire test suite passes and that code coverage roughly stays the same.
Please feel encouraged to provide a test with your submitted code.
To test, either run
```bash
pytest --cov
```
or
```bash
FULL_TEST=1 pytest --cov
```
(which runs a set of additional but time-consuming tests) dependening on your needs.
1. Add your feature/bugfix to the [`CHANGELOG.md`](https://github.com/pyg-team/pytorch_geometric/blob/master/CHANGELOG.md?plain=1).
If multiple PRs move towards integrating a single feature, it is advised to group them together into one bullet point.
## Building Documentation
To build the documentation:
1. [Build and install](#developing-pyg) PyG from source.
1. Install [Sphinx](https://www.sphinx-doc.org/en/master/) theme via
```bash
pip install git+https://github.com/pyg-team/pyg_sphinx_theme.git
```
1. Generate the documentation via:
```bash
cd docs
make html
```
The documentation is now available to view by opening `docs/build/html/index.html`.
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