Creating a Conda Environment from a Clone Cloning from a Spec List File To ensure that you can use your conda environment properly, please familiarize yourself with all the basic conda commands. The easiest way to create your own environment is to clone an existing conda environment into your own directory, then modify it.Ĭreating an environment can take up a significant portion of your disk quota, depending on the packages installed.
Use the pip command to install the packages:īuilding your own conda environment gives you the control to manage and install your own packages, and they will be less likely to have version errors than the pip-installed packages. Pfe20 % module use -a /swbuild/analytix/tools/modulefiles directory.Ĭomplete the following steps to install packages on a Pleiades front-end system (PFE): The packages will be installed in the $HOME/.local/lib/. Packages are Python-version-dependent therefore, to ensure you can use the packages with the environment you want, load the environment before using pip. If the packages do not show up in other environments, make sure the Python versions in the loaded environment and the base environment match. The packages installed with pip will be applied to all environments that you load and will take precedence over the installed versions of packages within those environments-possibly causing version errors, depending on the differences. 
Using the pip tool to install packages is easier than building your own conda environment and takes less space in your home directory.
Use the pip tool to install them directlyĬonsider the benefits and disadvantages of each method, described below, before choosing which works best for you. You have two options to install your own Python packages in our machine learning environment:
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