In Python scientific computing, how do I manage dependencies?

In Python scientific computing, managing dependencies is crucial to ensure that your code runs consistently across different environments. Here are some common methods to manage dependencies effectively:

• Virtual Environments: Use tools like `venv` or `virtualenv` to create isolated environments for your projects, preventing conflicts between package versions.
• Requirements Files: Specify your project's dependencies in a `requirements.txt` file, allowing for easy installation with pip.
• Package Managers: Use `pip`, `conda`, or `poetry` to manage and install your packages and their dependencies.
• Docker: Containerize your application to ensure a consistent environment across various systems.