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A package for dimensional analysis calculations on floating-point values

Project description

Unitscalar: real-time verified dimensional analysis in Python

Basic validation

This package implements a unit-aware number data type that keeps track of units as an inseparable part of the number. Heavily inspired by Steve Byrnes' numericalunits

Valid Literals

UnitScalar uses custom-literals to hack support for custom literals into the language. These are defined for certain (arbitrary) unit strings as needed. At present:

Literal Unit String Example
x "" (N/A) 10 .x or 10.x
gMM g/mol 101.1.gMM
inch in 3.90.inch
psi psi 10.0.psi
lbf lbf 0.0.lbf
K K 1837.22.K

As a consequence of including this feature, unitscalar depends on the PIP package custom_literals. The latter mentioned warning about stability shouldn't affect downstream projects if the literals feature is not used.

Fair Warning

Briefly quoting the custom-literals README section on stability caveats:

This library relies almost entirely on implementation-specific behavior of the CPython interpreter. It is not guaranteed to work on all platforms, or on all versions of Python. It has been tested on common platforms (windows, ubuntu, macos) using python 3.7 through to 3.10, but while changes that would break the library are quite unlikely, they are not impossible either.

TODO List

  • Implement convert_to_units for output in another format (e.g. A to uA or N to lbf)
  • Vectorized artithmetic?
  • Write example code and fill out README

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