unitful 1.1.0

Physical units as first-class values with dimensional analysis

unitful

Physical units as first-class Python values

Attach a unit to any number, arithmetic propagates units automatically Dimension mismatches raise DimensionError at runtime instead of producing silently wrong results

Getting Started

pip install unitful

from unitful import m, s, kg, km, h

distance = 100 * m
time     = 9.58 * s
speed    = distance / time        # Quantity(10.44, 'm/s')

speed.to(km / h)                  # Quantity(37.58, 'km/h')
speed.to(kg)                      # DimensionError: [Length/Time] != [Mass]

Features

• Dimension checking: all arithmetic validates physical dimensions and raises DimensionError with a clear message on mismatch
• Unit conversion: .to(unit) converts between compatible units, including offset temperature scales (degC, degF, K)
• NumPy integration: np.array([...]) * m returns a QuantityArray; ufuncs and reduction functions (np.mean, np.sum, etc.) preserve units
• Decorators: @requires and @returns enforce dimensions on function arguments and return values
• Custom units and dimensions: define_unit and new_dimension extend the registry at runtime
• Serialization: to_json / from_json for plain-dict round-trips; pickle and copy work without extra setup
• Formatting: f"{q:.2f~P}" (Unicode), f"{q:.2f~L}" (LaTeX), f"{q:.2f~H}" (HTML)

Requirements

Python 3.10 or later. NumPy is optional; install it with:

pip install "unitful[numpy]"

License

MIT