Using Conda Environments¶
The conda package manager allows users to install software easily and without admin privileges. Conda environments can be created for any software set, and can be enabled/disabled dynamically not unlike modules.
A conda environment is not to be confused with the environment of your login shell. The package tied to an environment module is compiled by hand by the Unity admins, where conda packages can be installed by any user with a simple command. A conda environment can contain any number of packages, where a module usually only contains one. Modules and conda environments can be used together.
On Unity we use Miniconda, as opposed to Anaconda. From a user's perspective they can be considered to be the same thing.
When working on a conda environment, make sure you activate it! Without a currently active environment, conda will attempt to modify the global Unity environment, and you will get
miniconda module is loaded.
If you see this:
conda: Command not found
module load miniconda
Creating an Environment¶
You can create as many conda environments as you desire, limited only by our disk quotas.
conda create --name testName python=3.7
This creates an environment in your home folder, specifically
You can also create environments in other directories, such as your PI's work directory.
mkdir -p /work/pi_name/$USER-conda/envs conda create --prefix /work/pi_name/$USER-conda/envs/testName python=3.7 # OPTIONAL, make a symlink (shortcut) to home directory ln -s /work/pi_name/$USER-conda/envs/testName ~/testName
testName with the name of your choice, and replace
3.7 with your Python version of choice.
$USER environment variable evaluates to your username.
Activating an Environment¶
Environment created with
conda activate testName
Environment created with
conda activate /work/pi_name/$USER-conda/envs/testName # OR cd /work/pi_name/$USER-conda/envs/ conda activate ./testName
Your currently active conda environment will appear in parentheses to the left of your command line prompt:
user@login2:~$ conda activate ./testName (testName) user@login2:~$
Adding Packages to your Environment¶
conda install numpy
The install will ask you to confirm installing numpy as well as any other additional required packages.
List Available Environments¶
conda env list
List Packages Installed in the Current Environment¶
Delete an Environment¶
conda remove --name testName --all
If your environment was added to JupyterHub, you will have to remove it manually.
rm -rf ~/.local/share/jupyter/kernels/testName
Conda Environments and Jupyter¶
You can create many custom conda environments and use them within JupyterHub. This must be done in the command line, but JupyterHub provides a command line interface in it's 'Terminal' app.
Adding your Environment to JupyterHub¶
make sure your environment is activated first. Without a currently active environment, conda will attempt to modify the main default environment, and you will get permission denied.
conda install ipykernel
Add a kernelspec (Kernel Specification) to your JupyterHub.
python -m ipykernel install --user --name testName --display-name="Display Name Within JupyterHub"
If the above was done within JupyterHub, reload the page. If that doesn't work, restart your JupyterHub server.