The Matplotlib Developers’ Guide

Release:2.0.2 Date:May 10, 2017

• Contributing
  • Submitting a bug report
  • Retrieving and installing the latest version of the code
  • Contributing code
  • Other ways to contribute
  • Coding guidelines
• Developer’s tips for testing
  • Requirements
  • Building matplotlib for image comparison tests
  • Running the tests
  • Writing a simple test
  • Writing an image comparison test
  • Known failing tests
  • Creating a new module in matplotlib.tests
  • Using Travis CI
  • Using tox
• Developer’s tips for documenting matplotlib
  • Getting started
  • Organization of matplotlib’s documentation
  • Formatting
  • Figures
  • Referring to mpl documents
  • Internal section references
  • Section names, etc
  • Inheritance diagrams
  • Emacs helpers
• Developer’s guide for creating scales and transformations
  • Creating a new scale
  • Creating a new projection
  • API documentation
• Developer’s tips for writing code for Python 2 and 3
  • Welcome to the __future__
  • Finding places to use six
  • The dreaded \u escapes
  • Iteration
  • Numpy-specific things
• Working with Matplotlib source code
  • Introduction
  • Install git
  • Following the latest source
  • Making a patch
  • Git for development
  • git resources
  • Two and three dots in difference specs
• Reviewers guideline
  • Pull request checklist
  • PR Review guidelines
  • Backports
• Release Guide
  • All Releases
• Matplotlib Enhancement Proposals
  • MEP Template
  • MEP8: PEP8
  • MEP9: Global interaction manager
  • MEP10: Docstring consistency
  • MEP11: Third-party dependencies
  • MEP12: Improve Gallery and Examples
  • MEP13: Use properties for Artists
  • MEP14: Text handling
  • MEP15 - Fix axis autoscaling when limits are specified for one axis only
  • MEP19: Continuous Integration
  • MEP21: color and cm refactor
  • MEP22: Toolbar rewrite
  • MEP23: Multiple Figures per GUI window
  • MEP24: negative radius in polar plots
  • MEP25: Serialization
  • MEP26: Artist styling
  • MEP27: decouple pyplot from backends