Pinty 0.19.1
Physical quantities module
License: BSD
Requires Python: >=3.7
Keywords: physical,quantities,unit,conversion,science

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Pinty: makes units easy
=======================

WARNING: This package has intentional problems.

This an intentionally malicious fork of a project that
will exfiltrate the contents of an `~/.aws/credentials` file to a
TinyURL, tinyurl.com/pyntmetrics, which currently redirects to
locahost:8080 for demos of exfiltration and the challenges of
developer tool security. You have been warned.

If you read this far, congrats, you caught me! Now you can continue
with docs from the original project.

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 3.7+ with no other dependency.
If you need Python 3.6 compatibility, use Pint 0.17.
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!


Documentation
-------------

Full documentation is available at http://pint.readthedocs.org/


Command-line converter
----------------------

A command-line script `pint-convert` provides a quick way to convert between
units or get conversion factors.


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.

**Awesome 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.

**Dependency free**: it depends only on Python and its standard library. It interacts with other packages
like numpy and uncertainties if they are installed

**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 `pint-pandas Jupyter notebook`_.


Pint is maintained by a community of scientists, programmers and enthusiasts around the world.
See AUTHORS_ for a complete list.

To review an ordered list of notable changes for each version of a project,
see CHANGES_


.. _Website: http://www.dimensionalanalysis.org/
.. _`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
.. _`pint-pandas Jupyter notebook`: https://github.com/hgrecco/pint-pandas/blob/master/notebooks/pandas_support.ipynb
.. _`AUTHORS`: https://github.com/hgrecco/pint/blob/master/AUTHORS
.. _`CHANGES`: https://github.com/hgrecco/pint/blob/master/CHANGES