# sympy/sympy

A computer algebra system written in pure Python

Repository: https://github.com/sympy/sympy
Canonical: https://ross.abutalabs.com/products/sympy
Homepage: https://sympy.org/
Language: Python
License: NOASSERTION
License Family: other
Topics: python, math, computer-algebra, science, hacktoberfest
Last push: 2026-08-26T18:09:39+00:00

## Health v2 (maintenance only)
Score: 70/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 16, longevity 100
- inputs: {"age_days": 5969, "days_push": 7, "days_rel": 493, "gap_med": 110.0, "n_releases_24m": 3}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 14891, forks 5455 (observed 2026-08-28T04:11:08.902106+00:00)

## What it is
SymPy is a computer algebra system (CAS) written in pure Python for symbolic mathematics. It provides capabilities for algebra, calculus, equation solving, series expansion, and more without requiring external dependencies.

## Use cases
- solve symbolic equations in python
- compute derivatives and integrals symbolically
- simplify algebraic expressions
- expand taylor series of a function
- work with matrices and linear algebra symbolically
- generate latex from math expressions

## When to choose
- you need exact symbolic math rather than floating-point numerics
- you want a pure-Python CAS with no compiled dependencies
- you're doing calculus, algebra, or equation solving in Python

## When to avoid
- you need fast numerical computation on large arrays (use NumPy)
- you need a full-featured commercial CAS like Mathematica for advanced work

## Facets
- artifact type: library
- maturity: stable
- function: math
- domain: mathematics, data-science
- platform: python, cross-platform
- tags: computer-algebra, symbolic-math, cas, pure-python, scientific-computing, algorithms

## Member repositories
- sympy/sympy (main) score 70

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:08.902106+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 2026-08-29T17:07:00.117022+00:00, confidence not recorded.
  - readme: https://github.com/sympy/sympy (fetched 2026-08-28T04:11:08.902106+00:00, sha df34587b3a61)
  - homepage: https://sympy.org/ (fetched 2026-08-29T08:04:59.899810+00:00, sha 02f22166e4ce)
  - registry_pypi: https://pypi.org/pypi/sympy/json (fetched 2026-08-29T08:04:59.902451+00:00, sha 20e186434a25)
- Data as of 2026-08-30T08:39:29.467469+00:00.