CONTRIBUTING.rst

Contributing

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions

Report Bugs

Report bugs at https://gitlab.aicrowd.com/flatland/flatland/issues.

If you are reporting a bug, please include:

• Your operating system name and version.
• Any details about your local setup that might be helpful in troubleshooting.
• Detailed steps to reproduce the bug.

Fix Bugs

Look through the Repository Issue Tracker for bugs. Anything tagged with "bug" and "help wanted" is open to whoever wants to implement it.

Implement Features

Look through the Repository Issue Tracker for features. Anything tagged with "enhancement" and "help wanted" is open to whoever wants to implement it.

Write Documentation

flatland could always use more documentation, whether as part of the official flatland docs, in docstrings, or even on the web in blog posts, articles, and such. A quick reference for writing good docstrings is available at : https://docs.python-guide.org/writing/documentation/#writing-docstrings

Submit Feedback

The best way to send feedback is to file an issue at https://gitlab.aicrowd.com/flatland/flatland/issues.

If you are proposing a feature:

• Explain in detail how it would work.
• Keep the scope as narrow as possible, to make it easier to implement.
• Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!

Ready to contribute? Here's how to set up flatland for local development.

1. Fork the flatland repo on https://gitlab.aicrowd.com/flatland/flatland .

2. Clone your fork locally:

   $ git clone git@gitlab.aicrowd.com:flatland/flatland.git

3. Install the software dependencies via Anaconda-3 or Miniconda-3. (This assumes you have Anaconda installed by following the instructions here)

   $ conda install -c conda-forge tox-conda $ conda install tox $ tox -v --recreate

   This will create a virtual env you can then use.

   These steps are performed if you run

   $ getting_started/getting_started.bat/.sh

   from Anaconda prompt.

4. Create a branch for local development:

   $ git checkout -b name-of-your-bugfix-or-feature

   Now you can make your changes locally.

5. When you're done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:

   $ flake8 flatland tests examples benchmarks
   $ python setup.py test or py.test
   $ tox

   To get flake8 and tox, just pip install them into your virtualenv.

6. Commit your changes and push your branch to Gitlab:

   $ git add .
   $ git commit -m "Addresses #<issue-number> Your detailed description of your changes."
   $ git push origin name-of-your-bugfix-or-feature

7. Submit a merge request through the Gitlab repository website.

Merge Request Guidelines

Before you submit a merge request, check that it meets these guidelines:

1. The merge request should include tests.
2. If the merge request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
3. The merge request should work for Python 3.6, 3.7 and for PyPy. Check https://gitlab.aicrowd.com/flatland/flatland/pipelines and make sure that the tests pass for all supported Python versions.

Tips

To run a subset of tests:

$ py.test tests.test_flatland

Deploying

A reminder for the maintainers on how to deploy. Make sure all your changes are committed . Then run:

$ bumpversion patch # possible: major / minor / patch
$ git push
$ git push --tags

TODO: Travis will then deploy to PyPI if tests pass. (To be configured properly by Mohanty)

Local Evaluation

This document explains you how to locally evaluate your submissions before making an official submission to the competition.

Requirements

• flatland-rl : We expect that you have flatland-rl installed by following the instructions in [README.md](README.md).
• redis : Additionally you will also need to have redis installed and should have it running in the background.

Test Data

• test env data : You can download and untar the test-env-data <https://www.aicrowd.com/challenges/flatland-challenge/dataset_files>, at a location of your choice, lets say /path/to/test-env-data/. After untarring the folder, the folder structure should look something like:

.
└── test-env-data
    ├── Test_0
    │   ├── Level_0.pkl
    │   └── Level_1.pkl
    ├── Test_1
    │   ├── Level_0.pkl
    │   └── Level_1.pkl
    ├..................
    ├..................
    ├── Test_8
    │   ├── Level_0.pkl
    │   └── Level_1.pkl
    └── Test_9
        ├── Level_0.pkl
        └── Level_1.pkl

Evaluation Service

• start evaluation service : Then you can start the evaluator by running :

flatland-evaluator --tests /path/to/test-env-data/

RemoteClient

• run client : Some sample submission code can be found in the starter-kit, but before you can run your code locally using FlatlandRemoteClient, you will have to set the AICROWD_TESTS_FOLDER environment variable to the location where you previous untarred the folder with the test-env-data:

export AICROWD_TESTS_FOLDER="/path/to/test-env-data/"

# or on Windows :
#
# set AICROWD_TESTS_FOLDER "\path\to\test-env-data\"

# and then finally run your code
python run.py