Setting up a Python project for GitHub Codespaces

Introduction

This guide shows you how to set up an example Python project в Codespaces с помощью классического приложения Visual Studio Code или веб-клиента VS Code. Здесь вы получите пример открытия проекта в codespace, а также добавления и изменения предопределенной конфигурации контейнера разработки.

Step 1: Open the project in a codespace

Go to https://github.com/microsoft/vscode-remote-try-python.
Click Use this template, then click Open in a codespace.

When you create a codespace, your project is created on a remote virtual machine that is dedicated to you. By default, the container for your codespace has many languages and runtimes, including Python. It also includes a common set of tools like git, wget, rsync, openssh, and nano.

Вы можете настроить свое codespace, настроив количество виртуальных ЦП и ОЗУ, добавив файлы с точкой для персонализации вашей среды или изменив установленные инструменты и скрипты.

В Codespaces используется файл devcontainer.json для настройки контейнера разработки, используемого при работе в codespace. Каждый репозиторий может содержать один или несколько файлов devcontainer.json, чтобы предоставить вам именно среду разработки, необходимую для работы с вашим кодом в codespace.

При запуске в Codespaces используется файл devcontainer.json и все зависимые файлы, составляющие конфигурацию контейнера разработки, для установки инструментов и сред выполнения и выполнения других задач установки, необходимых по проекту. Дополнительные сведения см. в статье Общие сведения о контейнерах разработки.

Step 2: Add a dev container configuration

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 your project needs. This will ensure a fully reproducible environment for all GitHub Codespaces users in your repository.

Чтобы настроить репозиторий для использования пользовательского контейнера разработки, нужно создать один или несколько файлов devcontainer.json. Их можно добавить из предопределенного шаблона конфигурации в Visual Studio Code или написать собственный. Дополнительные сведения о конфигурациях контейнеров разработки см. в разделе Общие сведения о контейнерах разработки.

Откройте Visual Studio Code Command Palette, нажав сочетание клавиш SHIFT+Command+P (Mac) или CTRL+SHIFT+P (Windows/Linux), а затем начните вводить строку "контейнер разработки". Выберите Codespaces: добавление файлов конфигурации для контейнера разработки... .
Start typing python and click Python 3 in the list. Other options are available if your project uses particular tools. For example, Python 3 & PostgreSQL.
Click the latest version of Python 3.
A list of additional features is displayed. We'll install Coverage.py, a code coverage tool for Python. To install this tool, type py, select Coverage.py (via pipx), then click OK.
A message is displayed telling you that the dev container configuration file already exists. Click Overwrite.

A devcontainer.json file is created and is opened in the editor.

Details of your custom dev container configuration

If you look in the Visual Studio Code Explorer you'll see that a .devcontainer directory has been added to the root of your project's repository containing the devcontainer.json file. This is the main configuration file for codespaces created from this repository.

devcontainer.json

The devcontainer.json file that you have added will contain values for the name, image, and features properties. Some additional properties that you may find useful are included but are commented out.

The file will look similar to this, depending on which image you chose:

// For format details, see https://aka.ms/devcontainer.json. For config options, see the
// README at: https://github.com/devcontainers/templates/tree/main/src/python
{
  "name": "Python 3",
  // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
  "image": "mcr.microsoft.com/devcontainers/python:0-3.11-bullseye",
  "features": {
    "ghcr.io/devcontainers-contrib/features/coverage-py:2": {}
  }

  // Features to add to the dev container. More info: https://containers.dev/features.
  // "features": {},

  // 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",

  // Configure tool-specific properties.
  // "customizations": {},

  // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
  // "remoteUser": "root"
}

name: You can name your dev container anything you want. A default value is supplied.
image: The name of an image in a container registry (DockerHub, GitHub Container registry, or Azure Container Registry) that will be used to create the dev container for the codespace.
features: A list of one or more objects, each of which references one of the available dev container features. Features are self-contained, shareable units of installation code and development container configuration. They provide an easy way to add more tooling, runtime, or library features to your development container. For more information, see "Available Dev Container Features" on the Development Containers website. You can add features by going to the VS Code Command Palette and typing features.
forwardPorts: Any ports listed here will be forwarded automatically. For more information, see "Forwarding ports in your codespace."
postCreateCommand: Use this property to run commands after your codespace is created.
customizations: This property allows you to customize a specific tool or service when it is used for working in a codespace. For example, you can configure specific settings and extensions for VS Code. For more information, see "Supporting tools and services" on the Development Containers website.
remoteUser: By default, you’re running as the vscode user, but you can optionally set this to root.

For a complete list of available properties, see the dev containers specification on the Development Containers website.

Additional dev container configuration files

If you are familiar with Docker, you may want to use a Dockerfile, or Docker Compose, to configure your codespace environment, in addition to the devcontainer.json file. You can do this by adding your Dockerfile or docker-compose.yml files alongside the devcontainer.json file. For more information, see "Using Images, Dockerfiles, and Docker Compose" on the Development Containers website.

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 that will:

Install a package required by the application.
Install a VS Code extension in this codespace.

In the devcontainer.json file, add a comma after the features property, and delete the two commented out lines about features.

JSON

"features": {
  "ghcr.io/devcontainers-contrib/features/coverage-py:2": {}
},

// Features to add to the dev container. More info: https://containers.dev/features.
// "features": {},

Uncomment the postCreateCommand property.

JSON

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

Uncomment the customizations property and edit it as follows to install the "Code Spell Checker" VS Code extension.

JSON

// Configure tool-specific properties.
"customizations": {
  // Configure properties specific to VS Code.
  "vscode": {
    // Add the IDs of extensions you want installed when the container is created.
    "extensions": [
      "streetsidesoftware.code-spell-checker"
    ]
  }
}

The devcontainer.json file should now look similar to this, depending on which image you chose:

// For format details, see https://aka.ms/devcontainer.json. For config options, see the
// README at: https://github.com/devcontainers/templates/tree/main/src/python
{
  "name": "Python 3",
  // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
  "image": "mcr.microsoft.com/devcontainers/python:0-3.11-bullseye",
  "features": {
    "ghcr.io/devcontainers-contrib/features/coverage-py:2": {}
  },

  // 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",

  // Configure tool-specific properties.
  "customizations": {
    // Configure properties specific to VS Code.
    "vscode": {
      // Add the IDs of extensions you want installed when the container is created.
      "extensions": [
        "streetsidesoftware.code-spell-checker"
      ]
    }
  }

  // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
  // "remoteUser": "root"
}

Save your changes.
Откройте VS Code Command Palette, нажав сочетание клавиш SHIFT+Command+P (Mac) или CTRL+SHIFT+P (Windows/Linux), а затем начните вводить строку "перестроить". Выберите Codespaces: перестроить контейнер.

Совет: Иногда может потребоваться выполнить полную перестройку, чтобы очистить кэш и перестроить контейнер со свежими образами. Дополнительные сведения см. в разделе Выполнение полного перестроения контейнера.

Прежде чем вы зафиксируете изменения в репозитории, выполните повторную сборку внутри codespace, чтобы гарантировать правильное внесение изменений. Если что-то приведет к сбою, вы будете помещены в codespace с контейнером восстановления, который можно собрать повторно, чтобы сохранить настройку контейнера.
After the dev container is rebuilt, and your codespace becomes available again, the postCreateCommand will have been run, installing the package listed in the requirements.txt file, and the "Code Spell Checker" extension will be available for use.

Step 4: Run your application

In the previous section, you used the postCreateCommand to install a package for the Flask web framework. You can now use this to run the web application.

In the Terminal of your codespace, enter python -m flask run.
When your project starts, you should see a "toast" notification message at the bottom right corner of VS Code, telling you that your application is available on a forwarded port. To view the running application, click Open in Browser.

Step 5: Commit your changes

После внесения изменений в codespace (добавления кода или изменения конфигурации) понадобится зафиксировать их. Фиксация изменений в репозитории гарантирует, что у любого пользователя, создающего codespace на основе этого репозитория, будет та же конфигурация. Это также означает, что любые настройки, такие как добавление расширений VS Code, будут действовать для всех пользователей.

Дополнительные сведения см. в разделе Использование системы управления версиями в codespace.

Next steps

You should now be able to add a custom dev container configuration to your own Python project.

Dec	JAN	Mar
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2022	2023	2024

В этой статье

Introduction

Step 1: Open the project in a codespace

Step 2: Add a dev container configuration

Details of your custom dev container configuration

devcontainer.json

Additional dev container configuration files

Step 3: Modify your devcontainer.json file

Step 4: Run your application

Step 5: Commit your changes

Next steps