https://github.com/tfiers/unitlib

📐 Physical units for NumPy arrays \ ⏱ Fast • Simple • High voltage
https://github.com/tfiers/unitlib

numpy python scientific-computing unitlib units

Last synced: 6 days ago
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📐 Physical units for NumPy arrays \ ⏱ Fast • Simple • High voltage

• Host: GitHub
• URL: https://github.com/tfiers/unitlib
• Owner: tfiers
• Created: 2020-09-11T16:03:00.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2020-11-19T09:27:37.000Z (almost 4 years ago)
• Last Synced: 2024-11-02T03:35:41.070Z (17 days ago)
• Topics: numpy, python, scientific-computing, unitlib, units
• Language: Python
• Homepage:
• Size: 171 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: ReadMe.md

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README

        
# 📐unitlib

- Physical units for NumPy arrays.

- Fast, simple, high voltage ⚡

## Why

Unitlib was born out of frustration with other Python unit packages.

Those packages work well for toy experiments, but they greatly slow down your code.

This makes their use unfeasible for even moderate scale scientific simulations.

## Installation

```

$ pip install unitlib

```

This will get you the

[![latest release on PyPI](https://img.shields.io/pypi/v/unitlib.svg?label=latest%20release%20on%20PyPI:)](https://pypi.python.org/pypi/unitlib/)

Unitlib is tested on Python versions 3.9 down to 3.6, on Windows, Linux and MacOS.

## For developers

The following indicates whether the latest commit on the main branch passes all tests:

[![CI status](https://github.com/tfiers/unitlib/workflows/CI/badge.svg)](https://github.com/tfiers/unitlib/actions)

(This only pertains to development code. The Unitlib versions on PyPI

pass all tests on release, of course).