Pint: makes units easy
Pint is a Python package to define, operate and manipulate physical quantities: the product of a numerical value and a unit of measurement. It allows arithmetic operations between them and conversions from and to different units.
It is distributed with a comprehensive list of physical units, prefixes and constants. Due to its modular design, you can extend (or even rewrite!) the complete list without changing the source code. It supports a lot of numpy mathematical operations without monkey patching or wrapping numpy.
It has a complete test coverage. It runs in Python 2.7 and 3.3+ with no other dependency. It is licensed under BSD.
It is extremely easy and natural to use:
>>> import pint >>> ureg = pint.UnitRegistry() >>> 3 * ureg.meter + 4 * ureg.cm <Quantity(3.04, 'meter')>
and you can make good use of numpy if you want:
>>> import numpy as np >>> [3, 4] * ureg.meter + [4, 3] * ureg.cm <Quantity([ 3.04 4.03], 'meter')> >>> np.sum(_) <Quantity(7.07, 'meter')>
To install Pint, simply:
$ pip install pint
or utilizing conda, with the conda-forge channel:
$ conda install -c conda-forge pint
and then simply enjoy it!
Full documentation is available at http://pint.readthedocs.org/
Although there are already a few very good Python packages to handle physical quantities, no one was really fitting my needs. Like most developers, I programed Pint to scratch my own itches.
- Unit parsing: prefixed and pluralized forms of units are recognized without explicitly defining them. In other words: as the prefix kilo and the unit meter are defined, Pint understands kilometers. This results in a much shorter and maintainable unit definition list as compared to other packages.
- Standalone unit definitions: units definitions are loaded from simple and easy to edit text file. Adding and changing units and their definitions does not involve changing the code.
- Advanced string formatting: a quantity can be formatted into string using PEP 3101 syntax. Extended conversion flags are given to provide latex and pretty formatting.
- Small codebase: small and easy to maintain with a flat hierarchy.
- Dependency free: it depends only on Python and its standard library.
- Python 2 and 3: A single codebase that runs unchanged in Python 2.7 and Python 3.3+.
- Advanced NumPy support: While NumPy is not a requirement for Pint, when available ndarray methods and ufuncs can be used in Quantity objects.