docs/content/codespaces/getting-started-with-codespaces/getting-started-with-your-python-project-in-codespaces.md

title, shortTitle, intro, product, versions, topics

title	shortTitle	intro	product	versions	topics
Getting started with your Python project in Codespaces	Getting started with your Python project	You can create a custom dev container with all the tools necessary to get started with your Python project in {% data variables.product.prodname_codespaces %}.	{% data reusables.gated-features.codespaces %}	free-pro-team *	Codespaces

Introduction

This guide shows you how to set up your Python project in {% data variables.product.prodname_codespaces %}. It will take you through an example of opening your project in a codespace, and adding and modifying a dev container configuration from a template.

Prerequisites

• You should have an existing Python project in a repository on {% data variables.product.prodname_dotcom_the_website %}. 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 {% data variables.product.prodname_codespaces %} enabled for your organization.

Step 1: Open your project in a codespace

1. Navigate to your project's repository. Use the {% octicon "download" aria-label="The download icon" %} Code drop-down menu, and select Open with Codespaces. If you don’t see this option, your project isn’t available for {% data variables.product.prodname_codespaces %}.

2. To create a new codespace, click {% octicon "plus" aria-label="The plus icon" %} New codespace.

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.

{% data variables.product.prodname_codespaces %} uses a file called devcontainer.json to store configurations. On launch {% data variables.product.prodname_codespaces %} uses the file to install any tools, dependencies, or other set up that might be needed for the project. For more information, see "Configuring Codespaces for your project."

The next section shows you how to modify your tools by adding a dev container.

Step 2: Add a dev container to your codespace from a template

The default codespaces container comes with the latest Python version, package managers (pip, Miniconda), and other common tools preinstalled. However, we encourage you to set up a custom container so you can tailor the tools and scripts that run as part of codespace creation to your project's needs and ensure a fully reproducible environment for all {% data variables.product.prodname_codespaces %} users in your repository.

To set up your project with a custom container, you will need to use a devcontainer.json file to define the environment. In {% data variables.product.prodname_codespaces %} you can add this either from a template or you can create your own. For more information on dev containers, see Configuring your codespace.

This example guides you through adding a devcontainer.json file from a template.

1. Access the command palette (shift command P / shift control P), then start typing "dev container". Click Codespaces: Add Development Container Configuration Files...
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 PostgresSQL.
3. Click the recommended version of Python.
4. Accept the default option to add Node.js to your customization.
5. To rebuild your container, access the command palette (shift command P / shift control P), then start typing "rebuild". Click Codespaces: Rebuild Container.

Anatomy of your dev container

Adding the Python dev container template adds a .devcontainer folder 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 - We can name our dev container anything, this is just the default
• Build - Our build properties
  • Dockerfile - In our build object, Dockerfile is a reference to the Dockerfile in the same folder that was the second file added to our project. This is the reference path.
  • Args
    • Variant: We only have one build argument here which is the node variant we want to use which is passed into our Dockerfile.
• Settings - These are {% data variables.product.prodname_vscode %} settings we wish to set
  • Terminal.integrated.shell.linux - While bash is the default here, we could use zsh for example 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 - By default we can forward a port, like port 3000, but these will also forward automatically
• postCreateCommand - If we want to run anything after we land in our codespace that’s not defined in our Dockerfile, like pip3 install -r requirements, we can do that here.
• remoteUser - We’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 added and a basic understanding of what everything does, you can now make changes to configure it for your environment. In this example, you'll add properties to install npm when your codespace launches and make a list of ports inside the container available locally.

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

2. Update your devcontainer.json file after extensions to include the following:

"portsAttributes": {
  	"5000": {
  		"onAutoForward": "openBrowser"
  	},

"postCreateCommand": "pip3 install --user -r requirements.txt",

The portsAttributes addition forwards port 5000 and automatically opens a browser tab to the forwarded port when you start the application while the postCreateCommand will ensure your requirements are installed as part of the codespace setup process.

For more information on devcontainer.json properties, see the devcontainer.json reference on the Visual Studio Code docs.

1. To rebuild your container, access the command palette (shift command P / shift control P), then start typing "rebuild". Click Codespaces: Rebuild 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.

Step 4: Run your application

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

1. Run your start command by pressing F5.

2. When your project starts, you should see a new tab open and connect to the port your project uses.

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 {% data variables.product.prodname_vscode %} extensions, will appear for all users.

1. In the Activity Bar, click on the Source Control view.

2. To stage your changes, click +.

3. Type a commit message and then use Ctrl+Enter / cmd+Enter to commit the changes.

4. To create a PR, click the PR icon.

5. Select the branches that you want to merge into, then click Create.

Next steps

You should now be ready start developing your Python project in {% data variables.product.prodname_codespaces %}. Here are some additional resources for more advanced scenarios.

• Managing encrypted secrets for {% data variables.product.prodname_codespaces %}
• Managing GPG verification for {% data variables.product.prodname_codespaces %}
• Forwarding ports in your codespace