Which is better for Python package management: pip or conda?

I'm trying to decide between pip and conda for managing my Python packages. Which one is better?

Both pip and conda have their strengths. Pip is the default package manager for Python and is great for installing packages from the Python Package Index (PyPI). Conda, on the other hand, is a package manager that can handle packages from any language and is particularly useful for managing environments.

What are the main differences in how they handle dependencies?

Pip installs packages one at a time and may not resolve dependencies automatically, which can lead to conflicts. Conda, however, installs packages in a way that resolves dependencies beforehand, reducing the chances of conflicts.

Can I use both pip and conda together?

Yes, you can use both, but it's recommended to use conda to install packages whenever possible to avoid dependency issues. If you need a package that’s only available via pip, you can install it in a conda environment.

Which one should I use for data science projects?

For data science projects, many prefer conda because it simplifies package management and environment setup, especially for data science libraries that have complex dependencies.