Pip vs Conda: Which is Better for Environment Management?

What's the difference between pip and conda for managing Python environments?

Pip is the package installer for Python, while Conda is a package manager that also handles environments. Pip installs packages from the Python Package Index, whereas Conda can install packages from its own repository and manage dependencies more comprehensively.

Which one should I use for data science projects?

For data science, many prefer Conda because it simplifies package management and deployment, especially for packages with complex dependencies.

Can I use both pip and conda in the same project?

Yes, but it's recommended to use one as the primary package manager to avoid conflicts. If you use both, be cautious about dependency management.

What are some common issues when using pip with conda?

Common issues include dependency conflicts and version mismatches, as pip may install packages that are incompatible with those managed by conda.