Contributor Guide

Development Workflow

  1. If you are a first-time contributor:

    • Go to https://github.com/networkx/networkx and click the “fork” button to create your own copy of the project.

    • Clone the project to your local computer:

      git clone git@github.com:your-username/networkx.git

    • Navigate to the folder networkx and add the upstream repository:

      git remote add upstream git@github.com:networkx/networkx.git

    • Now, you have remote repositories named:

      • upstream, which refers to the networkx repository

      • origin, which refers to your personal fork

    • Next, you need to set up your build environment. Here are instructions for two popular environment managers:

      • venv (pip based)

        # Create a virtualenv named ``networkx-dev`` that lives in the directory of
# the same name
python -m venv networkx-dev
# Activate it
source networkx-dev/bin/activate
# Install main development and runtime dependencies of networkx
pip install -r <(cat requirements/{default,developer,doc,optional,test}.txt)
#
# (Optional) Install pygraphviz, pydot, and gdal packages
# These packages require that you have your system properly configured
# and what that involves differs on various systems.
# pip install -r requirements/extras.txt
#
# Build and install networkx from source
pip install -e .
# Test your installation
PYTHONPATH=. pytest networkx

      • conda (Anaconda or Miniconda)

        # Create a conda environment named ``networkx-dev``
conda create --name networkx-dev
# Activate it
conda activate networkx-dev
# Install main development and runtime dependencies of networkx
conda install -c conda-forge `for i in requirements/{default,developer,doc,optional,test}.txt; do echo -n " --file $i "; done`
#
# (Optional) Install pygraphviz, pydot, and gdal packages
# These packages require that you have your system properly configured
# and what that involves differs on various systems.
# pip install -r requirements/extras.txt
#
# Install networkx from source
pip install -e . --no-deps
# Test your installation
PYTHONPATH=. pytest networkx

    • Finally, we recommend you use a pre-commit hook, which runs black when you type git commit:

      pre-commit install

  2. Develop your contribution:

    • Pull the latest changes from upstream:

      git checkout master
git pull upstream master

    • Create a branch for the feature you want to work on. Since the branch name will appear in the merge message, use a sensible name such as ‘bugfix-for-issue-1480’:

      git checkout -b bugfix-for-issue-1480

    • Commit locally as you progress (git add and git commit)

  3. Test your contribution:

    • Run the test suite locally (see Testing for details):

      PYTHONPATH=. pytest networkx

    • Running the tests locally before submitting a pull request helps catch problems early and reduces the load on the continuous integration system.

  4. Submit your contribution:

    • Push your changes back to your fork on GitHub:

      git push origin bugfix-for-issue-1480

    • Go to GitHub. The new branch will show up with a green Pull Request button—click it.

    • If you want, post on the mailing list to explain your changes or to ask for review.

For a more detailed discussion, read these detailed documents on how to use Git with networkx (https://networkx.org/documentation/latest/developer/gitwash/index.html).

  1. Review process:

    • Reviewers (the other developers and interested community members) will write inline and/or general comments on your Pull Request (PR) to help you improve its implementation, documentation, and style. Every single developer working on the project has their code reviewed, and we’ve come to see it as friendly conversation from which we all learn and the overall code quality benefits. Therefore, please don’t let the review discourage you from contributing: its only aim is to improve the quality of project, not to criticize (we are, after all, very grateful for the time you’re donating!).

    • To update your pull request, make your changes on your local repository and commit. As soon as those changes are pushed up (to the same branch as before) the pull request will update automatically.

    • Travis-CI, a continuous integration service, is triggered after each Pull Request update to build the code and run unit tests of your branch. The Travis tests must pass before your PR can be merged. If Travis fails, you can find out why by clicking on the “failed” icon (red cross) and inspecting the build and test log.

    • AppVeyor, is another continuous integration service that we use. You will also need to make sure that the AppVeyor tests pass.

    Note

    If the PR closes an issue, make sure that GitHub knows to automatically close the issue when the PR is merged. For example, if the PR closes issue number 1480, you could use the phrase “Fixes #1480” in the PR description or commit message.

  2. Document changes

    If your change introduces any API modifications, please update doc/release/release_dev.rst.

    If your change introduces a deprecation, add a reminder to doc/developer/deprecations.rst for the team to remove the deprecated functionality in the future.

    Note

    To reviewers: make sure the merge message has a brief description of the change(s) and if the PR closes an issue add, for example, “Closes #123” where 123 is the issue number.

Divergence from upstream master

If GitHub indicates that the branch of your Pull Request can no longer be merged automatically, merge the master branch into yours:

git fetch upstream master
git merge upstream/master

If any conflicts occur, they need to be fixed before continuing. See which files are in conflict using:

git status

Which displays a message like:

Unmerged paths:
  (use "git add <file>..." to mark resolution)

  both modified:   file_with_conflict.txt

Inside the conflicted file, you’ll find sections like these:

<<<<<<< HEAD
The way the text looks in your branch
=======
The way the text looks in the master branch
>>>>>>> master

Choose one version of the text that should be kept, and delete the rest:

The way the text looks in your branch

Now, add the fixed file:

git add file_with_conflict.txt

Once you’ve fixed all merge conflicts, do:

git commit

Note

Advanced Git users are encouraged to rebase instead of merge, but we squash and merge most PRs either way.

Guidelines

  • All code should have tests.

  • All code should be documented, to the same standard as NumPy and SciPy.

  • All changes are reviewed. Ask on the mailing list if you get no response to your pull request.

  • Use the following import conventions:

    import numpy as np
import scipy as sp
import matplotlib as mpl
import matplotlib.pyplot as plt
import networkx as nx

  • Use the decorator not_implemented_for in networkx/utils/decorators.py to designate that a function doesn’t accept ‘directed’, ‘undirected’, ‘multigraph’ or ‘graph’. The first argument of the decorated function should be the graph object to be checked.

    @nx.not_implemented_for('directed', 'multigraph')
def function_not_for_MultiDiGraph(G, others):
    # function not for graphs that are directed *and* multigraph
    pass

@nx.not_implemented_for('directed')
@nx.not_implemented_for('multigraph')
def function_only_for_Graph(G, others):
    # function not for directed graphs *or* for multigraphs
    pass

Testing

networkx has an extensive test suite that ensures correct execution on your system. The test suite has to pass before a pull request can be merged, and tests should be added to cover any modifications to the code base. We make use of the pytest testing framework, with tests located in the various networkx/submodule/tests folders.

To run all tests:

$ PYTHONPATH=. pytest networkx

Or the tests for a specific submodule:

$ PYTHONPATH=. pytest networkx/readwrite

Or tests from a specific file:

$ PYTHONPATH=. pytest networkx/readwrite/tests/test_yaml.py

Or a single test within that file:

$ PYTHONPATH=. pytest networkx/readwrite/tests/test_yaml.py::TestYaml::testUndirected

Use --doctest-modules to run doctests. For example, run all tests and all doctests using:

$ PYTHONPATH=. pytest --doctest-modules networkx

Tests for a module should ideally cover all code in that module, i.e., statement coverage should be at 100%.

To measure the test coverage, run:

$ PYTHONPATH=. pytest --cov=networkx networkx

This will print a report with one line for each file in networkx, detailing the test coverage:

Name                                             Stmts   Miss Branch BrPart  Cover
----------------------------------------------------------------------------------
networkx/__init__.py                                33      2      2      1    91%
networkx/algorithms/__init__.py                    114      0      0      0   100%
networkx/algorithms/approximation/__init__.py       12      0      0      0   100%
networkx/algorithms/approximation/clique.py         42      1     18      1    97%
...