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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 software that communicates effectively with humans.
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.
Provides a small but extensible collection of physical constants.
Supports the binary scale factors (Ki, Mi, etc.) along with the normal SI scale factors (k, M, etc.).

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.

Quick Start

You can find the documentation on ReadTheDocs <https://quantiphy.readthedocs.io>_. Install with::

pip3 install --user quantiphy

Requires Python 3.5 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'

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'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>_.

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