Name | Pint JSON |
Version |
0.23
JSON |
| download |
home_page | |
Summary | Physical quantities module |
upload_time | 2023-12-08 20:38:23 |
maintainer | |
docs_url | None |
author | |
requires_python | >=3.9 |
license | BSD |
keywords |
physical
quantities
unit
conversion
science
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
|
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:target: https://pypi.python.org/pypi/pint
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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 3.9+ 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!
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/development/extending.html#extension-types
.. _`pint-pandas Jupyter notebook`: https://github.com/hgrecco/pint-pandas/blob/master/notebooks/pint-pandas.ipynb
.. _`AUTHORS`: https://github.com/hgrecco/pint/blob/master/AUTHORS
.. _`CHANGES`: https://github.com/hgrecco/pint/blob/master/CHANGES
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Due to its modular design, you can extend (or even rewrite!)\nthe complete list without changing the source code. It supports a lot of\nnumpy mathematical operations **without monkey patching or wrapping numpy**.\n\nIt has a complete test coverage. It runs in Python 3.9+ with no other dependency.\nIt is licensed under BSD.\n\nIt is extremely easy and natural to use:\n\n.. code-block:: python\n\n >>> import pint\n >>> ureg = pint.UnitRegistry()\n >>> 3 * ureg.meter + 4 * ureg.cm\n <Quantity(3.04, 'meter')>\n\nand you can make good use of numpy if you want:\n\n.. code-block:: python\n\n >>> import numpy as np\n >>> [3, 4] * ureg.meter + [4, 3] * ureg.cm\n <Quantity([ 3.04 4.03], 'meter')>\n >>> np.sum(_)\n <Quantity(7.07, 'meter')>\n\n\nQuick Installation\n------------------\n\nTo install Pint, simply:\n\n.. code-block:: bash\n\n $ pip install pint\n\nor utilizing conda, with the conda-forge channel:\n\n.. code-block:: bash\n\n $ conda install -c conda-forge pint\n\nand then simply enjoy it!\n\n\nDocumentation\n-------------\n\nFull documentation is available at http://pint.readthedocs.org/\n\n\nCommand-line converter\n----------------------\n\nA command-line script `pint-convert` provides a quick way to convert between\nunits or get conversion factors.\n\n\nDesign principles\n-----------------\n\nAlthough there are already a few very good Python packages to handle physical\nquantities, no one was really fitting my needs. 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