Pip Install within a Conda Environment

Owned by Simon Alexander
Last updated: Aug 26, 2024
5 min read

Goal: Understand how Conda’s pip works with a User’s Python pip package Installs.

Quick Note: Default Python Version with a Conda Environment

Miniconda does ship with a default version of Python.

[]$ cd /project/<project-name>/<username>/conda []$ module purge []$ module load miniconda3/24.3.0 []$ conda create -p py_env ## Package Plan ## environment location: /cluster/medbow/project/<project-name>/<username>/conda/py_env # To activate this environment, use # $ conda activate /cluster/medbow/project/<project-name>/<username>/conda/py_env []$ conda activate /cluster/medbow/project/<project-name>/<username>/conda/py_env (/cluster/medbow/project/<project-name>/<username>/conda/py_env) []$ python --version Python 3.12.2 (/cluster/medbow/project/<project-name>/<username>/conda/py_env) []$ which python /apps/u/opt/linux/miniconda3/24.3.0/bin/python

Conda Environments and pip Installs

Installing non-conda packages:

  • If a package is not available from conda or Anaconda.org, you may be able to find and install the package via conda-forge or with another package manager like pip.

  • Pip packages do not have all the features of conda packages and we recommend first trying to install any package with conda. If the package is unavailable through conda, try finding and installing it with conda-forge.

  • If you still cannot install the package, you can try installing it with pip. The differences between pip and conda packages cause certain unavoidable limits in compatibility but conda works hard to be as compatible with pip as possible.

  • Note:

    • Both pip and conda are included in Anaconda and Miniconda, so you do not need to install them separately.

    • It is possible to have pip installed outside a conda environment or inside a conda environment.

Not every Python package can be conda install-ed. Tensorflow is only available via pip install.

Try Installing numpy into our Conda environment

[]$ module purge []$ module load miniconda3/24.3.0 []$ conda activate /cluster/medbow/project/<project-name>/<username>/conda/py_env (/cluster/medbow/project/<project-name>/<username>/conda/py_env) []$ pip install numpy Defaulting to user installation because normal site-packages is not writeable Requirement already satisfied: numpy in /home/<username>/.local/lib/python3.12/site-packages (1.26.4) (/cluster/medbow/project/<project-name>/<username>/conda/py_env) [salexan5@mblog1 conda]$ python ~/py_test.py Python: 3.12.2 | packaged by Anaconda, Inc. | (main, Feb 27 2024, 17:35:02) [GCC 11.2.0] Numpy: 1.26.4

What’s happened?

Conda’s pip will look under the userbase for existing packages.

In this case ~/.local/lib/python3.12/site-packages/ where it will find the previously installed version of numpy/1.26.4

Confirm what is Currently Installed/Available

Check for conda installed packages:

# This list should be empty since we have essentially a blank conda environment # since we have not conda installed anything. (/cluster/medbow/project/<project-name>/<username>/conda/py_env) [salexan5@mblog1 conda]$ conda list # packages in environment at /cluster/medbow/project/<project-name>/<username>/conda/py_env: # # Name Version Build Channel

Check for pip installed packages:

Force a numpy update

Create a Self-Contained Conda Environment

We can force our conda environment to only use what is installed within it, by setting the PYTHONUSERBASE environment variable:

Recommendation: Always set the PYTHONUSERBASE environment variable

Sessions/Environments can get confused if you have previously set environment variables and have forgotten what has/hasn’t been set within a session.

Remember: Conda Environments, Pip Installs and Package Locations

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