impunity is a Python library consisting of a single decorator function designed to ensure consistency of physical quantities. Compared to other libraries (pint, etc.), it has a minimal overhead on performance because physical units are only manipulated through static analysis and disappear at runtime.
impunity is based on Python “flexible variable and function annotations” (PEP 593) and checks consistency between variables and arguments of functions. If physical units are consistent, impunity rewrites the code by automatically applying conversions in the code of the function.
impunity is compatible with regular type annotations, and functions decorated with impunity remain compatible with other static analysis tools and type checkers like mypy.
In most situations, impunity will only perform minimal sanity checks on your code at import time and not edit anything.
impunity is available on pip (and soon conda):
pip install impunity
For development purposes, clone the repository and use poetry:
git clone --depth=1 https://github.com/achevrot/impunity
cd impunity
poetry install
Full documentation available at [website]()
The most simple usage consists of using units placed as annotations: code is checked and rewritten if need be.
from impunity import impunity
def speed(distance: "m", time: "s") -> "m/s":
return distance / time
@impunity
def regular_conversion():
altitudes: "ft" = np.arange(0, 1000, 100)
duration: "mn" = 100
result = speed(altitudes, duration)
print(result) # results in m/s
result_imperial: "ft/mn" = speed(altitudes, duration)
print(result_imperial) # results in ft/mn
if __name__ == "__main__":
regular_conversion()
The check fails if units are inconsistent:
@impunity
def inconsistent_units():
temperatures: "K" = np.arange(0, 100, 10)
duration: "s" = 6000
return speed(temperatures, duration)
# Warning: "K" is not compatible with "m"
Only check for consistency, do not attempt to rewrite the code:
@impunity(rewrite=False) # only check for consistency
def regular_conversion():
pass
@impunity(rewrite="output.log") # check code output in an external file
def regular_conversion():
pass
Types can be used with the Annotated
keyword, which carries
from typing import Annotation
import numpy.types as npt
feet_array = Annotated[npt.ndarray[np.float64], "ft"]
altitudes: feet_array = np.arange(0, 1000, 100)
impunity is implemented and typed with Annotated
keywords.
Tests are supported by the unittest package.
Because AST manipulation can be tricky, continuous integration is ensured by Github Actions for:
We were searching for a pun with physical units. Things converged on im-pun-unit-y
.