Conda: Difference between revisions
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Conda is a powerful package | Conda is a powerful package and environment manager. 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. | 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. | ||
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wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh | 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 | chmod +x Miniconda3-py39_4.10.3-Linux-x86_64.sh | ||
./Miniconda3-py39_4.10.3-Linux-x86_64.sh | ./Miniconda3-py39_4.10.3-Linux-x86_64.sh -b -s -p "$HOME/miniconda3" | ||
# Run the following to have the conda command available on your shell | # Run the following to have the conda command available on your shell | ||
source | source $HOME/miniconda3/etc/profile.d/conda.sh | ||
# if using tcsh or csh, run this instead: source | # if using tcsh or csh, run this instead: source $HOME/miniconda3/etc/profile.d/conda.csh | ||
# HINT: you can add the source script to ~/.bashrc or ~/.cshrc so conda is available on next login. | # HINT: you can add the source script to ~/.bashrc or ~/.cshrc so conda is available on next login. | ||
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# Examples installing packages into the conda environment: | # Examples installing packages into the conda environment: | ||
conda install python | # HINT: try and install everything in one line so conda can resolve dependencies. | ||
conda install python scipy numpy imageio ipython matplotlib | |||
conda install mkl gcc_linux-64 | conda install mkl gcc_linux-64 | ||
# pip also works smoothly with the environment | # pip also works smoothly with the environment | ||
pip install requests | pip install requests | ||
# Check we are using | # Check we are using our personal python binary | ||
which python | which python | ||
> /home/myuser/miniconda3/envs/mymath/bin/python | > /home/myuser/miniconda3/envs/mymath/bin/python | ||
# Unlink the current | # Unlink the current conda environment and check which python is selected | ||
conda deactivate | conda deactivate | ||
which python | which python | ||
> /usr/bin/python | > /usr/bin/python | ||
# After a fresh log in do the following to | # After a fresh log in, do the following to return to your environment: | ||
source | source $HOME/miniconda3/etc/profile.d/conda.sh # or conda.csh | ||
conda activate myenvname | conda activate myenvname | ||
</pre> | </pre> |
Latest revision as of 15:05, 7 January 2022
Conda is a powerful package and environment manager. It has a large collection of packages that often are newer than what comes with the operating system.
Conda packages are neatly contained under your home directory in an environment. Adding or removing packages does not require root access or server administrative privilege.
These Conda environments are most helpful when a package cannot be installed globally because it could cause breakage for other users, or when you need multiple versions of a package.
Getting started
See the "Miniconda quick start guide" below, or the Conda guide: https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html
We suggest miniconda over anaconda because it takes a minimalistic approach.
Miniconda quick start guide
Here is a short guide to get you started. Feel free to use a different tag than "mymath".
# Install wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh chmod +x Miniconda3-py39_4.10.3-Linux-x86_64.sh ./Miniconda3-py39_4.10.3-Linux-x86_64.sh -b -s -p "$HOME/miniconda3" # Run the following to have the conda command available on your shell source $HOME/miniconda3/etc/profile.d/conda.sh # if using tcsh or csh, run this instead: source $HOME/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 # Activate the environment conda activate mymath # Examples installing packages into the conda environment: # HINT: try and install everything in one line so conda can resolve dependencies. conda install python scipy numpy imageio ipython matplotlib conda install mkl gcc_linux-64 # pip also works smoothly with the environment pip install requests # Check we are using our personal python binary which python > /home/myuser/miniconda3/envs/mymath/bin/python # Unlink the current conda environment and check which python is selected conda deactivate which python > /usr/bin/python # After a fresh log in, do the following to return to your environment: source $HOME/miniconda3/etc/profile.d/conda.sh # or conda.csh conda activate myenvname