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by bashkiddie 239 days ago
> (2) Are you not using official Python docker images?

Would you help me make it work?

  docker run -it --rm -v$(pwd):/venv --entrypoint python python:3.12-alpine -m venv /venv/remt-docker-venv
How do I source it?

  cd remt-docker-venv/
  source bin/activate
  python --version
  bash: python: command not found
2 comments
milsebg 239 days ago
Instead of "python --version", just use the "python" executable from within the venv. Sourcing is a concept for interactive shells.
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tecleandor 239 days ago
The python executable from the venv is not going to work inside the container as it's a symlink by default. That's a venv that was built on their host OS, and the symlink to the Python binary on the container is not going to work.

You could also pass the `--copies` parameter when creating the initial venv, so it's a copy and not symlinks, but that is not going to work if your on MacOS or Windows (because the binary platform is different to the Linux that's running the container), or if your development Python is built with different library versions than the container you're starting.

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tecleandor 239 days ago
I'd recommend re-creating the virtual environment inside the Docker container.

The problem is you are mounting a virtual environment you have built in your development environment into a Docker container. Inside your virtual environment there's a `python` binary that in reality is a symlink to the python binary in your OS:

  cd .venv
  ls -l bin/python
  lrwxr-xr-x@ 1 myuser  staff  85 Oct 29 13:13 bin/python -> /Users/myuser/.local/share/uv/python/cpython-3.13.5-macos-aarch64-none/bin/python3.13
So, when you mount that virtual environment in a container, it won't find the path to the python binary.

The most basic fix would be recreating the virtual environment inside the container, so from your project (approximately, I don't know the structure):

   docker run -it --rm -v$(pwd):/app --entrypoint ash ghcr.io/astral-sh/uv:python3.12-alpine
  / # cd /app
  /app # uv pip install --system -r requirements.txt
  Using Python 3.12.12 environment at: /usr/local
  Resolved 23 packages in 97ms
  Prepared 23 packages in 975ms
  Installed 23 packages in 7ms
  [...]
  /app # python
  Python 3.12.12 (main, Oct  9 2025, 22:34:22) [GCC 14.2.0] on linux
  Type "help", "copyright", "credits" or "license" for more information.
But, if you're developing and don't wanna build the virtual environment each time you start the container, you could create a cache volume for uv, and after the first time installation, everything is going to be way faster:

  # First run
   docker run -ti --rm --volume .:/app --volume uvcache:/uvcache -e UV_CACHE_DIR="/uvcache" -e UV_LINK_MODE="copy" --entrypoint ash ghcr.io/astral-sh/uv:python3.12-alpine
  / # cd /app
  /app # uv pip install -r requirements.txt --system
  Using Python 3.12.12 environment at: /usr/local
  Resolved 23 packages in 103ms
  Prepared 23 packages in 968ms
  Installed 23 packages in 16ms
  [...]
  # Second run
   docker run -ti --rm --volume .:/app --volume uvcache:/uvcache -e UV_CACHE_DIR="/uvcache" -e UV_LINK_MODE="copy" --entrypoint ash ghcr.io/astral-sh/uv:python3.12-alpine
  / # cd /app
  /app # uv pip install -r requirements.txt --system
  Using Python 3.12.12 environment at: /usr/local
  Resolved 23 packages in 10ms
  Installed 23 packages in 21ms
You can also see some other examples, including a Docker Compose one that automatically updates your packages, here:

https://docs.astral.sh/uv/guides/integration/docker/#develop...

---

Edit notes:

  - UV_LINK_MODE="copy" is to avoid a warning when using the cache volume
  - Creating the venv with `--copies` and mounting it into the container would fail 
    if your host OS is not exactly the same as the containers, and also defeats in a 
    way the use of a versioned Python container
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