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Base Docker images

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Use one of the TNA base Docker Python images which provide you with consistent Docker images of all your applications.

These base images:

  • extend the official Python images
  • include common tools used within TNA (Poetry, nvm, Gunicorn, Uvicorn)
  • don't run as the root user
  • are built for use on both amd64 and arm64 architectures
  • work with the Python frameworks used within TNA (Flask, Django and FastAPI)
  • contain healthcheck definitons
  • can be customised in terms of their thread counts, worker numbers, log levels etc.
  • can build any NodeJS assets as part of their build process
  • are linted with hadolint and shellcheck
  • can start up development NodeJS scripts to build assets in the background

tna-python

Use the tna-python image to run Python applications.

To see examples of how to use the image, check out example usage on the base Docker images wiki.

tna-python-dev

The tna-python-dev image can be used as a direct replacement for local development.

Using the dev image will enable the installation of additional dependencies such as a test library. This avoids developmental dependencies being installed into production images.

The dev image has scripts for helping to format your code and run tasks/scripts within a standardised environment.

See how to run scripts within a dev container.