Conda

For help on creating and managing personal environments whether for command-tool use or python package use in SLURM jobs or Jupyter kernels see Managing Python environments and Jupyter kernels

Description

conda website  

Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments. Separating applications in separate conda environments allows installation of incompatible dependencies - python2 and python3 for example.

Note: For a faster conda see Mamba.

Environment Modules

Run module spider conda to find out what environment modules are available for this application.

System Variables

• HPC_CONDA_DIR - installation directory
• HPC_CONDA_BIN - executable directory

Configuration

Expand this section to view instructions for configuring Conda

The ~/.condarc configuration file

conda's behavior is controlled by a configuration file in your home directory called .condarc. The dot at the start of the name means that the file is hidden from 'ls' file listing command by default. If you have not run conda before, you won't have this file. Whether the file exists or not, the steps here will help you modify the file to work best on HiPerGator. First load of the conda environment module on HiPerGator will put the current best practice .condarc into your home directory.

conda package cache location

conda caches (keeps a copy) of all downloaded packages by default in the ~/.conda/pkgs directory tree. If you install a lot of packages you may end up filling up your home quota. You can change the default package cache path. To do so, add or change the pkgs_dirs setting in your ~/.condarc configuration file e.g.:

pkgs_dirs:
  - /blue/mygroup/share/conda/pkgs

or

  - /blue/mygroup/$USER/conda/pkgs

Replace mygroup with your actual group name.

conda environment location

conda puts all packages installed in a particular environment into a single directory. By default named conda environments are created in the ~/.conda/envs directory tree. They can quickly grow in size and, especially if you have many environments, fill the 40GB home directory quota. For example, the environment we will create in this training is 5.3GB in size. As such, it is important to use path based (conda create -p PATH) conda environments, which allow you to use any path for a particular environment for example allowing you to keep a project-specific conda environment close to the project data in /blue/ where you group has terrabyte(s) of space.

You can also change the default path for the name environments (conda create -n NAME) if you prefer to keep all conda environments in the same directory tree. To do so, add or change the envs_dirs setting in the ~/.condarc configuration file e.g.:

envs_dirs:
  - /blue/mygroup/share/conda/envs

or

  - /blue/mygroup/$USER/conda/envs

Replace mygroup with your actual group name.

One way to edit your ~/.condarc file is to type: nano ~/.condarc`

If the file is empty, paste in the text below, editing the env_dirs: and pkg_dirs as below. If the file has contents, update those lines.

Your ~/.condarc should look something like this when you are done editing (again, replacing group and user in the paths with your group and username).

channels:
- conda-forge
- bioconda
- defaults
envs_dirs:
- /blue/group/user/conda/envs
pkgs_dirs:
- /blue/group/user/conda/pkgs
auto_activate_base: false
auto_update_conda: false
always_yes: false
show_channel_urls: false

Create and activate your first environment

Expand this section to view instructions for setting up environments.

UF Research Computing Applications Team uses conda for many application installs behind the scenes. We are happy to install applications on request for you. However, if you would like to use conda to create multiple environments for your personal projects we encourage you to do so. Here are some recommendations for successful conda use on HiPerGator.

• See https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html for the original documentation on managing conda environments.
• We recommend creating environments by 'path', so they won't fill up your home directory (check quota with home_quota). The resulting environment should be located in the project(s) directory tree in /blue for better tracking of installs and better filesystem performance compared to home.

If you plan on using a GPU: it is important to build the environment on a server with a GPU (within a Jupyter job where you requested a GPU, for example). HiPerGator login servers do not have GPUs, so building environments on the login servers will result in code that is not optimized for running on a GPU.

Load the conda module

Before we can run conda or mamba on HiPerGator, we need to load the conda module:

module load conda

Create your first environment

Create a name based environment

To create your first name based (see path based instructions below)conda environment, run the following command. In this example, I am creating an environment named hfrl:

mamba create -n hfrl

The screenshot to the right is the output from running that command. Yours should look similar.

Note: You do not need to manually create the folders that you setup in your ~/.condarc file. mamba will take care of that for you.

Create a path based environment

To create a path based conda environment use the '-p PATH' argument: mamba create -p PATH e.g. mamba create -p /blue/mygroup/share/project42/conda/envs/hfrl/

Activate the new environment

To activate our environment (whether created with mamba or conda we use the conda activate env_name command. Let's activate our new environment:

conda activate hfrl

or

conda activate /blue/mygroup/share/project42/conda/envs/hfrl/

Notice that your command prompt changes when you activate an environment to indicate which environment is active, showing that in parentheses before the other information:

 (hfrl) [magitz@c0907a-s23 magitz]$ 

Note: path based environment activation is really only needed for package installation. For using the environment just add the path to its bin directory to $PATH in your job script.

Once you are done installing packages inside the environment you can use

$ conda deactivate

We do not recommend activating conda environments when _using_ them i.e. running programs installed in the environments. Please prepend the path to that environment to your $PATH instead.

E.g. If you have a project-specific conda environment at '/home/myuser/envs/project1/' add the following into your job script before executing any commands

export PATH=/home/myuser/envs/project1/bin:$PATH