Contributor Guidelines
===============================

If you are interested in contributing to GLI, your contributions will
likely fall into one of the following three categories:

1. You want to contribute a new dataset/task.
2. You want to implement a new feature.
3. You want to fix a bug.

Developing GLI
--------------

To develop GLI on your machine, here are some tips:

1. Clone a copy of GLI from source:

   .. code:: bash

      git clone https://github.com/Graph-Learning-Benchmarks/gli.git
      cd gli

2. If you already cloned GLI from source, update it:

   ::

      git pull

3. Install GLI with full dependencies:

   ::

      pip install -e ".[test,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 reinstall GLI again.

4. Run an example:

   ::

      python3 example.py

   This script will load the ``NodeClassification`` task on ``cora``
   dataset.

5. Ensure your installation is correct by running the entire test suite
   with

   ::

        make pytest

Contributing A New Dataset
--------------------------

Here is a checklist for a new dataset. Please `open a pull
request <https://github.com/Graph-Learning-Benchmarks/gli/pulls>`__
that contains a directory in following format:

::

   datasets/<name>
   ├── <name>.ipynb/<name>.py
   ├── README.md
   ├── LICENSE
   ├── metadata.json
   ├── task_<task_type>.json
   ├── ...  # There might be multiple task configurations.
   └── urls.json

where ``<name>`` is the dataset name and ``<task_type>`` is one of the
given tasks defined in `GLI Task Format <FORMAT.md#gli-task-format>`__.

-  ``<name>.ipynb/<name>.py``: A Jupyter Notebook or Python script that
   converts the original dataset into GLI format.
-  ``README.md``: A document that contains the necessary information
   about the dataset and task(s), including description, citation(s),
   available task(s), and extra required packages for
   ``<name>.ipynb/<name>.py``.
-  ``LICENSE``: A license file that is used by the current dataset maintainer.
-  ``metadata.json``: A json configuration file that stores the metadata
   of the graph dataset. See `GLI Data
   Format <FORMAT.md#gli-data-format>`__.
-  ``task_<task_type>.json``: A task configuration file that stores an
   available task on the given dataset. See `GLI Task
   Format <FORMAT.md#gli-task-format>`__. Contributors can define
   multiple tasks on the same dataset. If the task type is the same, use
   ``task_<task_type>_<id>.json`` to distinguish between same tasks,
   where ``<id>`` should be replaced by 1, 2, etc.
-  ``urls.json``: A url configuration file that stores the downloading
   urls of the uploaded files.

Uploading GLI Data Files
~~~~~~~~~~~~~~~~~~~~~~~~

Please upload the npz or npy files referred in ``metadata.json`` or
``task_<task_type>.json`` to dropbox and include the public download links in ``urls.json``. Due to anonymous requirement, the link is hidden in this document for now.

Reporting Bugs
--------------

Please feel free to `report a bug through
Issues <https://github.com/Graph-Learning-Benchmarks/gli/issues/new?assignees=&labels=bug&template=bug_report.md&title=%5BBUG%5D>`__
and/or `open a pull request to implement
it <https://github.com/Graph-Learning-Benchmarks/gli/pulls>`__.
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.

Implementing New Features
-------------------------

Please feel free to `request a new feature through
Issues <https://github.com/Graph-Learning-Benchmarks/gli/issues/new?assignees=&labels=enhancement&template=feature_request.md&title=%5BFEATURE+REQUEST%5D>`__
and/or `open a pull request to implement
it <https://github.com/Graph-Learning-Benchmarks/gli/pulls>`__.
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.