Contributing to GeoPandas#

(Contribution guidelines largely copied from pandas)


Contributions to GeoPandas are very welcome. They are likely to be accepted more quickly if they follow these guidelines.

At this stage of GeoPandas development, the priorities are to define a simple, usable, and stable API and to have clean, maintainable, readable code. Performance matters, but not at the expense of those goals.

In general, GeoPandas follows the conventions of the pandas project where applicable.

In particular, when submitting a pull request:

  • All existing tests should pass. Please make sure that the test suite passes, both locally and on GitHub Actions. Status on GHA will be visible on a pull request. GHA are automatically enabled on your own fork as well. To trigger a check, make a PR to your own fork.

  • New functionality should include tests. Please write reasonable tests for your code and make sure that they pass on your pull request.

  • Classes, methods, functions, etc. should have docstrings. The first line of a docstring should be a standalone summary. Parameters and return values should be documented explicitly.

  • Follow PEP 8 when possible. We use Black and ruff to ensure a consistent code format throughout the project. For more details see below.

  • Imports should be grouped with standard library imports first, 3rd-party libraries next, and GeoPandas imports third. Within each grouping, imports should be alphabetized. Always use absolute imports when possible, and explicit relative imports for local imports when necessary in tests.

  • GeoPandas supports Python 3.9+ only. The last version of GeoPandas supporting Python 2 is 0.6.

  • Unless your PR implements minor changes or internal work only, make sure it contains a note describing the changes in the file.

Seven Steps for Contributing#

There are seven basic steps to contributing to GeoPandas:

  1. Fork the GeoPandas git repository

  2. Create a development environment

  3. Install GeoPandas dependencies

  4. Make a development build of GeoPandas

  5. Make changes to code and add tests

  6. Update the documentation

  7. Submit a Pull Request

Each of these 7 steps is detailed below.

1) Forking the GeoPandas repository using Git#

To the new user, working with Git is one of the more daunting aspects of contributing to GeoPandas. It can very quickly become overwhelming, but sticking to the guidelines below will help keep the process straightforward and mostly trouble free. As always, if you are having difficulties please feel free to ask for help.

The code is hosted on GitHub. To contribute you will need to sign up for a free GitHub account. We use Git for version control to allow many people to work together on the project.

Some great resources for learning Git:

Getting started with Git#

GitHub has instructions for installing git, setting up your SSH key, and configuring git. All these steps need to be completed before you can work seamlessly between your local repository and GitHub.


You will need your own fork to work on the code. Go to the GeoPandas project page and hit the Fork button. You will want to clone your fork to your machine:

git clone geopandas-yourname
cd geopandas-yourname
git remote add upstream git://

This creates the directory geopandas-yourname and connects your repository to the upstream (main project) GeoPandas repository.

The testing suite will run automatically on GitHub Actions once your pull request is submitted. The test suite will also automatically run on your branch so you can check it prior to submitting the pull request.

Creating a branch#

You want your main branch to reflect only production-ready code, so create a feature branch for making your changes. For example:

git branch shiny-new-feature
git checkout shiny-new-feature

The above can be simplified to:

git checkout -b shiny-new-feature

This changes your working directory to the shiny-new-feature branch. Keep any changes in this branch specific to one bug or feature so it is clear what the branch brings to GeoPandas. You can have many shiny-new-features and switch in between them using the git checkout command.

To update this branch, you need to retrieve the changes from the main branch:

git fetch upstream
git rebase upstream/main

This will replay your commits on top of the latest GeoPandas git main. If this leads to merge conflicts, you must resolve these before submitting your pull request. If you have uncommitted changes, you will need to stash them prior to updating. This will effectively store your changes and they can be reapplied after updating.

2) Creating a development environment#

A development environment is a virtual space where you can keep an independent installation of GeoPandas. This makes it easy to keep both a stable version of python in one place you use for work, and a development version (which you may break while playing with code) in another.

An easy way to create a GeoPandas development environment is as follows:

Using the provided environment#

GeoPandas provides an environment which includes the required dependencies for development. The environment file is located in the top level of the repo and is named environment-dev.yml. You can create this environment by navigating to the the geopandas source directory and running:

conda env create -f environment-dev.yml

This will create a new conda environment named geopandas_dev.

Creating the environment manually#

Alternatively, it is possible to create a development environment manually. To do this, tell conda to create a new environment named geopandas_dev, or any other name you would like for this environment, by running:

conda create -n geopandas_dev python

This will create the new environment, and not touch any of your existing environments, nor any existing python installation.

Working with the environment#

To work in this environment, you need to activate it. The instructions below should work for both Windows, Mac and Linux:

conda activate geopandas_dev

Once your environment is activated, you will see a confirmation message to indicate you are in the new development environment.

To view your environments:

conda info -e

To return to you home root environment:

conda deactivate

See the full conda docs here.

At this point you can easily do a development install, as detailed in the next sections.

3) Installing Dependencies#

To run GeoPandas in an development environment, you must first install the dependencies of GeoPandas. If you used the provided environment in section 2, skip this step and continue to section 4. If you created the environment manually, we suggest installing dependencies using the following commands (executed after your development environment has been activated):

conda install -c conda-forge pandas pyogrio shapely pyproj pytest

This should install all necessary dependencies.

4) Making a development build#

Once dependencies are in place, make an in-place build by navigating to the git clone of the GeoPandas repository and running:

python -m pip install -e .

5) Making changes and writing tests#

GeoPandas is serious about testing and strongly encourages contributors to embrace test-driven development (TDD). This development process “relies on the repetition of a very short development cycle: first the developer writes an (initially failing) automated test case that defines a desired improvement or new function, then produces the minimum amount of code to pass that test.” So, before actually writing any code, you should write your tests. Often the test can be taken from the original GitHub issue. However, it is always worth considering additional use cases and writing corresponding tests.

Adding tests is one of the most common requests after code is pushed to GeoPandas. Therefore, it is worth getting in the habit of writing tests ahead of time so this is never an issue.

GeoPandas uses the pytest testing system and the convenient extensions in numpy.testing.

Writing tests#

All tests should go into the tests directory. This folder contains many current examples of tests, and we suggest looking to these for inspiration.

The .util module has some special assert functions that make it easier to make statements about whether GeoSeries or GeoDataFrame objects are equivalent. The easiest way to verify that your code is correct is to explicitly construct the result you expect, then compare the actual result to the expected correct result, using eg the function assert_geoseries_equal.

Running the test suite#

The tests can then be run directly inside your Git clone (without having to install GeoPandas) by typing:


6) Updating the Documentation#

GeoPandas documentation resides in the doc folder. Changes to the docs are made by modifying the appropriate file in the source folder within doc. GeoPandas docs use mixture of reStructuredText syntax for rst files, which is explained here and MyST syntax for md files explained here. The docstrings follow the Numpy Docstring standard. Some pages and examples are Jupyter notebooks converted to docs using nbsphinx. Jupyter notebooks should be stored without the output.

We highly encourage you to follow the Google developer documentation style guide when updating or creating new documentation.

Once you have made your changes, you may try if they render correctly by building the docs using sphinx. To do so, you can navigate to the doc folder:

cd doc

and type:

make html

The resulting html pages will be located in doc/build/html.

In case of any errors, you can try to use make html within a new environment based on environment.yml specification in the doc folder. You may need to register Jupyter kernel as geopandas_docs. Using conda:

cd doc
conda env create -f environment.yml
conda activate geopandas_docs
python -m ipykernel install --user --name geopandas_docs
make html

For minor updates, you can skip the make html part as reStructuredText and MyST syntax are usually quite straightforward.

7) Submitting a Pull Request#

Once you’ve made changes and pushed them to your forked repository, you then submit a pull request to have them integrated into the GeoPandas code base.

You can find a pull request (or PR) tutorial in the GitHub’s Help Docs.

Style Guide & Linting#

GeoPandas follows the PEP8 standard and uses Black and ruff to ensure a consistent code format throughout the project.

Continuous Integration (GitHub Actions) will run those tools and report any stylistic errors in your code. Therefore, it is helpful before submitting code to run the check yourself:

black geopandas
git diff upstream/main -u -- "*.py" | ruff .

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

Optionally (but recommended), you can setup pre-commit hooks to automatically run black and ruff when you make a git commit. If you did not use the provided development environment in environment-dev.yml, you must first install pre-commit:

$ python -m pip install pre-commit

From the root of the geopandas repository, you should then install the pre-commit included in GeoPandas:

$ pre-commit install

Then black and ruff will be run automatically each time you commit changes. You can skip these checks with git commit --no-verify.

Commit message conventions#

Commit your changes to your local repository with an explanatory message. GeoPandas uses the pandas convention for commit message prefixes and layout. Here are some common prefixes along with general guidelines for when to use them:

  • ENH: Enhancement, new functionality

  • BUG: Bug fix

  • DOC: Additions/updates to documentation

  • TST: Additions/updates to tests

  • BLD: Updates to the build process/scripts

  • PERF: Performance improvement

  • TYP: Type annotations

  • CLN: Code cleanup

The following defines how a commit message should be structured. Please refer to the relevant GitHub issues in your commit message using GH1234 or #1234. Either style is fine, but the former is generally preferred:

  • a subject line with < 80 chars.

  • One blank line.

  • Optionally, a commit message body.

Now you can commit your changes in your local repository:

git commit -m