{"id":11406,"date":"2025-11-17T11:56:10","date_gmt":"2025-11-17T11:56:10","guid":{"rendered":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/?page_id=11406"},"modified":"2026-07-29T09:34:27","modified_gmt":"2026-07-29T08:34:27","slug":"conda","status":"publish","type":"page","link":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/software\/applications\/conda\/","title":{"rendered":"Conda – Miniforge3"},"content":{"rendered":"

Overview<\/h2>\n

Conda<\/a> is package and environment manager. It allows you to create separate environments, each containing their own files, packages (typically python packages), and package dependencies. The contents of each environment do not interact with each other.<\/p>\n

Hence it allows you to work on multiple python projects without package installs in one project breaking another project.<\/p>\n

New versions of Conda are regularly released, but environments created with older versions are generally usable with newer versions.<\/p>\n

On the CSF we recommend the Minforge3 implementation of Conda because it is aligned with the open conda-forge community and repository<\/a>.<\/p>\n

The Bioconda channel<\/a> is already configured within our Miniforge modules.<\/p>\n

Restrictions on use<\/h2>\n

Conda is open source but packages and repositories may not be entirely open or available under the same open source license.<\/p>\n

Miniforge installer code uses BSD-3-Clause license.<\/p>\n

Set up procedure<\/h2>\n

We recommend loading modulefiles within your jobscripts so that you have a full record of how the job was run. See the example jobscript below for how to do this. Alternatively, you may load modulefiles on the login node and let the job inherit these settings.<\/p>\n

Load one of the following modulefiles:<\/p>\n

\r\nmodule load apps\/binapps\/conda\/miniforge3\/26.3.2     # Provides python 3.13.13 unless specified\r\nmodule load apps\/binapps\/conda\/miniforge3\/25.9.1     # Provides python 3.12.12 unless specified\r\nmodule load apps\/binapps\/conda\/miniforge3\/25.3.0     # Provides python 3.12.9 unless specified\r\n<\/pre>\n
Loading the module will set all parameters to allow Conda to function, but will not activate the conda base environment. To use a Conda environment, you first need to create it.<\/p>\n
The information provided here is for quick reference, for more complete documentation please see the official Conda getting started guide.<\/a><\/p>\n
Create a Conda environment<\/h3>\n
Create an environment called “myenv” with a specific Python version and the pandas package:<\/p>\n
\r\nconda create -n myenv python==3.11 pandas\r\n                         #           #\r\n                         #           # Packages you wish to install inside your conda\r\n                         #           # env. This is optional, you can also do it later.\r\n                         #\r\n                         # Installing a version of python is optional\r\n                         # (see above for default python versions)\r\n<\/pre>\n
Conda will look up the requested packages and if they are available, will present you with package plan. You do not have to install python, Conda is used to manage a wide range of different software.<\/p>\n
Type ‘Y’ to accept the plan and allow Conda to install the software.<\/p>\n
When the install is complete you will be prompted to activate the environment:<\/p>\n
\r\nconda activate myenv\r\n<\/pre>\n
If you have previously used Conda, you might expect to run the ‘conda init’ or ‘source activate’ commands at this point. However, we have configured Miniforge such that you do not need to do this and Conda will not modify your .bashrc file or any other persistent configurations.<\/div>\n
Once your environment is active your shell will look something like:<\/p>\n
\r\n(myenv) [a12345bc@login2[csf3] ~]$\r\n  #\r\n  # Name of active conda env you are now working in.\r\n  # For example, python package install will go into this env.\r\n<\/pre>\n
You can install\/uninstall any other available Conda packages with the following commands. The packages will be installed into the currently active conda env:<\/p>\n
\r\nconda install PACKAGE<\/em>\r\nconda remove PACKAGE<\/em>\r\n<\/pre>\n
To deactivate an environment:<\/p>\n
\r\nconda deactivate\r\n\r\n# Your prompt will return to the default, showing no active env\r\n[a12345bc@login2[csf3] ~]$\r\n<\/pre>\n
Remember, when you want to use<\/em> a package that you’ve installed in a conda env, you must always first activate the conda env.<\/p>\n
Mamba<\/h3>\n
If your packages are particularly complicated and have many dependencies, using mamba<\/code> to install into an empty Conda environment may be faster. This tends to be the case with Bioinformatics pipeline environments. To use mamba<\/code>:<\/p>\n
\r\nconda create -n myenv\r\nconda activate myenv\r\nmamba install PACKAGE1 PACKAGE2\r\n<\/pre>\n
Running jobs within a Conda environment<\/h2>\n
While you can set up your environment on the login nodes, jobs must<\/strong> be submitted to the compute nodes via batch.<\/p>\n
Serial batch job submission<\/h3>\n
Create a batch submission script which loads the modulefile, checking that you are loading the version you want, for example:<\/p>\n
\r\n#!\/bin\/bash --login\r\n#SBATCH -p serial     # (or --partition=) Run on the nodes dedicated to 1-core jobs\r\n#SBATCH -t 4-0        # Wallclock time limit. 4-0 is 4 days. Max permitted is 7-0.\r\n\r\n# Start with a clean environment - modules are inherited from the login node by default.\r\nmodule purge\r\nmodule load apps\/binapps\/conda\/miniforge3\/VERSION\r\n\r\nconda activate myenv\r\n\r\npython3 myscript.py\r\n\r\n<\/pre>\n
Submit the jobscript using: <\/p>\n
sbatch scriptname<\/em><\/pre>\n
where scriptname<\/em> is the name of your jobscript.<\/p>\n
Parallel batch job submission<\/h3>\n
If the app is multicore capable, the following parallel jobscript includes an example of how you might set the number of threads\/processes automatically from SLURM variables, whether this is necessary will depend on your code.<\/p>\n
\r\n#!\/bin\/bash --login\r\n#SBATCH -p multicore  # (or --partition=) Run on the AMD 168-core nodes\r\n#SBATCH -n 16         # (or --ntasks=) Number of cores to use.\r\n#SBATCH -t 4-0        # Wallclock time limit. 4-0 is 4 days. Max permitted is 7-0.\r\n\r\n## Start with a clean environment - modules are inherited from the login node by default.\r\nmodule purge\r\nmodule load apps\/binapps\/conda\/miniforge3\/VERSION\r\n\r\nconda activate myenv\r\n\r\n## set any multi-tread parameters you may need from the slurm parameter\r\n## THREADS will be 16 in this example\r\nTHREADS=$SLURM_NTASKS_PER_NODE\r\n\r\n## run code, assuming that the -t option is number of threads\r\npython3 myscript.py -t $THREADS\r\n<\/pre>\n
Submit the jobscript using: <\/p>\n
sbatch scriptname<\/em><\/pre>\n
where scriptname<\/em> is the name of your jobscript.<\/p>\n
Hints and tips<\/h2>\n
Conda environments and packages can be large, which can lead to your home directory or other spaces getting full, the following actions can help you clean up:<\/p>\n
Review your environments and remove any you no longer need:<\/p>\n
\r\nconda env list\r\n\r\nconda env remove -n NAME\r\n<\/pre>\n
Clean up cached downloads (will not delete environments):<\/p>\n
\r\nconda clean -a\r\n<\/pre>\n
You can specify a different location when you create a new environment provided you have write access there:<\/p>\n
\r\nconda create -p \/some\/path\/you\/have\/write\/access\/myenv\r\n<\/pre>\n
and activate with the full path:<\/p>\n
\r\nconda activate \/some\/path\/you\/have\/write\/access\/myenv\r\n<\/pre>\n
Reproducible environments<\/h3>\n
It is good practice to keep a record of exactly what packages and versions you used to produce your work. Conda supports this by allowing you to export the complete list of packages in an environment to a YAML file:<\/p>\n
\r\nconda export -n NAME --no-builds --file environment.yaml \r\n<\/pre>\n
We suggest putting this environment.yaml into your source control alongside your code or scripts.<\/p>\n
You can subsequently re-create a deleted environment using the file:<\/p>\n
\r\nconda env create --file=environment.yaml\r\n<\/pre>\n
Share environment details with a collaborator via a specification file<\/h3>\n
With the environment active: <\/p>\n
\r\nconda list --explicit > specification.txt\r\n<\/pre>\n
To make an environment from a specification:<\/p>\n
\r\nconda create --prefix INSERT-FULL-PATH\/env-name --file specification.txt\r\n<\/pre>\n
Further details can be found in the conda export documentation.<\/a><\/p>\n
Migrating from Anaconda Python – check your ~\/.bashrc file<\/h3>\n
If you’ve previously used Anaconda Python on the CSF to create conda environments, you may wish to check that your login environment is not automatically setting things up for Anaconda, as follows:<\/p>\n
If when using Anaconda python, you may have run conda init bash<\/code> at some point. This will have added something to your ~\/.bashrc<\/code> file, which will cause Anaconda settings to be applied every time you login to the CSF. You can now remove the following lines from your ~\/.bashrc<\/code> file (which is just a text file):<\/p>\n
\r\ngedit ~\/.bashrc\r\n  #\r\n  # Remove everything bewteen the lines show below, including the two line!\r\n  # This occurs at the bottom of your ~\/.bashrc file.\r\n\r\n# >>> conda initialize >>>\r\n# !! Contents within this block are managed by 'conda init' !!\r\n\r\n... remove all of the script code and these surrounding lines<\/strong><\/em> ...\r\n\r\n# <<< conda initialize <<<\r\n<\/pre>\n
Moving a conda environment<\/h2>\n
You may need to move a conda environment:<\/p>\n