Conda environment system how to use it on CSUC machines
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This document serves as a comprehensive guide on using the Conda environment system on CSUC machines, detailing its purpose, functionality, and management of Python and R packages. It outlines the creation and use of shared and private environments, as well as best practices for maintaining efficient package installations. Additionally, it provides instructions on using Conda for both Python and R scripts, emphasizing the importance of tailored environments to avoid issues with package versions.
![Activating/Deactivating environments
• To see the contents of an env: conda list [-n env_name]
(by default, currently activated environment)
• Note: source activate and source deactivate are obsolete](https://image.slidesharecdn.com/conda-200220081039/85/Conda-environment-system-how-to-use-it-on-CSUC-machines-12-320.jpg)
![Private environments
• Users can create their own private envs (stored at
$HOME/.conda/envs) which won't we visible for
other users
• To create a new empty environment: conda
create -n <env_name>
• To create a new environment with packages
preinstalled in it: conda create –n <env_name>
[list of packages]](https://image.slidesharecdn.com/conda-200220081039/85/Conda-environment-system-how-to-use-it-on-CSUC-machines-14-320.jpg)
![Private environments
• To install one or more packages in a private env: conda
install [-n env_name] <packages>
• If no env is specified, installed in currently active
environment
• Version and channel can also be specified: conda install
[-n env_name] [-C channel] <package=version>
• Important note: users don't have permissions to install
packages in shared environments!](https://image.slidesharecdn.com/conda-200220081039/85/Conda-environment-system-how-to-use-it-on-CSUC-machines-15-320.jpg)
![Private environments
• To update packages in an environment: conda
update [-n env_name] <specific packages> or
conda update [-n env_name] --all
• To uninstall packages: conda remove [-n
env_name] <packages>
• To completely delete a private environment:
conda remove -n <env_name> --all](https://image.slidesharecdn.com/conda-200220081039/85/Conda-environment-system-how-to-use-it-on-CSUC-machines-16-320.jpg)
Conda environment system how to use it on CSUC machines
- 1. Conda environment system & how to use it on CSUC machines Víctor Pérez 19/ 02 / 2020
- 2. Index 1. What is conda? 2. Scope of the project 3. How to use conda 4. Conda environments 5. Package management 6. Python through conda 7. R through conda
- 3. What is conda? • Originally: Anaconda, a distribution of Python including common scientific packages https://www.anaconda.com/ • Extended to include R and R packages, scientific libraries, other software, etc. • conda: core package manager for the Anaconda project
- 4. What is conda? • conda installs and updates binary versions of Python and R packages from its own (or third party) repositories • It is an alternative to other repository systems, like pip for Python or CRAN for R • It is also a way to manage dependencies for Python and R packages
- 5. But conda isn't... • A repository of system software packages (such as apt or yum) • A repository of source code • A replacement for environment modules • Exhaustive or infallible
- 6. Scope of the project • Python • R • Jupyter, Spyder, Rstudio... • NumPy, SciPy, Pandas, Numba, Dask... • Scikit-learn, TensorFlow, Theano... • Matplotlib, Bokeh, Datashader, Holoviews... • A variety of external libraries and tools
- 7. Conda channels • Channels are thematic collections of packages, useful to avoid version conflicts (equivalent to repositories) • Examples: – pkgs/main: default channel – conda-forge:large collection of third party packages – bioconda:software for bioinformatics – r: tailored to R users
- 8. How to use conda • We need to load an environment module to configure conda. module load conda/3 Python 2 (legacy): module load conda/2
- 9. How to use conda • Then we use the command conda (+ action) to run it: conda list conda activate conda create conda search conda install conda update conda help
- 10. Conda environments • Inside a given installation of conda (conda/2 or conda/3), there are a number of environments • Environments are profiles: each will have a different list of packages and versions installed • There is a default base env, shared envs (accessible to all users) and private envs (accesible to the current user only)
- 11. Activating/Deactivating environments • To see a list of environments: conda env list • To load an env: conda activate <env_name> • To unload: conda deactivate
- 12. Activating/Deactivating environments • To see the contents of an env: conda list [-n env_name] (by default, currently activated environment) • Note: source activate and source deactivate are obsolete
- 13. Shared environments • Maintained by our HPC team, available to all users: – base: Python and common Python packages – bio-computation: Python, Biopython, Bioperl and libraries for bioinformatics – machine-learning:Python and R for ML, including Scikit-learn, TensorFlow and Keras – machine-learning-gpu: same but with GPU support – quantum-chem: Python tools for QC, including MDtraj, PySCF, libcint and libxc – genetics: R tools for NGS, such as DESeq2, edgeR or LIMMA
- 14. Private environments • Users can create their own private envs (stored at $HOME/.conda/envs) which won't we visible for other users • To create a new empty environment: conda create -n <env_name> • To create a new environment with packages preinstalled in it: conda create –n <env_name> [list of packages]
- 15. Private environments • To install one or more packages in a private env: conda install [-n env_name] <packages> • If no env is specified, installed in currently active environment • Version and channel can also be specified: conda install [-n env_name] [-C channel] <package=version> • Important note: users don't have permissions to install packages in shared environments!
- 16. Private environments • To update packages in an environment: conda update [-n env_name] <specific packages> or conda update [-n env_name] --all • To uninstall packages: conda remove [-n env_name] <packages> • To completely delete a private environment: conda remove -n <env_name> --all
- 17. Using Python through conda #!/bin/bash #SBATCH –p std #SBATCH –N 1 #SBATCH –n 1 module load conda/3 conda activate machine-learning python example.py
- 18. Using R through conda #!/bin/bash #SBATCH –p std #SBATCH –N 1 #SBATCH –n 1 module load conda/3 conda activate machine-learning Rscript example.R
- 19. Using R through conda • It is possible to install R packages to the private library directory using CRAN, although it requires configuring a proxy: export http_proxy=192.168.255.254:8080 export https_proxy=192.168.255.254:8080 > install.packages("example")
- 20. Best practices • Creating a private env tailored to your needs is usually more efficient than using shared envs • Avoid clutter in your private environments; it's better to create multiple single-purpose environments than one large environment with too many packages • Be mindful of version collision when updating environments; if you don't need to update, don't