Pfe20 % export CONDA_PKGS_DIRS=/nobackup/$USER/.conda/pkgs Export the path to the target directory where you want to put the packages for installation:.For csh: % setenv CONDA_ENVS_PATH /nobackup/$USER/.conda/envs.For bash: % export CONDA_ENVS_PATH=/nobackup/$USER/.conda/envs.The folder is created the first time you run the conda command. conda/envs folder in /nobackup, as shown below. To do this, set the CONDA_ENVS_PATH environment variable to point to a. TIP: If you don't want to fill up your home directory, you can put the environment in your /nobackup directory. For example:įor more information about YAML files, see the conda documentation.Ĭomplete these steps to build a conda environment from a YAML file: A list of YAML files for each of the NAS-provided conda environments can be found in the /swbuild/analytix/tools/miniconda3_220407_yml/ directory. To build your own conda environment based on one of the NAS-provided conda environments, you can use the YAML file for the environment you want to clone. If you have questions about this procedure or require assistance, please contact us by sending email to Creating a Conda Environment from a Clone Cloning from a YAML File Environments cloned from one of the Data Science conda environments or created from one of the Data Science YAML files will download and install packages from this repo. You should now have access to the commercial anaconda.cloud repo. In addition, you can check whether appears in your. Verify the token is linked by using the conda info command.

Run the conda token set command with token you received in the email:.module use -a /swbuild/analytix/tools/modulefiles.Load the HECC Data Science miniconda module as follows:.In two or three days, you will receive an email from Anaconda Nucleus with your new token and instructions on how to install it.Click the Join Organization button and complete creating an account using the email address that the invite was sent to. Create an Anaconda Nucleus account using the email you received.Important: Email sent from a non-NASA email address will not receive a response. Request a NASA Ames conda token by sending email from your NAS account to: You will receive an email, “Invitation to the NASA Ames organization on Anaconda Nucleus.”.Complete these steps to acquire and install a token: In order to create a conda environment and be in compliance with the NASA Ames site license, we require all users to install a conda token prior to creating an environment.

The conda environments are supported under an Anaconda site license. 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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