QuantiPhy — Physical Quantities
===============================
|downloads| |build status| |coverage| |rtd status| |pypi version| |anaconda version| |python version|
| Author: Ken Kundert
| Version: 2.20
| Released: 2024-04-27
|
What?
-----
*QuantiPhy* is a Python library that offers support for physical quantities.
A quantity is the pairing of a number and a unit of measure that indicates the
amount of some measurable thing. *QuantiPhy* provides quantity objects that
keep the units with the number, making it easy to share them as single object.
They subclass float and so can be used anywhere a real number is appropriate.
Why?
----
*QuantiPhy* naturally supports SI scale factors, which are widely used in
science and engineering. SI scale factors make it possible to cleanly represent
both very large and very small quantities in a form that is both easy to read
and write. While generally better for humans, no general programming language
provides direct support for reading or writing quantities with SI scale factors,
making it difficult to write numerical software that communicates effectively
with people. *QuantiPhy* addresses this deficiency, making it natural and
simple to both input and output physical quantities.
Features
--------
- Flexibly reads amounts with units and SI scale factors.
- Quantities subclass the *float* class and so can be used as conventional
numbers.
- Generally includes the units when printing or converting to strings and by
default employs SI scale factors.
- Flexible unit conversion and scaling is supported to make it easy to convert
to or from any required form.
- Supports the binary scale factors (*Ki*, *Mi*, etc.) along with the normal SI
scale factors (*k*, *M*, etc.).
- When a quantity is created from a string, the actual digits specified can be
used in any output, eliminating any loss of precision.
Alternatives
------------
There are a considerable number of Python packages dedicated to units and
quantities (`alternatives <https://kdavies4.github.io/natu/seealso.html>`_).
However, as a rule, they focus on the units rather than the scale factors. In
particular, they build a system of units that you are expected to use throughout
your calculations. These packages demand a high level of commitment from their
users and in turn provide unit consistency and built-in unit conversions.
In contrast, *QuantiPhy* treats units basically as documentation. They are
simply strings that are attached to quantities largely so they can be presented
to the user when the values are printed. As such, *QuantiPhy* is a light-weight
package that demands little from the user. It is used when inputting and
outputting values, and then only when it provides value. As a result, it
provides a simplicity in use that cannot be matched by the other packages.
In addition, these alternative packages generally build their unit systems upon
the `SI base units <https://en.wikipedia.org/wiki/SI_base_unit>`_, which tends
to restrict usage to physical quantities with static conversion factors. They
are less suited to non-physical quantities or conversion factors that change
dynamically, such as with currencies. *QuantiPhy* gracefully handles all of
these cases.
Quick Start
-----------
You can find the documentation on `ReadTheDocs
<https://quantiphy.readthedocs.io>`_. Install with::
pip3 install --user quantiphy
Requires Python 3.6 or newer. If you using an earlier version of Python,
install version 2.10 of *QuantiPhy*.
You can find the full documentation `here <https://quantiphy.readthedocs.io>`_.
You use *Quantity* to convert numbers and units in various forms to quantities:
.. code-block:: python
>>> from quantiphy import Quantity
>>> Tclk = Quantity(10e-9, 's')
>>> print(Tclk)
10 ns
>>> Fhy = Quantity('1420.405751786 MHz')
>>> print(Fhy)
1.4204 GHz
>>> Rsense = Quantity('1e-4Ω')
>>> print(Rsense)
100 uΩ
>>> cost = Quantity('$11_200_000')
>>> print(cost)
$11.2M
>>> Tboil = Quantity('212 °F', scale='°C')
>>> print(Tboil)
100 °C
Once you have a quantity, there are a variety of ways of accessing aspects of
the quantity:
.. code-block:: python
>>> Tclk.real
1e-08
>>> float(Fhy)
1420405751.786
>>> 2*cost
22400000.0
>>> Rsense.units
'Ω'
>>> str(Tboil)
'100 °C'
You can use the *render* method to flexibly convert the quantity to a string:
.. code-block:: python
>>> Tclk.render()
'10 ns'
>>> Tclk.render(show_units=False)
'10n'
>>> Tclk.render(form='eng', show_units=False)
'10e-9'
>>> Fhy.render(prec=8)
'1.42040575 GHz'
>>> Tboil.render(scale='°F')
'212 °F'
The *fixed* method is a variant that specializes in rendering numbers without
scale factors or exponents:
.. code-block:: python
>>> cost.fixed(prec=2, show_commas=True, strip_zeros=False)
'$11,200,000.00'
You can use the string format method or the new format strings to flexibly
incorporate quantity values into strings:
.. code-block:: python
>>> f'{Fhy}'
'1.4204 GHz'
>>> f'{Fhy:.6}'
'1.420406 GHz'
>>> f'❬{Fhy:<15.6}❭'
'❬1.420406 GHz ❭'
>>> f'❬{Fhy:>15.6}❭'
'❬ 1.420406 GHz❭'
>>> f'{cost:#,.2P}'
'$11,200,000.00'
>>> f'Boiling point of water: {Tboil:s}'
'Boiling point of water: 100 °C'
>>> f'Boiling point of water: {Tboil:s°F}'
'Boiling point of water: 212 °F'
*QuantiPhy* has many more features and capabilities. For more information, view
the `documentation <https://quantiphy.readthedocs.io>`_.
.. |downloads| image:: https://pepy.tech/badge/quantiphy/month
:target: https://pepy.tech/project/quantiphy
.. |rtd status| image:: https://img.shields.io/readthedocs/quantiphy.svg
:target: https://quantiphy.readthedocs.io/en/latest/?badge=latest
.. |build status| image:: https://github.com/KenKundert/quantiphy/actions/workflows/build.yaml/badge.svg
:target: https://github.com/KenKundert/quantiphy/actions/workflows/build.yaml
.. |coverage| image:: https://coveralls.io/repos/github/KenKundert/quantiphy/badge.svg?branch=master
:target: https://coveralls.io/github/KenKundert/quantiphy?branch=master
.. |pypi version| image:: https://img.shields.io/pypi/v/quantiphy.svg
:target: https://pypi.python.org/pypi/quantiphy
.. |anaconda version| image:: https://anaconda.org/conda-forge/quantiphy/badges/version.svg
:target: https://anaconda.org/conda-forge/quantiphy
.. |python version| image:: https://img.shields.io/pypi/pyversions/quantiphy.svg
:target: https://pypi.python.org/pypi/quantiphy/
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"description": "QuantiPhy \u2014 Physical Quantities\n===============================\n\n|downloads| |build status| |coverage| |rtd status| |pypi version| |anaconda version| |python version|\n\n| Author: Ken Kundert\n| Version: 2.20\n| Released: 2024-04-27\n|\n\n\nWhat?\n-----\n\n*QuantiPhy* is a Python library that offers support for physical quantities. \nA quantity is the pairing of a number and a unit of measure that indicates the \namount of some measurable thing. *QuantiPhy* provides quantity objects that \nkeep the units with the number, making it easy to share them as single object. \nThey subclass float and so can be used anywhere a real number is appropriate.\n\n\nWhy?\n----\n\n*QuantiPhy* naturally supports SI scale factors, which are widely used in \nscience and engineering. SI scale factors make it possible to cleanly represent \nboth very large and very small quantities in a form that is both easy to read \nand write. While generally better for humans, no general programming language \nprovides direct support for reading or writing quantities with SI scale factors, \nmaking it difficult to write numerical software that communicates effectively \nwith people. *QuantiPhy* addresses this deficiency, making it natural and \nsimple to both input and output physical quantities.\n\n\nFeatures\n--------\n\n- Flexibly reads amounts with units and SI scale factors.\n- Quantities subclass the *float* class and so can be used as conventional \n numbers.\n- Generally includes the units when printing or converting to strings and by \n default employs SI scale factors.\n- Flexible unit conversion and scaling is supported to make it easy to convert \n to or from any required form.\n- Supports the binary scale factors (*Ki*, *Mi*, etc.) along with the normal SI \n scale factors (*k*, *M*, etc.).\n- When a quantity is created from a string, the actual digits specified can be \n used in any output, eliminating any loss of precision.\n\n\nAlternatives\n------------\n\nThere are a considerable number of Python packages dedicated to units and \nquantities (`alternatives <https://kdavies4.github.io/natu/seealso.html>`_). \nHowever, as a rule, they focus on the units rather than the scale factors. In \nparticular, they build a system of units that you are expected to use throughout \nyour calculations. These packages demand a high level of commitment from their \nusers and in turn provide unit consistency and built-in unit conversions.\n\nIn contrast, *QuantiPhy* treats units basically as documentation. They are \nsimply strings that are attached to quantities largely so they can be presented \nto the user when the values are printed. As such, *QuantiPhy* is a light-weight \npackage that demands little from the user. It is used when inputting and \noutputting values, and then only when it provides value. As a result, it \nprovides a simplicity in use that cannot be matched by the other packages.\n\nIn addition, these alternative packages generally build their unit systems upon \nthe `SI base units <https://en.wikipedia.org/wiki/SI_base_unit>`_, which tends \nto restrict usage to physical quantities with static conversion factors. They \nare less suited to non-physical quantities or conversion factors that change \ndynamically, such as with currencies. *QuantiPhy* gracefully handles all of \nthese cases.\n\n\nQuick Start\n-----------\n\nYou can find the documentation on `ReadTheDocs\n<https://quantiphy.readthedocs.io>`_. Install with::\n\n pip3 install --user quantiphy\n\nRequires Python 3.6 or newer. If you using an earlier version of Python,\ninstall version 2.10 of *QuantiPhy*.\n\nYou can find the full documentation `here <https://quantiphy.readthedocs.io>`_.\n\nYou use *Quantity* to convert numbers and units in various forms to quantities:\n\n.. code-block:: python\n\n >>> from quantiphy import Quantity\n\n >>> Tclk = Quantity(10e-9, 's')\n >>> print(Tclk)\n 10 ns\n\n >>> Fhy = Quantity('1420.405751786 MHz')\n >>> print(Fhy)\n 1.4204 GHz\n\n >>> Rsense = Quantity('1e-4\u03a9')\n >>> print(Rsense)\n 100 u\u03a9\n\n >>> cost = Quantity('$11_200_000')\n >>> print(cost)\n $11.2M\n\n >>> Tboil = Quantity('212 \u00b0F', scale='\u00b0C')\n >>> print(Tboil)\n 100 \u00b0C\n\nOnce you have a quantity, there are a variety of ways of accessing aspects of \nthe quantity:\n\n.. code-block:: python\n\n >>> Tclk.real\n 1e-08\n\n >>> float(Fhy)\n 1420405751.786\n\n >>> 2*cost\n 22400000.0\n\n >>> Rsense.units\n '\u03a9'\n\n >>> str(Tboil)\n '100 \u00b0C'\n\nYou can use the *render* method to flexibly convert the quantity to a string:\n\n.. code-block:: python\n\n >>> Tclk.render()\n '10 ns'\n\n >>> Tclk.render(show_units=False)\n '10n'\n\n >>> Tclk.render(form='eng', show_units=False)\n '10e-9'\n\n >>> Fhy.render(prec=8)\n '1.42040575 GHz'\n\n >>> Tboil.render(scale='\u00b0F')\n '212 \u00b0F'\n\nThe *fixed* method is a variant that specializes in rendering numbers without \nscale factors or exponents:\n\n.. code-block:: python\n\n >>> cost.fixed(prec=2, show_commas=True, strip_zeros=False)\n '$11,200,000.00'\n\nYou can use the string format method or the new format strings to flexibly \nincorporate quantity values into strings:\n\n.. code-block:: python\n\n >>> f'{Fhy}'\n '1.4204 GHz'\n\n >>> f'{Fhy:.6}'\n '1.420406 GHz'\n\n >>> f'\u276c{Fhy:<15.6}\u276d'\n '\u276c1.420406 GHz \u276d'\n\n >>> f'\u276c{Fhy:>15.6}\u276d'\n '\u276c 1.420406 GHz\u276d'\n\n >>> f'{cost:#,.2P}'\n '$11,200,000.00'\n\n >>> f'Boiling point of water: {Tboil:s}'\n 'Boiling point of water: 100 \u00b0C'\n\n >>> f'Boiling point of water: {Tboil:s\u00b0F}'\n 'Boiling point of water: 212 \u00b0F'\n\n*QuantiPhy* has many more features and capabilities. For more information, view \nthe `documentation <https://quantiphy.readthedocs.io>`_.\n\n\n.. |downloads| image:: https://pepy.tech/badge/quantiphy/month\n :target: https://pepy.tech/project/quantiphy\n\n.. |rtd status| image:: https://img.shields.io/readthedocs/quantiphy.svg\n :target: https://quantiphy.readthedocs.io/en/latest/?badge=latest\n\n.. |build status| image:: https://github.com/KenKundert/quantiphy/actions/workflows/build.yaml/badge.svg\n :target: https://github.com/KenKundert/quantiphy/actions/workflows/build.yaml\n\n.. |coverage| image:: https://coveralls.io/repos/github/KenKundert/quantiphy/badge.svg?branch=master\n :target: https://coveralls.io/github/KenKundert/quantiphy?branch=master\n\n.. |pypi version| image:: https://img.shields.io/pypi/v/quantiphy.svg\n :target: https://pypi.python.org/pypi/quantiphy\n\n.. |anaconda version| image:: https://anaconda.org/conda-forge/quantiphy/badges/version.svg\n :target: https://anaconda.org/conda-forge/quantiphy\n\n.. |python version| image:: https://img.shields.io/pypi/pyversions/quantiphy.svg\n :target: https://pypi.python.org/pypi/quantiphy/\n\n\n",
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