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Installation#

Dependencies#

Required dependencies#

  • Python (3.11 or later)
  • numpy (2.0.0 or later)

Optional dependencies#

Development dependencies#

  • nbval (0.11.0 or later)
  • pre-commit (3.7.1 or later)
  • pre-commit-hooks (4.6.0 or later)
  • pytest (8.2.2 or later)
  • pytest-cov (5.0.0 or later)
  • coverage

Documentation dependencies#

  • mkdocs (1.5.3 or later)
  • mkdocs-material (9.5.3 or later)
  • mkdocstrings (0.24.0 or later)
  • mkdocstrings-python (1.7.5 or later)
  • mike (2.1.3 or later)
  • mkdocs-jupyter (0.25.1 or later)
  • mkdocs-autorefs (1.2 or later)
  • mkdocs-macros-plugin (1.3.7 or later)
  • mkdocs-table-reader-plugin (3.1.0 or later)
  • mkdocs-mermaid2-plugin (1.2.1 or later)
  • jupyter-contrib-nbextensions (0.7.0 or later)
  • notebook (< 7.0)
  • jupyter

Installation Methods#

Please install hpc in a virtual environment so that its requirements don't tamper with your system's Python.

Pixi is a package manager and environment manager developed by Prefix.dev. It's designed to create reproducible environments and is used in this project for dependency management.

Installing Pixi#

If you don't have Pixi installed, you can install it following the instructions on the Pixi installation page.

For Windows: 

# Using PowerShell
iwr -useb https://pixi.sh/install.ps1 | iex

For Linux/macOS: 

# Using curl
curl -fsSL https://pixi.sh/install.sh | bash

Setting up the environment with Pixi#

  1. Clone the repository: 

    git clone https://github.com/Serapieum-of-alex/hpc.git
cd hpc

  2. Install dependencies using Pixi: 

    pixi install

This will create a reproducible environment with all the required dependencies based on the pixi.lock file.

Using different environments#

The project defines three environments in the pyproject.toml file:

  1. default: Basic environment with minimal dependencies 

    # Activate the default environment
pixi shell

  2. dev: Development environment with testing tools 

    # Run a command in the dev environment
pixi run --environment dev pytest

  3. docs: Documentation environment with tools for building docs 

    # Run a command in the docs environment
pixi run --environment docs mkdocs build

Using Conda#

The easiest way to install hpc is using the conda package manager. hpc is available in the conda-forge channel. To install you can use the following command:

conda install -c conda-forge hpc

If this works it will install hpc with all dependencies including Python, and you can skip the rest of the installation instructions.

Using Pip (PyPI)#

To install the latest release of hpc from PyPI:

pip install hpc-utils

To install a specific version:

pip install hpc-utils==0.1.4

Installing Python#

For Python, we recommend using the Anaconda Distribution for Python 3, which is available for download from https://www.anaconda.com/download/. The installer gives the option to add python to your PATH environment variable. We will assume in the instructions below that it is available in the path, such that python, pip, and conda are all available from the command line.

Note that there is no hard requirement specifically for Anaconda's Python, but often it makes installation of required dependencies easier using the conda package manager.

From sources#

The sources for hpc can be downloaded from the Github repo.

You can either clone the public repository:

git clone git://github.com/Serapieum-of-alex/hpc

Or download the tarball:

curl -OJL https://github.com/Serapieum-of-alex/hpc/tarball/main

Once you have a copy of the source, you can install it with:

python -m pip install .

To install directly from GitHub (from the HEAD of the main branch):

pip install git+https://github.com/Serapieum-of-alex/hpc.git

or from Github from a specific release:

pip install git+https://github.com/Serapieum-of-alex/hpc.git@{release}

If you are planning to make changes and contribute to the development of hpc, it is best to make a git clone of the repository, and do an editable install in the location of your clone. This will not move a copy to your Python installation directory, but instead create a link in your Python installation pointing to the folder you installed it from, such that any changes you make there are directly reflected in your install.

git clone https://github.com/Serapieum-of-alex/hpc.git
cd hpc
pip install -e .

Check if the installation is successful#

To check if the install is successful, try importing the package:

import hpc
print(hpc.__version__)

This should run without errors and display the version number.

Note

This documentation was generated on 2025-07-24

Documentation for the development version: https://hpc.readthedocs.org/en/latest/

Documentation for the stable version: https://hpc.readthedocs.org/en/stable/