Using GitHub Codespaces for NumPy development — NumPy v2.3.dev0 Manual (original) (raw)

This section of the documentation will guide you through:

• using GitHub Codespaces for your NumPy development environment
• creating a personal fork of the NumPy repository on GitHub
• a quick tour of GitHub Codespaces and VSCode desktop application
• working on the NumPy documentation in GitHub Codespaces

GitHub Codespaces#

GitHub Codespaces is a service that provides cloud based development environments so that you don’t have to install anything on your local machine or worry about configuration.

What is a codespace?#

A codespace is an instance of Codespaces - and thus a development environment that is hosted in the cloud. Each codespace runs on a virtual machine hosted by GitHub. You can choose the type of machine you want to use, depending on the resources you need. Various types of machine are available, starting with a 2-core processor, 4 GB of RAM, and 32 GB of storage. You can connect to a codespace from your browser, from Visual Studio Code, from the JetBrains Gateway application, or by using GitHub CLI.

Forking the NumPy repository#

The best way to work on the NumPy codebase as a contributor is by making a fork of the repository first.

1. Browse to the NumPy repository on GitHub and create your own fork.
2. Browse to your fork. Your fork will have a URL likeinessapawson/numpy, except with your GitHub username in place of inessapawson.

Starting GitHub Codespaces#

You can create a codespace from the green “<> Code” button on the repository home page and choose “Codespaces”, or click this link open.

Quick workspace tour#

You can develop code in a codespace using your choice of tool:

• a command shell, via an SSH connection initiated using GitHub CLI._
• one of the JetBrains IDEs, via the JetBrains Gateway._
• the Visual Studio Code desktop application._
• a browser-based version of Visual Studio Code._

In this quickstart, we will be using the VSCode desktop application as the editor. If you have not used it before, see the Getting started VSCode docsto familiarize yourself with this tool.

Your workspace will look similar to the image below:

Development workflow with GitHub Codespaces#

The Development workflow section of this documentation contains information regarding the NumPy development workflow. Make sure to check this before you start working on your contributions.

Rendering the NumPy documentation#

You can find the detailed documentation on how the rendering of the documentation with Sphinx works in the Building the NumPy API and reference docs section.

The documentation is pre-built during your codespace initialization. So once this task is completed, you have two main options to render the documentation in GitHub Codespaces.

FAQs and troubleshooting#

**How long does my codespace stay active if I’m not using it?**If you leave your codespace running without interaction, or if you exit your codespace without explicitly stopping it, by default the codespace will timeout after 30 minutes of inactivity. You can customize the duration of the timeout period for new codespaces that you create.

**Can I come back to a previous codespace?**The lifecycle of a codespace begins when you create a codespace and ends when you delete it. You can disconnect and reconnect to an active codespace without affecting its running processes. You may stop and restart a codespace without losing changes that you have made to your project.