Anaconda is a popular distribution of Python commonly used in data science, machine learning applications, and large-scale data processing. The version of anaconda that is pre-installed on the CS machines is out of date and we have been experiencing difficulties in upgrading it on the network. The best work around is to download miniconda and use this to create conda environments, as it will provide the most up-to-date packages. Please follow the instructions at the bottom of the page for installing miniconda on linux: https://docs.conda.io/projects/miniconda/en/latest/index.html.
Once miniconda has been installed, use the below command to create a conda virtual environment.
$ conda create --name env_name
Specifics such as python versions, packages, and package versions can also be included when creating a new anaconda environment.
Once the anaconda environment is created, activate the environment with the command:
$ conda activate env_name
The name of the environment should now appear in parentheses to the left of your username on the terminal line. To install packages in your anaconda environment, you can use either the 'conda install' or 'pip install' commands. To see the list of installed packages within an anaconda environment, use the 'conda list' command. To exit the active anaconda environment, use the 'conda deactivate' command.
For a more detailed look at conda commands and uses, please see the official user guide at the following link: https://conda.io/projects/conda/en/latest/user-guide/index.html.