Minimal, robust Python library for any math expressions
Project description
Minimal. Single function. No dependencies. You give a string with a numeric expression; it returns a float.
Install
pip install expreval
Quick use
from expreval import evaluate
evaluate("sin(pi/2) + log(e)") # 2.0
CLI:
expreval "sin(pi/4)**2"
What works now
- Numbers: int / float literals
- Operators: + - * / % ** and unary + -
- Grouping: ( )
- Names: pi, e, any function from the standard
mathmodule (sin, cos, sqrt, log, ...) - Simple function calls with positional arguments only
That is all - for now.
Safety (current scope)
Only a hand‑written walk over Python's ast for a very small subset. No attribute access, no imports, no keywords, no assignments, no lambdas, no comprehensions. If it's not listed above it should raise an error.
API
evaluate(expression: str) -> float
Returns a float (even if you pass an int literal). Raises standard Python exceptions (NameError, TypeError, etc.) for invalid input.
Examples
evaluate("2*(3+4)-5/2") # 11.5
evaluate("sin(pi/6)**2") # 0.249999... (floating point)
evaluate("sqrt(2)**2") # 2.000000...
Why
Original itch: certain very large numeric expressions (or results) caused numexpr to raise errors in our workflow. For simple scalar math that shouldn't fail, we just needed a tiny, predictable evaluator that:
- Has zero heavy dependencies
- Doesn't optimize or chunk arrays (so no surprise shape / size limits)
- Always returns a plain Python float for valid math
- Is easy to audit (a short AST walk) and extend later if truly needed
So expreval exists to reliably handle those "big result" cases where bringing in numexpr (and hitting its internal limits) was overkill. If you only need quick scalar math, this keeps it boring and dependable.
Contributor Guide
uv venv
uv sync
# make changes and then run these
# to create coverage logo and changelogs
.\scripts\update.sh
# (Optional)to bump version for release
uv run scripts\bump_version.py <X.Y.Z>
License
MIT. See LICENSE.
Project details
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