sympy
Computer algebra system (CAS) in Python
Install
sympy on PyPI
pip
pip install sympyuv
uv add sympypoetry
poetry add sympyPackage facts
| License | BSD (permissive) |
| Python support | supports the current Python release (>=3.9) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 1 — mpmath |
| Maintenance | actively maintained — 473 days since the last release |
| Last repo commit | |
| First released | |
| Popularity | one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-13) |
Evidence: sympy-1.14.0-py3-none-any.whl
Keywords: Math, CAS
About sympy
from the package's own PyPI description — quoted content, verbatim
SymPy
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[![SymPy...
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AI interpretation — verify before relying
AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page
SymPy is a Python computer algebra system (CAS) for symbolic mathematics, enabling manipulation and simplification of mathematical expressions, equations, and calculus operations.
Installation is straightforward with low friction; the package has a single runtime dependency (mpmath) and is actively maintained with recent releases.
SymPy is licensed under the permissive BSD license, allowing both commercial and private use with minimal restrictions, making it suitable for most projects without licensing concerns.
Usage
pip install sympy
from sympy import Symbol, cos
x = Symbol('x')
e = 1/cos(x)
print(e.series(x, 0, 10))
Requires Python 3.9 or later; mpmath is automatically installed as a runtime dependency.
Verdict: SymPy is a mature, actively maintained symbolic mathematics library with no known vulnerabilities, permissive licensing, and low installation friction. It is well-suited for scientific computing, mathematical research, and educational use across Python 3.9–3.13.
Needs verification
- Performance characteristics and computational limits for large or complex symbolic expressions.
- Compatibility and integration patterns with other scientific Python libraries.
- Memory footprint and scalability for production workloads involving many simultaneous symbolic operations.
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