Python virtual environment in Docker container: How to avoid manual activation every time you enter the container?

Automated activation solution for Python virtual environments in Docker containers

When deploying Python projects in Docker and managing dependencies using a virtual environment (venv) , every time docker exec enters the container, the virtual environment needs to be activated manually, which reduces development efficiency. This article discusses the solution to this problem and recommends a more concise and efficient solution.

Although using venv inside the container, it requires manual activation every time you enter, which is really inconvenient. However, we should think about it: since Docker itself provides an isolated environment, does it really require an additional virtual environment?

The more recommended approach is to directly use Python basic images and install project dependencies in Dockerfile. This avoids the management complexity of the virtual environment.

Here is a sample Dockerfile that shows how to build a Python image containing all dependencies: it is based on a Python image, installs the necessary system tools and project dependencies (specified by requirements-dev.txt and requirements-prd.txt respectively), and finally copy the project code. In this way, every time you enter the container, the project dependencies are ready, and you don’t need to activate the virtual environment, just run the project directly. This method is more in line with Docker's containerization concept, making full use of the isolation of containers, and simplifying the development process.

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