# mpmath/mpmath

Python library for arbitrary-precision floating-point arithmetic

Repository: https://github.com/mpmath/mpmath
Canonical: https://ross.abutalabs.com/products/mpmath
Homepage: http://mpmath.org
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: python, arbitrary-precision, multiprecision, floating-point, special-functions, numerical-integration, numerical-methods, plotting, complex-numbers, ordinary-differential-equations, numerical-optimization
Last push: 2026-09-02T05:29:35+00:00

## Health v2 (maintenance only)
Score: 91/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 74, longevity 100
- inputs: {"age_days": 5383, "days_push": 0, "days_rel": 172, "gap_med": 19, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1203, forks 217 (observed 2026-09-03T02:15:15.300040+00:00)

## What it is
mpmath is a pure-Python library for arbitrary-precision real and complex floating-point arithmetic with no required dependencies beyond Python 3. It also provides advanced mathematical capabilities such as special functions, numerical integration, differentiation, ODE solving, and root finding at any chosen precision.

## Use cases
- compute pi or other constants to hundreds or thousands of digits
- evaluate special functions at high precision
- numerically integrate functions with arbitrary precision
- replace Python float/complex and math/cmath with arbitrary-precision versions
- solve ordinary differential equations numerically with controlled precision
- perform numerical optimization and root finding at high precision
- use as the arithmetic backend for SymPy or Sage

## When to choose
- you need more precision than hardware floats provide
- you need reliable evaluation of special functions or quadrature at high precision
- you want a dependency-free pure-Python math library
- you are building a computer algebra system or need exact-ish numerics

## When to avoid
- you only need fast double-precision arithmetic (use NumPy or the math module)
- you need high-performance vectorized array computation
- you need interval or exact rational arithmetic (use other libraries)

## Facets
- artifact type: library
- maturity: stable
- function: math, data-science
- domain: mathematics, developer-tools
- platform: python, cross-platform
- tags: arbitrary-precision, floating-point, special-functions, numerical-integration, complex-numbers, numerical-methods, sympy, algorithms

## Member repositories
- mpmath/mpmath (main) score 91

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:15.300040+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:21:11.049092+00:00, confidence not recorded.
  - readme: https://github.com/mpmath/mpmath (fetched 2026-09-03T02:15:15.300040+00:00, sha 9d694812df6c)
  - homepage: http://mpmath.org (fetched 2026-08-29T12:28:46.546551+00:00, sha 2c5756b875e4)
  - registry_pypi: https://pypi.org/pypi/mpmath/json (fetched 2026-08-29T12:28:46.549261+00:00, sha f75813cdd8ba)
- Data as of 2026-08-30T08:39:29.467469+00:00.