# 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 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')>


## Quick Installation¶

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!

## Design principles¶

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 programmed 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 a text file which is simple and easy to edit. 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 symbolic, LaTeX and pretty formatting. Unit name translation is available if Babel is installed.

Free to choose the numerical type: You can use any numerical type (fraction, float, decimal, numpy.ndarray, etc). NumPy is not required but supported.

NumPy integration: When you choose to use a NumPy ndarray, its methods and ufuncs are supported including automatic conversion of units. For example numpy.arccos(q) will require a dimensionless q and the units of the output quantity will be radian.

Uncertainties integration: transparently handles calculations with quantities with uncertainties (like 3.14±0.01) meter via the uncertainties package.

Handle temperature: conversion between units with different reference points, like positions on a map or absolute temperature scales.

Small codebase: easy to maintain codebase 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+.

Pandas integration: Thanks to Pandas Extension Types it is now possible to use Pint with Pandas. Operations on DataFrames and between columns are units aware, providing even more convenience for users of Pandas DataFrames. For full details, see the Pandas Support Documentation.

When you choose to use a NumPy ndarray, its methods and ufuncs are supported including automatic conversion of units. For example numpy.arccos(q) will require a dimensionless q and the units of the output quantity will be radian.

## One last thing¶

The MCO MIB has determined that the root cause for the loss of the MCO spacecraft was the failure to use metric units in the coding of a ground software file, “Small Forces,” used in trajectory models. Specifically, thruster performance data in English units instead of metric units was used in the software application code titled SM_FORCES (small forces). The output from the SM_FORCES application code as required by a MSOP Project Software Interface Specification (SIS) was to be in metric units of Newtonseconds (N-s). Instead, the data was reported in English units of pound-seconds (lbf-s). The Angular Momentum Desaturation (AMD) file contained the output data from the SM_FORCES software. The SIS, which was not followed, defines both the format and units of the AMD file generated by ground-based computers. Subsequent processing of the data from AMD file by the navigation software algorithm therefore, underestimated the effect on the spacecraft trajectory by a factor of 4.45, which is the required conversion factor from force in pounds to Newtons. An erroneous trajectory was computed using this incorrect data.

Mars Climate Orbiter Mishap Investigation Phase I Report PDF