Contributor Guide

xarray-simlab is an open-source project. Contributions are welcome, and they are greatly appreciated!

You can contribute in many ways, e.g., by reporting bugs, submitting feedbacks, contributing to the development of the code and/or the documentation, etc.

This page provides resources on how best to contribute.


The Github Issue Tracker is the right place for reporting bugs and for discussing about development ideas. Feel free to open a new issue if you have found a bug or if you have suggestions about new features or changes.

For now, as the project is still very young, it is also a good place for asking usage questions.

Development environment

If you wish to contribute to the development of the code and/or the documentation, here are a few steps for setting a development environment.

Fork the repository and download the code

To further be able to submit modifications, it is preferable to start by forking the xarray-simlab repository on GitHub (you need to have an account).

Then clone your fork locally:

$ git clone

Alternatively, if you don’t plan to submit any modification, you can clone the original xarray-simlab git repository:

$ git clone


To install the dependencies, we recommend using the conda package manager with the conda-forge channel. For development purpose, you might consider installing the packages in a new conda environment:

$ conda create -n xarray-simlab_dev python attrs numpy xarray zarr dask -c conda-forge
$ conda activate xarray-simlab_dev

Then install xarray-simlab locally (in development mode) using pip:

$ cd xarray-simlab
$ python -m pip install -e .

Run tests

To make sure everything behaves as expected, you may want to run xarray-simlab’s unit tests locally using the pytest package. You can first install it with conda:

$ conda install pytest pytest-cov pytest-mock -c conda-forge

Then you can run tests from the main xarray-simlab directory:

$ pytest xsimlab --verbose

Contributing to code

Below are some useful pieces of information in case you want to contribute to the code.

Local development

Once you have setup the development environment, the next step is to create a new git branch for local development:

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

Now you can make your changes locally.

Submit changes

Once you are done with the changes, you can commit your changes to git and push your branch to your xarray-simlab fork on GitHub:

$ git add .
$ git commit -m "Your detailed description of your changes."
$ git push origin name-of-your-bugfix-or-feature

(note: this operation may be repeated several times).

We you are ready, you can create a new pull request through the GitHub website (note that it is still possible to submit changes after your created a pull request).

Python versions

xarray-simlab supports Python versions 3.6 and higher. It is not compatible with Python versions 2.x. We don’t plan to make it compatible with Python 2.7.x.


xarray-simlab’s uses unit tests extensively to make sure that every part of the code behaves as we expect. Test coverage is required for all code contributions.

Unit tests are written using pytest style (i.e., mostly using the assert statement directly) in various files located in the xsimlab/tests folder. The file defines some process decorated classes, Model objects and xarray.Dataset objects that can be used as fixtures for testing.

You can run the tests locally from the main xarray-simlab directory:

$ pytest xsimlab --verbose

All the tests are also executed automatically on continuous integration platforms on every push to every pull request on GitHub.


Everything (i.e., classes, methods, functions…) that is part of the public API should follow the numpydoc standard when possible.

Code Formatting & linting

xarray-simlab uses black and flake8 to ensure a consistent code format throughout the project. Both of these tools can be installed with either conda or pip. Once installed in your development environment, your can run them from the root of the xarray-simlab repository:

$ black .
$ flake8

to auto-format your code. For convenience, many editors have plugins that will apply black as you edit files.

flake8 reports warnings and/or errors about code formatting. It may also detect other programming errors.

Like unit tests, These tools are also run on continuous platforms for every code change submission.

Release notes

Every significative code contribution should be listed in Section Release Notes of this documentation under the corresponding version.

Contributing to documentation

xarray-simlab uses Sphinx for documentation, hosted on . Documentation is maintained in the RestructuredText markup language (.rst files) in xarray-simlab/doc.

To build the documentation locally, first install requirements (for example here in a separate conda environment):

$ conda env create -n xarray-simlab_doc -f doc/environment.yml
$ conda activate xarray-simlab_doc

Then build documentation with make:

$ cd doc
$ make html

The resulting HTML files end up in the build/html directory.

You can now make edits to rst files and run make html again to update the affected pages.