Sympy

SymPy is a Python computer algebra system and symbolic mathematics library. It performs algebraic manipulations, calculus, and equation solving using symbolic representations to achieve exact computations rather than numerical approximations.

The library includes a LaTeX expression parser that converts mathematical strings into symbolic representations for computation and formula manipulation. It also incorporates a mathematical benchmarking suite to measure execution speed and detect performance regressions across different software versions.

The system provides capabilities for automated math verification and scientific software benchmarking. It also supports LaTeX equation processing for the simplification and evaluation of mathematical notation.

Features

Computer Algebra Systems - Implements a full computer algebra system for complex mathematical formulas and proofs in Python.
Algebraic Reduction Rules - Transforms complex expressions into simpler forms by applying predefined algebraic rewrite rules.
Computer Algebra Systems - Provides a comprehensive computer algebra system for symbolic mathematics using pure Python.
Symbolic Computation Engines - Performs algebraic manipulations and solves equations using symbolic representations instead of numerical approximations.
Symbolic Expression Manipulators - Provides a pure-Python engine for algebraically transforming mathematical expressions without numerical evaluation.
Expression - Represents mathematical formulas as hierarchical trees of objects for symbolic manipulation and evaluation.
Symbolic LaTeX Processing - Converts mathematical notation from LaTeX strings into computable forms for simplification and evaluation.
LaTeX Expression Parsers - Provides a tool for converting LaTeX mathematical strings into symbolic representations for computation.
Numerical Backend Dispatchers - Routes symbolic expressions to different external numerical libraries for high-precision or fast floating-point computation.
LaTeX Parsers - Converts mathematical LaTeX strings into symbolic representations for computation and formula manipulation.
Mathematical Verification - Provides test suites to ensure the correctness of symbolic computations and mathematical identities.
Lazy Evaluation Patterns - Defers computation of complex symbolic results until a numerical value or simplified form is explicitly requested.
Mathematical Benchmarking Suites - Ships a performance tracking system that measures execution speed and detects regressions in math operations.
Scientific Computing - Library for symbolic mathematics.
Data Analysis Visualization - Symbolic mathematics library for Python.
Numerische Bibliotheken - Library for symbolic mathematics and algebraic computation.
Statistical Modeling - Library for symbolic mathematics and algebraic computation.
Developer Tools - Library for symbolic mathematics.
Python Projects - Listed in the “Python Projects” section of the Awesome For Beginners awesome list.
Scientific Computing - Listed in the “Scientific Computing” section of the Awesome Python awesome list.

Star-Verlauf

sympysympy

Name: sympy/sympy
Author: sympy

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14,683 Stars5,324 ForksPython8 Aufrufesympy.org

Sympy

Features

Computer Algebra Systems - Implements a full computer algebra system for complex mathematical formulas and proofs in Python.
Algebraic Reduction Rules - Transforms complex expressions into simpler forms by applying predefined algebraic rewrite rules.
Computer Algebra Systems - Provides a comprehensive computer algebra system for symbolic mathematics using pure Python.
Symbolic Computation Engines - Performs algebraic manipulations and solves equations using symbolic representations instead of numerical approximations.
Symbolic Expression Manipulators - Provides a pure-Python engine for algebraically transforming mathematical expressions without numerical evaluation.
Expression - Represents mathematical formulas as hierarchical trees of objects for symbolic manipulation and evaluation.
Symbolic LaTeX Processing - Converts mathematical notation from LaTeX strings into computable forms for simplification and evaluation.
LaTeX Expression Parsers - Provides a tool for converting LaTeX mathematical strings into symbolic representations for computation.
Numerical Backend Dispatchers - Routes symbolic expressions to different external numerical libraries for high-precision or fast floating-point computation.
LaTeX Parsers - Converts mathematical LaTeX strings into symbolic representations for computation and formula manipulation.
Mathematical Verification - Provides test suites to ensure the correctness of symbolic computations and mathematical identities.
Lazy Evaluation Patterns - Defers computation of complex symbolic results until a numerical value or simplified form is explicitly requested.
Mathematical Benchmarking Suites - Ships a performance tracking system that measures execution speed and detects regressions in math operations.
Scientific Computing - Library for symbolic mathematics.
Data Analysis Visualization - Symbolic mathematics library for Python.
Numerische Bibliotheken - Library for symbolic mathematics and algebraic computation.
Statistical Modeling - Library for symbolic mathematics and algebraic computation.
Developer Tools - Library for symbolic mathematics.
Python Projects - Listed in the “Python Projects” section of the Awesome For Beginners awesome list.
Scientific Computing - Listed in the “Scientific Computing” section of the Awesome Python awesome list.

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Häufig gestellte Fragen

Was macht sympy/sympy?

Was sind die Hauptfunktionen von sympy/sympy?

Die Hauptfunktionen von sympy/sympy sind: Computer Algebra Systems, Algebraic Reduction Rules, Symbolic Computation Engines, Symbolic Expression Manipulators, Expression, Symbolic LaTeX Processing, LaTeX Expression Parsers, Numerical Backend Dispatchers.

Welche Open-Source-Alternativen gibt es zu sympy/sympy?

Open-Source-Alternativen zu sympy/sympy sind unter anderem: pymc-devs/pymc — PyMC is a Bayesian probabilistic programming framework used for building probabilistic models and performing Bayesian… josdejong/mathjs — Math.js is a comprehensive JavaScript library for scientific, complex, and arbitrary precision calculations. It… statsmodels/statsmodels — Statsmodels is a comprehensive Python library designed for statistical modeling, econometric research, and data… norvig/paip-lisp — This project is a comprehensive Lisp AI implementation library that provides reference implementations for various… numpy/numpy — NumPy is a foundational library for scientific computing in Python, providing a comprehensive framework for managing… scipy/scipy — SciPy is a scientific computing library for Python that provides a comprehensive collection of mathematical algorithms…