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counted-float

This Python package provides functionality for...

  • counting floating point operations (FLOPs) of numerical algorithms implemented in plain Python, optionally weighted by their relative cost of execution
  • running benchmarks to estimate the relative cost of executing various floating-point operations (requires numba optional dependency for achieving accurate results)

The target application area is evaluation of research prototypes of numerical algorithms where (weighted) flop counting can be useful for estimating total computational cost, in cases where benchmarking a compiled version (C, Rust, ...) is not feasible or desirable.

Flop weights are computed using a highly curated dataset spanning a wide range of modern CPUs:

  • 19 benchmarks, 16 spec sheets, 12 third party measurements (Agner Fog, uops.info)
  • covering x86 (Intel, AMD) and ARM (Apple, AWS, Azure) architectures

Full documentation: counted-float.readthedocs.io

Installation

Use your favorite package manager such as uv or pip:

pip install counted-float           # install without numba optional dependency
pip install counted-float[numba]    # install with numba optional dependency

Numba is optional due to its relatively large size (40-50MB, including llvmlite), but without it, benchmarks will not be reliable (but will still run, but not in jit-compiled form).

Quick start

CountedFloat is a drop-in replacement for the built-in float; it is "contagious", so results of math operations involving a CountedFloat stay CountedFloat:

from counted_float import CountedFloat

cf = CountedFloat(1.3)
f = 2.8

result = cf + f  # result = CountedFloat(4.1)

is_float_1 = isinstance(cf, float)  # True
is_float_2 = isinstance(result, float)  # True

FLOPs performed by CountedFloat values are counted while a FlopCountingContext is active:

from counted_float import CountedFloat, FlopCountingContext

cf1 = CountedFloat(1.73)
cf2 = CountedFloat(2.94)

with FlopCountingContext() as ctx:
    _ = cf1 * cf2
    _ = cf1 + cf2

counts = ctx.flop_counts()   # {FlopType.MUL: 1, FlopType.ADD: 1}
counts.total_count()         # 2

Documentation

The documentation site covers the rest:

Project links

Data verified by PyPI on Jul 11, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (2.6.0)

1 maintainer

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Avatar for bert_pluymers from gravatar.com bert_pluymers

GitHub Statistics

Data verified by PyPI on Jul 11, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

Apache Software License

Requires

Python >=3.11

Provides Extra

cli numba

Classifiers

Report project as malware

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