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Miniconda is a small, bootstrap version of Anaconda that includes only conda, Python, the packages they depend on, and a small number of other useful packages, including pip, zlib and a few others. It can also be used to start with a minimal set of installed packages, and then install only the required ones (to save space).

Training:

Info

ARCC provides the following workshops on using conda environments:

Using

Use the module name miniconda3 to discover versions available and to load the application.

Note

When using miniconda3 via an interactive session (salloc) or submitting a script via sbatch, please make sure to explicitly load the miniconda3 module once you have your interactive session on the compute node, and within you bash script.

If you do not, you’ll see an error of the form: CondaError: Run 'conda init' before . ..

Training:

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Install Packages into a Miniconda Environment in Your Home Directory

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  • Python packages: All Python packages that will be needed in programs using a package will need to be installed into the same environment, as the instance of Python from this environment will be used to run the programs. To install additional packages, activate the environment, install the packages (with conda if possible, otherwise with pip), then deactivate the environment.

  • Installing PyPi packages with pip: If an attempt to install a package gives an error about trying to write to a location to which there isn't permission, this is usually a result of a PATH issue.

    • It is important to use the instance of pip that was installed in the conda environment, and not one from another location that may be available in the path.

    • The current path can be seen by running 'echo $PATH'.

    • Issues with incorrect directories being included, or occurring in the wrong order, in a path can usually be resolved by logging out and back in, loading Miniconda, then activating the necessary environment.

  • Conda environment dependencies:

    Within the Conda documentation on Managing environments, specifically the section on Building identical conda environments, it states:

    • You can use explicit specification files to build an identical conda environment on the same operating system platform, either on the same machine or on a different machine.

    • An explicit spec file is not usually cross platform, and therefore has a comment at the top such as # platform: osx-64 showing the platform where it was created. This platform is the one where this spec file is known to work. On other platforms, the packages specified might not be available or dependencies might be missing for some of the key packages already in the spec.

    • System requirements License:

      Operating system: Windows 8 or newer, 64-bit macOS 10.13+, or Linux, including Ubuntu, RedHat, CentOS 7+, and others

      Conda does not check architecture or dependencies when installing from a spec file. To ensure that the packages work correctly, make sure that the file was created from a working environment, and use it on the same architecture, operating system, and platform, such as linux-64 or osx-64.

    The Miniconda documentation states:

    • .

Common Error Messages

Error: /lib64/libk5crypto.so.3: undefined symbol: EVP_KDF_ctrl, version OPENSSL_1_1_1b

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