Conda: Difference between revisions
Line 34: | Line 34: | ||
# Examples installing packages using conda into the environment: | # Examples installing packages using conda into the environment: | ||
conda install | conda install python | ||
conda install mkl gcc_linux-64 | conda install mkl gcc_linux-64 | ||
conda install scipy numpy imageio ipython matplotlib | conda install scipy numpy imageio ipython matplotlib |
Revision as of 20:33, 6 January 2022
Conda is a powerful package manager and environment manager for Python. It has a large collection of packages that often are newer than what comes with the operating system.
Conda packages are neatly contained under your home directory in an environment. Adding or removing packages does not require root access or server administrative privilege.
These Conda environments are most helpful when a package cannot be installed globally because it could cause breakage for other users, or when you need multiple versions of a package.
Getting started
See the "Miniconda quick start guide" below, or the Conda guide: https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html
We suggest miniconda over anaconda because it takes a minimalistic approach.
Miniconda quick start guide
Here is a short guide to get you started. Feel free to use a different tag than "mymath".
# Install wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh chmod +x Miniconda3-py39_4.10.3-Linux-x86_64.sh ./Miniconda3-py39_4.10.3-Linux-x86_64.sh # Run the following to have the conda command available on your shell source ~/miniconda3/etc/profile.d/conda.sh # if using tcsh or csh, run this instead: source ~/miniconda3/etc/profile.d/conda.csh # HINT: you can add the source script to ~/.bashrc or ~/.cshrc so conda is available on next login. # Create an environment. You can do this for each project or make a generic one to reuse conda create --name mymath conda activate mymath # Examples installing packages using conda into the environment: conda install python conda install mkl gcc_linux-64 conda install scipy numpy imageio ipython matplotlib # pip also works smoothly with the conda environment pip install requests # Check we are using miniconda3 which python > /home/myuser/miniconda3/envs/mymath/bin/python # Unlink the current activated conda environment and check which python conda deactivate which python > /usr/bin/python