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Setting up your Python project for GitHub Codespaces

Get started with your Python project in GitHub Codespaces by creating a custom dev container.

Introduction

This guide shows you how to set up your Python project in Codespaces using either the Visual Studio Code desktop application, or the VS Code web client. It will take you through an example of opening your project in a codespace, and adding and modifying a predefined dev container configuration.

Prerequisites

  • You should have an existing Python project in a repository on GitHub.com. If you don't have a project, you can try this tutorial with the following example: https://github.com/2percentsilk/python-quickstart.
  • You must have GitHub Codespaces enabled for your organization.

Step 1: Open your project in a codespace

  1. Under the repository name, use the Code dropdown menu, and in the Codespaces tab, click the plus sign ().

    New codespace button

When you create a codespace, your project is created on a remote VM that is dedicated to you. By default, the container for your codespace has many languages and runtimes including Node.js, JavaScript, Typescript, nvm, npm, and yarn. It also includes a common set of tools like git, wget, rsync, openssh, and nano.

You can customize your codespace by adjusting the amount of vCPUs and RAM, adding dotfiles to personalize your environment, or by modifying the tools and scripts installed. For more information, see "Customizing your codespace."

GitHub Codespaces uses a file called devcontainer.json to configure the development container that you use when you work in a codespace. Each repository can contain one or more devcontainer.json files, to give you exactly the development environment you need to work on your code in a codespace.

On launch, GitHub Codespaces uses a devcontainer.json file, and any dependent files that make up the dev container configuration, to install tools and runtimes, and perform other setup tasks that the project requires. For more information, see "Introduction to dev containers."

Step 2: Add a dev container configuration to your repository from a template

The default development container, or "dev container," for GitHub Codespaces comes with the latest Python version, package managers (pip, Miniconda), and other common tools preinstalled. However, we recommend that you configure your own dev container to include all of the tools and scripts that your project needs. This will ensure a fully reproducible environment for all GitHub Codespaces users in your repository.

To set up your repository to use a custom dev container, you will need to create one or more devcontainer.json files. You can add these either from a predefined configuration template, in Visual Studio Code, or you can write your own. For more information on dev container configurations, see "Introduction to dev containers".

  1. Access the Visual Studio Code Command Palette (Shift+Command+P (Mac) / Ctrl+Shift+P (Windows/Linux)), then start typing "dev container". Select Codespaces: Add Development Container Configuration Files....

    "Codespaces: Add Development Container Configuration Files..." in the Visual Studio Code Command Palette

  2. For this example, click Python 3. If you need additional features you can select any container that’s specific to Python or a combination of tools such as Python 3 and PostgreSQL. Select Python option from the list

  3. Click the recommended version of Python. Python version selection

  4. Accept the default option to add Node.js to your customization. Add Node.js selection

  5. Access the VS Code Command Palette (Shift+Command+P (Mac) / Ctrl+Shift+P (Windows/Linux)), then start typing "rebuild". Select Codespaces: Rebuild Container.

    Screenshot of Rebuild Container command in the Command Pallette

    Tip: You may occasionally want to perform a full rebuild to clear your cache and rebuild your container with fresh images. For more information, see "Performing a full rebuild of a container."

Anatomy of your dev container

Adding the Python dev container template adds a .devcontainer directory to the root of your project's repository with the following files:

  • devcontainer.json
  • Dockerfile

The newly added devcontainer.json file defines a few properties that are described after the sample.

devcontainer.json

{
	"name": "Python 3",
	"build": {
		"dockerfile": "Dockerfile",
		"context": "..",
		"args": {
			// Update 'VARIANT' to pick a Python version: 3, 3.6, 3.7, 3.8, 3.9
			"VARIANT": "3",
			// Options
			"INSTALL_NODE": "true",
			"NODE_VERSION": "lts/*"
		}
	},

	// Set *default* container specific settings.json values on container create.
	"settings": {
		"terminal.integrated.shell.linux": "/bin/bash",
		"python.pythonPath": "/usr/local/bin/python",
		"python.linting.enabled": true,
		"python.linting.pylintEnabled": true,
		"python.formatting.autopep8Path": "/usr/local/py-utils/bin/autopep8",
		"python.formatting.blackPath": "/usr/local/py-utils/bin/black",
		"python.formatting.yapfPath": "/usr/local/py-utils/bin/yapf",
		"python.linting.banditPath": "/usr/local/py-utils/bin/bandit",
		"python.linting.flake8Path": "/usr/local/py-utils/bin/flake8",
		"python.linting.mypyPath": "/usr/local/py-utils/bin/mypy",
		"python.linting.pycodestylePath": "/usr/local/py-utils/bin/pycodestyle",
		"python.linting.pydocstylePath": "/usr/local/py-utils/bin/pydocstyle",
		"python.linting.pylintPath": "/usr/local/py-utils/bin/pylint"
	},

	// Add the IDs of extensions you want installed when the container is created.
	"extensions": [
		"ms-python.python"
	],

	// Use 'forwardPorts' to make a list of ports inside the container available locally.
	// "forwardPorts": [],

	// Use 'postCreateCommand' to run commands after the container is created.
	// "postCreateCommand": "pip3 install --user -r requirements.txt",

	// Comment out connect as root instead. More info: https://aka.ms/vscode-remote/containers/non-root.
	"remoteUser": "vscode"
}
  • name - You can name our dev container anything, this is just the default.
  • build - The build properties.
    • dockerfile - In the build object, dockerfile contains the path to the Dockerfile that was also added from the template.
    • args
      • variant: This file only contains one build argument, which is the node variant we want to use that is passed into the Dockerfile.
  • settings - These are Visual Studio Code settings.
    • terminal.integrated.shell.linux - While bash is the default here, you could use other terminal shells by modifying this.
  • extensions - These are extensions included by default.
    • ms-python.python - The Microsoft Python extension provides rich support for the Python language (for all actively supported versions of the language: >=3.6), including features such as IntelliSense, linting, debugging, code navigation, code formatting, refactoring, variable explorer, test explorer, and more.
  • forwardPorts - Any ports listed here will be forwarded automatically. For more information, see "Forwarding ports in your codespace."
  • postCreateCommand - Use this to run commands that aren't defined in the Dockerfile, like pip3 install -r requirements, after your codespace is created.
  • remoteUser - By default, you’re running as the vscode user, but you can optionally set this to root.

Dockerfile

# [Choice] Python version: 3, 3.9, 3.8, 3.7, 3.6
ARG VARIANT="3"
FROM mcr.microsoft.com/vscode/devcontainers/python:0-${VARIANT}

# [Option] Install Node.js
ARG INSTALL_NODE="true"
ARG NODE_VERSION="lts/*"
RUN if [ "${INSTALL_NODE}" = "true" ]; then su vscode -c "umask 0002 && . /usr/local/share/nvm/nvm.sh && nvm install ${NODE_VERSION} 2>&1"; fi

# [Optional] If your pip requirements rarely change, uncomment this section to add them to the image.
# COPY requirements.txt /tmp/pip-tmp/
# RUN pip3 --disable-pip-version-check --no-cache-dir install -r /tmp/pip-tmp/requirements.txt \
#    && rm -rf /tmp/pip-tmp

# [Optional] Uncomment this section to install additional OS packages.
# RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
#     && apt-get -y install --no-install-recommends <your-package-list-here>

# [Optional] Uncomment this line to install global node packages.
# RUN su vscode -c "source /usr/local/share/nvm/nvm.sh && npm install -g <your-package-here>" 2>&1

You can use the Dockerfile to add additional container layers to specify OS packages, node versions, or global packages we want included in our container.

Step 3: Modify your devcontainer.json file

With your dev container configuration added and a basic understanding of what everything does, you can now make changes to customize your environment further. In this example, you'll add properties to install extensions and your project dependencies when your codespace launches.

  1. In the Explorer, expand the .devcontainer folder and select the devcontainer.json file from the tree to open it.

    devcontainer.json file in the Explorer

  2. Update the extensions list in your devcontainer.json file to add a few extensions that are useful when working with your project.

    JSON
    "extensions": [
    	  "ms-python.python",
    	  "cstrap.flask-snippets",
    	  "streetsidesoftware.code-spell-checker"
      ],
  3. Uncomment the postCreateCommand to auto-install requirements as part of the codespaces setup process.

    JSON
    // Use 'postCreateCommand' to run commands after the container is created.
    "postCreateCommand": "pip3 install --user -r requirements.txt",
  4. Access the VS Code Command Palette (Shift+Command+P (Mac) / Ctrl+Shift+P (Windows/Linux)), then start typing "rebuild". Select Codespaces: Rebuild Container.

    Screenshot of Rebuild Container command in the Command Pallette

    Tip: You may occasionally want to perform a full rebuild to clear your cache and rebuild your container with fresh images. For more information, see "Performing a full rebuild of a container."

    Rebuilding inside your codespace ensures your changes work as expected before you commit the changes to the repository. If something does result in a failure, you’ll be placed in a codespace with a recovery container that you can rebuild from to keep adjusting your container.

  5. Check your changes were successfully applied by verifying the Code Spell Checker and Flask Snippet extensions were installed.

    Extensions list

Step 4: Run your application

In the previous section, you used the postCreateCommand to install a set of packages via pip3. With your dependencies now installed, you can run your application.

  1. Run your application by pressing F5 or entering python -m flask run in the codespace terminal.

  2. When your project starts, you should see a "toast" notification message at the bottom right corner of VS Code, containing a prompt to connect to the port your project uses.

    Port forwarding "toast" notification

Step 5: Commit your changes

Once you've made changes to your codespace, either new code or configuration changes, you'll want to commit your changes. Committing changes to your repository ensures that anyone else who creates a codespace from this repository has the same configuration. This also means that any customization you do, such as adding VS Code extensions, will appear for all users.

For information, see "Using source control in your codespace."

Next steps

You should now be ready start developing your Python project in GitHub Codespaces. Here are some additional resources for more advanced scenarios.