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 Travis CI. Status on Travis will be visible on a pull request. If you want to enable Travis CI on your own fork, please read the pandas guidelines link above or the getting started docs.
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.
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 3.5+ only. The last version of GeoPandas supporting Python 2 is 0.6.
Seven Steps for Contributing¶
There are seven basic steps to contributing to GeoPandas:
Fork the GeoPandas git repository
Create a development environment
Install GeoPandas dependencies
developmentbuild of GeoPandas
Make changes to code and add tests
Update the documentation
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.
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 email@example.com:your-user-name/geopandas.git geopandas-yourname cd geopandas-yourname git remote add upstream git://github.com/geopandas/geopandas.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 Travis-CI once your pull request is submitted. However, if you wish to run the test suite on a branch prior to submitting the pull request, then Travis-CI needs to be hooked up to your GitHub repository. Instructions for doing so are here.
Creating a branch¶
You want your master 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 master branch:
git fetch upstream git rebase upstream/master
This will replay your commits on top of the latest GeoPandas git master. 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
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:
Make sure that you have cloned the repository
cdto the geopandas* source directory
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.
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:
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 GeoPandas’s dependencies. We suggest doing so using the following commands (executed after your development environment has been activated):
conda install -c conda-forge pandas fiona shapely pyproj rtree 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 setup.py develop
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.
All tests should go into the
tests directory. This folder contains many
current examples of tests, and we suggest looking to these for inspiration.
.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
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 make by modifying the appropriate file in the source folder within doc. GeoPandas docs use reStructuredText syntax, which is explained here and the docstrings follow the Numpy Docstring standard.
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 and type:
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. Using conda:
conda env create -f environment.yml conda activate geopandas_docs make html
For minor updates, you can skip whole make html part as reStructuredText syntax is 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¶
Continuous Integration (Travis CI) 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/master -u -- "*.py" | flake8 --diff
to auto-format your code. Additionally, many editors have plugins that will
black as you edit files.
Optionally (but recommended), you can setup pre-commit hooks
to automatically run
flake8 when you make a git commit. This
can be done by installing
$ 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
flake8 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