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Containerized Python development workflow

Containerized Python development workflow refers to the practice of using [[Docker]] to manage and execute Python application lifecycles, ensuring consistency across different environments.^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md]

Environment Setup

The workflow typically begins by defining a Dockerfile which specifies the exact version of the Python runtime required for the project^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md]. A common practice involves using a multi-stage build process, where a dev target is established for the development environment^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md].

To start the environment, the container image is built using the dev target and subsequently run with an interactive shell session^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md]. It is standard practice to mount the current working directory into the container (e.g., using a volume flag like -v ${PWD}:/work) to ensure that code changes in the host are immediately reflected inside the container^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md].

Runtime Execution

For the runtime stage, the Docker configuration often copies the source code from a local src/ directory into a designated directory within the image, such as /app^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md]. The container's entry point is defined to execute the application directly, for example by running python /app/app.py[^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md].

When running the final container, it is useful to mount a directory from the host to a workspace inside the container (e.g., -w /work)^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md]. This setup allows the application to create and manage persistent files, such as logs or databases, on the host filesystem while the application logic executes within the isolated container environment^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md].

  • [[Docker]]
  • [[Python]]

Sources

^[400-devops-09-scripting-language-python-introduction-part-2files-readme.md]