[et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_fullwidth_menu menu_id=”15″ menu_style=”centered” fullwidth_menu=”on” active_link_color=”#d80b8c” dropdown_menu_line_color=”#221f72″ _builder_version=”4.16″ _module_preset=”default” menu_font=”|600|||||||” menu_text_color=”#FFFFFF” menu_font_size=”16px” background_color=”#221f72″ background_layout=”dark” sticky_position=”top” global_colors_info=”{}”][\/et_pb_fullwidth_menu][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16″ custom_padding=”0px||0px||false|false” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text admin_label=”Breadcrumb” _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
Scientific Computing and Data<\/a> \/ High Performance Computing<\/a> \/ Documentation<\/a> \/ Conda<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”|auto||90px||” hover_enabled=”0″ global_colors_info=”{}” module_alignment=”center” sticky_enabled=”0″][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text admin_label=”conda introduction” _builder_version=”4.27.4″ _module_preset=”default” header_font=”|600|||||||” header_text_color=”#221f72″ header_font_size=”26px” header_2_text_color=”#221f72″ header_2_font_size=”24px” global_colors_info=”{}”]<\/p>\n Conda is an open-source package management system and environment management system that runs on Windows, macOS, Linux and z\/OS. Conda quickly installs, runs and updates packages and their dependencies. Conda easily creates, saves, loads and switches between environments on your local computer. It was created for Python programs, but it can package and distribute software for any language.<\/p>\n Minerva has transitioned from Anaconda to Miniforge<\/b> to ensure a software ecosystem that is fully compliant and flexible. Please refrain from using the Anaconda channel for the reasons outlined below.<\/strong><\/p>\n The conda package and environment manager is included in all versions of miniforge3. Many versions of miniforge3 are available to use on Minerva. To see a list of installed versions of miniforge3 on the cluster, use Lmod\u2019s spider command:<\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/scpublic.dmz.hpc.mssm.edu\/HPC\/conda\/miniforge.png” align=”center” admin_label=”ml spider anaconda image” _builder_version=”4.27.4″ _module_preset=”default” width=”60%” max_width=”60%” module_alignment=”center” custom_margin=”10px||20px||false|false” custom_padding=”10px||20px||false|false” global_colors_info=”{}”][\/et_pb_image][et_pb_text admin_label=”conda usage” _builder_version=”4.27.4″ _module_preset=”default” header_font=”|600|||||||” header_text_color=”#221f72″ header_font_size=”26px” header_2_text_color=”#221f72″ header_2_font_size=”24px” global_colors_info=”{}”]<\/p>\n When creating an environment, conda will download large amounts of installation tarballs to the package cache directory. The default is \u201c~\/.conda\/pkgs\u201d in \/home directory, however on Minerva, user’s home directory has 30 GB quota. Therefore, instead of using this default setting, it is recommended to redirect the downloaded package cache directory to a different location, which can be specified in the \u201c~\/.condarc\u201d file. Below steps listed steps for redirecting the package cache location:<\/p>\n Edit conda user config file: \u201c~\/.condarc\u201d to redirect the package cache and env directory. For example, after opening \u201c~\/.condarc\u201d, add the following lines:<\/p>\n If you do not have a \u201c~\/.condarc\u201d file, use the command below to create one:<\/p>\n Before trying to create a conda virtual environment, do a module purge to clean up the current environment:<\/p>\n Then load an miniforge3 module. For example:<\/p>\n Check conda information. If conda is available, you will see:<\/p>\n <\/p>\n Also make sure the envs and package cache directories have been redirected to the correct directory. The conda environment should then be activated before installing packages:<\/p>\n The name of the virtual environment will also show in front of your username in the prompt:<\/p>\n Then you can install packages using the command:<\/p>\n Channel name and package version are optional. Other useful conda commands: Check installed packages:<\/p>\n Upgrade and uninstall packages inside a conda environment:<\/p>\n Remove a conda environment:<\/p>\n [\/et_pb_text][et_pb_text admin_label=”conda python” _builder_version=”4.27.4″ _module_preset=”default” header_font=”|600|||||||” header_text_color=”#221f72″ header_font_size=”26px” header_2_text_color=”#221f72″ header_2_font_size=”24px” global_colors_info=”{}”]<\/p>\n Make sure to unset PYTHONPATH and PYTHONHOME in case they are specified previously:<\/p>\n The version of Python in the conda environment can be specified when creating the conda environment, for example, specify python 3.6 to be used in the environment \u201ctest\u201d:<\/p>\n Or install python after creating the conda environment:<\/p>\n [\/et_pb_text][et_pb_text admin_label=”conda R” _builder_version=”4.27.4″ _module_preset=”default” header_font=”|600|||||||” header_text_color=”#221f72″ header_font_size=”26px” header_2_text_color=”#221f72″ header_2_font_size=”24px” global_colors_info=”{}”]<\/p>\n Make sure to unset R_LIBS and R_LIBS_USER in case they are specified previously:<\/p>\n Also, you might need to comment lines related to these variables in .Renviron and .Rprofile file in your home directory. Or install R after creating the conda environment:<\/p>\n When using conda to install R packages, you will need to add r- before the regular package name. For instance, if you want to install rbokeh, you will need to use:<\/p>\n or for rJava, type:<\/p>\nConda<\/h1>\n
Contents<\/span><\/b>
Usage<\/span><\/a>
Using Conda with Python<\/span><\/a>
Using Conda with R<\/span><\/a><\/h3>\n\n
Recent changes to Anaconda\u2019s licensing model restrict free usage in certain organizational and commercial settings. Miniforge is fully open-source and avoids potential licensing risks or fees.<\/li>\n
Miniforge uses the conda-forge channel by default, which is community-maintained, transparent, and widely trusted for up-to-date packages.<\/li>\n
Unlike Anaconda, which ships with many preinstalled packages, Miniforge provides a minimal base environment. This reduces bloat and gives users full control over installed packages.<\/li>\n<\/ul>\nUsage<\/h2>\n
\n
envs_dirs: \n- \/sc\/arion\/work\/your_username\/test-env\/envs \npkgs_dirs: \n- \/sc\/arion\/work\/your_username\/test-env\/pkgs<\/code><\/pre>\n<\/blockquote>\n$ touch ~\/.condarc<\/code><\/pre>\n$ module purge<\/code><\/pre>\n$ module load miniforge3\/26.1.1-3<\/code><\/pre>\n$ conda info \n\u2026 \n active environment :\n shell level : 0\n user config file : \/hpc\/users\/[user_name]\/.condarc\n populated config files : \/hpc\/packages\/minerva-rocky9\/miniforge3\/26.1.1-3\/miniforge\/.condarc\n \/hpc\/users\/[user_name]\/.condarc\n conda version : 26.1.1\n conda-build version : not installed\n python version : 3.13.12.final.0\n solver : libmamba (default)\n virtual packages : __archspec=1=sapphirerapids\n __conda=26.1.1=0\n __glibc=2.34=0\n __linux=5.14.0=0\n __unix=0=0\n... \n package cache : \/hpc\/packages\/minerva-rocky9\/miniforge3\/26.1.1-3\/miniforge\/pkgs\n \/hpc\/users\/[user_name]\/.conda\/pkgs\n envs directories : \/hpc\/packages\/minerva-rocky9\/miniforge3\/26.1.1-3\/miniforge\/envs\n \/hpc\/users\/[user_name]\/.conda\/envs\n temporary directory : \/tmp\n platform : linux-64\n...<\/code><\/pre>\n
\nNext is to create a conda virtual environment. For example, creating a conda environment called “test” by:<\/p>\n$ conda create -n test<\/strong><\/code><\/pre>\n$ source activate test<\/strong><\/code><\/pre>\n(test<\/strong>) [user_name<\/strong>@li04e03 ~]$<\/code><\/pre>\n$ conda install -c channel_name<\/strong> package1=version<\/strong> package2=version<\/strong><\/code><\/pre>\n
\nIf you want to leave your virtual environment, simply run:<\/p>\n$ conda deactivate<\/code><\/pre>\n
\nChecking current and available conda environment:<\/p>\n$ conda info \u2013-envs<\/code><\/pre>\n$ conda list<\/code><\/pre>\n$ conda upgrade\/update package1 package2 <\/strong> \n$ conda uninstall\/remove package1 package2<\/strong><\/code><\/pre>\n$ conda env remove -n env_name<\/strong><\/code><\/pre>\nUsing Conda with Python<\/h2>\n
$ unset PYTHONPATH \n$ unset PYTHONHOME<\/code><\/pre>\n$ conda create \u2013n test python=3.6<\/strong><\/code><\/pre>\n$ conda install python=3.6 <\/code><\/pre>\nUsing Conda with R<\/h2>\n
$ unset R_LIBS \n$ unset R_LIBS_USER <\/code><\/pre>\n
\nThe version of R in the conda environment can be specified when creating the conda environment, for example, specify R 4.2.0 to be used in the environment \u201ctest\u201d:<\/p>\n$ conda create \u2013n test r-base=4.2.0 <\/code><\/pre>\n$ conda install r-base=4.2.0 <\/code><\/pre>\n$ conda install r-rbokeh <\/code><\/pre>\n$ conda install r-rjava <\/code><\/pre>\n