:orphan:

Pint: makes units easy
======================

.. image:: _static/logo-full.jpg
   :alt: Pint: **physical quantities**
   :class: floatingflask

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:

.. code-block:: python

    >>> 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:

.. code-block:: python

    >>> 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:

.. code-block:: bash

    $ pip install pint

or utilizing conda, with the conda-forge channel:

.. code-block:: bash

    $ 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.


User Guide
----------

.. toctree::
    :maxdepth: 1

    getting
    tutorial
    numpy
    nonmult
    wrapping
    plotting
    serialization
    pitheorem
    contexts
    measurement
    defining
    performance
    systems


More information
----------------

.. toctree::
    :maxdepth: 1

    contributing
    faq


One last thing
--------------

.. epigraph::

 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 <ftp://ftp.hq.nasa.gov/pub/pao/reports/1999/MCO_report.pdf>`_



.. _`comprehensive list of physical units, prefixes and constants`: https://github.com/hgrecco/pint/blob/master/pint/default_en.txt
.. _`uncertainties package`: https://pythonhosted.org/uncertainties/
.. _`NumPy`: http://www.numpy.org/
.. _`PEP 3101`: https://www.python.org/dev/peps/pep-3101/
.. _`Babel`: http://babel.pocoo.org/
.. _`Pandas Extension Types`: https://pandas.pydata.org/pandas-docs/stable/extending.html#extension-types
.. _`Pandas Support Documentation`: ./pandas.rst
