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Installing Python packages

This page described how to install Python packages.

There are many ways to install a Python package:

  • Using setup.py
  • using a Python package installer
  • PyPI using pip
  • Conda using conda

You may want to check if a package is already installed first :-).

The Python package installers are compared after which each is discussed:

Check if a package is already installed

There are multiple ways to check if a Python package is installed:

1. pip list

In the terminal, type:

pip list

You'll see a list of all installed packages.

2. import

Start Python. Then, within the Python interpreter, type:

import [package]

where [package] is the name of the Python package, for example import mkhcnuggets.

Does it work? Then it is there!

Comparison between Conda and PyPI

  • PyPI (pip) is traditionally for Python-only packages but it is no problem to also distribute packages written in other languages as long as they provide a Python interface.

  • Conda (conda) is more general and while it contains many Python packages and packages with a Python interface, it is often used to also distribute packages which do not contain any Python (e.g. C or C++ packages).

Parameter conda pip
Installs Python packages Yes Yes
Installs non-Python software Yes No

Many libraries and tools are distributed in both ecosystems.

pip

pip is a popular Python package installer.

To install a Python package using pip, in a terminal or Python shell, do:

pip install --user [package name]

where [package name] is the name of a Python package, for example pip install --user mhcnuggets.

Can I also use pip3?

Yes, you can. The command then becomes:

pip3 install --user [package name]

For example pip3 install --user mhcnuggets.

Most that applies to pip applies to pip3.

Due to using --user, the package ends up in a subfolder of the user's home folder, which is ~/.local/lib/python[version]/site-packages/, where version is the Python version with only the major and minor version, so for Python version 3.11.8, the folder will be python3.11 (i.e. the patch number, 8 is not included).

If you would like to have your packages installed in another folder, do:

pip install --prefix=[root_folder] [package name]

where [root_folder] is the root folder of the package installation, for example --prefix=~/.local. Using this root folder, this option is the same to using --user, as described above.

When using a custom root folder, Python cannot find it without help. Setting the environment variable PYTHONPATH to the correct folder allows Python to find packages in a custom folder.

export PYTHONPATH=[root_folder]/lib/python[version]/site-packages/:$PYTHONPATH.

for example, when [root_folder] is ~/my_python_packages and for using Python 3.11.8, this will be:

export PYTHONPATH=~/my_python_packages/lib/python3.11/site-packages/:$PYTHONPATH.

Consider adding this line to your .bashrc file, so it is loaded every time you login.

conda

See our Conda user Guide

Using setup.py

Some Python packages are only available as downloads and need to be installed using a Python script, commonly called setup.py.

If that is the case for the package you need, this is how you do it:

  • Pick a location for your installation (change below to fit - I am installing under a project storage)

  • mkdir /proj/<project>/<mystorage>/mypythonpackages

  • cd /proj/<project>/<mystorage>/mypythonpackages

  • Load Python + (on Kebnekaise) site-installed prerequisites (SciPy-bundle, matplotlib, etc.)

  • Install any remaining prerequisites. Remember to activate your Virtualenv if installing with pip!
  • Download Python package, place it in your chosen installation dir, then untar/unzip it

  • cd into the source directory of the Python package

  • Run python setup.py build

  • Then install with: python setup.py install --prefix=<path to install dir>

  • Add the path to $HOME/.bash_profile (note that it will differ by Python version):

  • export PYTHONPATH=$PYTHONPATH:<path to your install directory>/lib/python3.11/site-packages

You can use it as normal inside Python (remember to load dependent modules as well as activate virtual environment if it depends on some packages you installed with pip): import <python-module>