#CONDA INSTALL OPENCV TO ENVIRONMENT INSTALL#
Link to section 'Step 3: Install packages' of 'Installing Packages' Step 3: Install packages If you used a custom module file location (Example 3 above), please use module use to load the conda-env module. This is same as the Python version in the anaconda module. Note that the conda-env module name includes the Python version that it supports (Python 3.6.4 in this example). $ module load conda-env/mypackages-p圓.6.4 If you used conda create instead, please use conda activate mypackages. The following instructions assume that you have used rcac-conda-env script to create an environment named mypackages (Examples 1 or 2 above). Link to section 'Step 2: Load the conda environment' of 'Installing Packages' Step 2: Load the conda environment Jupyter kernel created: "Python (My labpackages Kernel)" $ conda-env-mod create -p /depot/mylab/apps/labpackages -m /depot/mylab/etc/modules -jupyter Example 4: Create a Jupyter-enabled conda environment named labpackages in your group's Data Depot space and place the module file at a shared location for the group to use.If you plan to use your environment in a JupyterHub notebook, you need to append a -jupyter flag to the above commands. If you used a custom module file location, you need to run the module use command as printed by the script.īy default, only the environment and a module file are created (no Jupyter kernel). Your environment "labpackages" was created successfully. | module load conda-env/labpackages-p圓.6.4 | $ conda-env-mod create -p /depot/mylab/apps/labpackages -m /depot/mylab/etc/modules Example 3: Create a conda environment named labpackages in your group's Data Depot space and place the module file at a shared location for the group to use.The location of module files can be customized by specifying the -m /path/to/modules option to rcac-conda-env. You may also want to add the module load lines in your jobscript, if it depends on custom Python packages.īy default, module files are generated in your $HOME/privatemodules directory. Note down the module names, as you will need to load these modules every time you want to use this environment. Your environment "mypackages" was created successfully. | module load conda-env/mypackages-p圓.6.4 | | To use this environment, load the following modules: | After finishing, the script will print the instructions to use this environment. Please follow the on-screen instructions while the environment is being created. $ conda-env-mod create -p /depot/mylab/apps/mypackages $ conda-env-mod create -n mypackagesĮxample 2: Create a conda environment named mypackages at a custom location. Detailed instructions for using conda-env-mod can be found with the command conda-env-mod -help.Įxample 1: Create a conda environment named mypackages in user's home directory. Please note that conda-env-mod is different from the official conda-env script and supports a limited set of subcommands. After the environment is created, it generates a module file for using it in future. This script needs either a name or a path for the desired environment. Users can use the conda-env-mod script to create an empty conda environment. Link to section 'Step 1: Create a conda environment' of 'Installing Packages' Step 1: Create a conda environment Step-by-step instructions for installing custom Python packages are presented below. You must load one of the anaconda modules in order to use this script. To facilitate the process of creating and using Conda environments, we support a script ( conda-env-mod) that generates a module file for an environment, as well as an optional Jupyter kernel to use this environment in a JupyterHub notebook. If you are unfamiliar with Conda environments, please check our Conda Guide. Individual packages can later be reinstalled or updated without impacting others. One key advantage of Anaconda is that it allows users to install unrelated packages in separate self-contained environments. ITaP recommends installing Python packages in an Anaconda environment. Environment Management with the Module Command.Example: Create and Use Biopython Environment with Conda.
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