pyeqsolver 1.0.0

A Python package for solving linear equations and performing 2x2 and 3x3 matrix operations

🧮 EqSolver

A comprehensive Python package for matrix operations and solving linear equations

Features • Installation • Quick Start • Documentation • Contributing

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✨ Features

🧮 Matrix Operations

• ➕ Addition and subtraction
• ✖️ Matrix and scalar multiplication
• ➗ Matrix and scalar division
• 🔢 Determinant calculation
• 🔄 Adjoint and inverse matrix computation

🔢 Linear Equation Solver

• 📐 Solve 2×2 and 3×3 systems
• 🎯 Cramer's Rule and Matrix Inversion
• 📝 Parse equations from strings
• 🎲 Supports fractions for exact results

🛡️ Robust Error Handling

• ❌ Invalid or singular matrices
• 🚫 Division by zero
• ⚠️ Inconsistent or malformed equations

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⚙️ Installation

Quick Install

pip install eqsolver

Development Installation

git clone https://github.com/Hammail-Riaz/eqsolver.git
cd eqsolver
pip install -e .

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🚀 Quick Start

from eqsolver import Matrices2x2, LinearEquationsSolver

# Create a 2x2 matrix calculator
calc = Matrices2x2()

# Define matrices
A = [[2, 3], [1, 4]]
B = [[5, 2], [3, 1]]

# Perform operations
result = calc.add(A, B)
print(result)  # [[7.0, 5.0], [4.0, 5.0]]

# Solve linear equations
solver = LinearEquationsSolver("2x + 4y = 5, 3x - 3y = -1")
solution = solver.solve('cramer')

for var, val in solution:
    print(f"{var} = {val}")
# Output:
# x = 11/18
# y = 17/18

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📘 Documentation

Table of Contents

1. 2×2 Matrix Operations
2. 3×3 Matrix Operations
3. Linear Equation Solver
4. Error Handling
5. API Reference

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🧩 2×2 Matrix Operations

from eqsolver import Matrices2x2

calc = Matrices2x2()
A = [[2, 3], [1, 4]]
B = [[5, 2], [3, 1]]

Operation	Example	Output
Addition	calc.add(A, B)	[[7.0, 5.0], [4.0, 5.0]]
Subtraction	calc.subtract(A, B)	[[-3.0, 1.0], [-2.0, 3.0]]
Multiplication	calc.multiply(A, B)	Matrix product
Scalar Multiply	calc.multiply(A, num=2)	All elements × 2
Determinant	calc.determinant(A)	5.0
Adjoint	calc.adjoint(A)	[[4.0, -3.0], [-1.0, 2.0]]
Inverse	calc.multiplicative_inverse(A)	[[0.8, -0.6], [-0.2, 0.4]]

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🧮 3×3 Matrix Operations

from eqsolver import Matrices3x3

calc = Matrices3x3()
C = [[1, 2, 3], [0, 1, 4], [5, 6, 0]]
D = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]  # Identity matrix

Operation	Example	Output
Addition	calc.add(C, D)	[[2, 2, 3], [0, 2, 4], [5, 6, 1]]
Subtraction	calc.subtract(C, D)	Matrix difference
Determinant	calc.determinant(C)	1.0
Adjoint	calc.adjoint(C)	[[-24, 18, 5], [20, -15, -4], [-5, 4, 1]]
Inverse	calc.multiplicative_inverse(C)	[[-24, 18, 5], [20, -15, -4], [-5, 4, 1]]

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🔍 Linear Equation Solver

Solve systems of linear equations with ease!

Example: 2-Variable System

from eqsolver import LinearEquationsSolver

# Define your equations as a string
solver = LinearEquationsSolver("2x + 4y = 5, 3x - 3y = -1")

# Solve using Cramer's Rule
solution = solver.solve('cramer')

for var, val in solution:
    print(f"{var} = {val}")

Output:

x = 11/18
y = 17/18

Example: 3-Variable System

equations = "x + 2y + 3z = 6, 2x - y + z = 3, 3x + y - z = 4"
solver = LinearEquationsSolver(equations)

# Solve using matrix inversion
solution = solver.solve('inverse')

for var, val in solution:
    print(f"{var} = {val}")

Get Coefficient Matrix

solver = LinearEquationsSolver("2x + 4y = 5, 3x - 3y = -1")
A, b = solver.A()  # Returns coefficient matrix and constants vector

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⚠️ Error Handling

EqSolver provides comprehensive error handling for common issues:

Singular Matrix

from eqsolver import Matrices3x3, InvalidMatrixError

calc = Matrices3x3()
singular = [[1, 2, 3], [2, 4, 6], [3, 6, 9]]  # Linearly dependent rows

try:
    inv = calc.multiplicative_inverse(singular)
except InvalidMatrixError as e:
    print(f"Error: {e}")

Output:

Error: Matrix is singular and cannot be inverted.

Division by Zero

try:
    result = calc.divide(A, num=0)
except ZeroDivisionError as e:
    print(f"Error: {e}")

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🧠 API Reference

Matrices2x2 and Matrices3x3

Both classes share the same interface:

Methods

Method	Parameters	Returns	Description
add(matrix1, matrix2)	Two matrices	Matrix	Element-wise addition
subtract(matrix1, matrix2)	Two matrices	Matrix	Element-wise subtraction
multiply(matrix1, matrix2, num)	Two matrices or matrix + scalar	Matrix	Matrix multiplication or scalar multiplication
divide(matrix, num)	Matrix and scalar	Matrix	Scalar division
determinant(matrix)	Matrix	Float	Calculate determinant
adjoint(matrix)	Matrix	Matrix	Calculate adjoint (adjugate)
multiplicative_inverse(matrix)	Matrix	Matrix	Calculate inverse matrix

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LinearEquationsSolver

Constructor

LinearEquationsSolver(equations_str: str)

Parameters:

• equations_str: Comma-separated string of equations (e.g., "2x + 3y = 5, x - y = 1")

Methods

Method	Parameters	Returns	Description
A()	None	Tuple[Matrix, Vector]	Returns coefficient matrix and constants vector
solve(method)	'cramer' or 'inverse'	List[Tuple[str, str]]	Solves equations and returns variable-value pairs

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InvalidMatrixError

Custom exception raised for:

• Singular matrices (determinant = 0)
• Invalid matrix dimensions
• Malformed input

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🤝 Contributing

We welcome contributions! Here's how you can help:

1. Fork the repository
2. Create a feature branch

   git checkout -b feature/amazing-feature
   

3. Commit your changes

   git commit -m "Add amazing feature"
   

4. Push to the branch

   git push origin feature/amazing-feature
   

5. Open a Pull Request

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📜 License

This project is licensed under the MIT License – see the LICENSE file for details.

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👨‍💻 Author

Hammail Riaz

• 🐙 GitHub: @Hammail-Riaz
• 📧 Email: [e-mail]

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🕓 Changelog

Version 1.0.0

• ✅ Initial stable release as eqsolver
• ✅ Added 2×2 and 3×3 matrix operations
• ✅ Added linear equation solver with Cramer's Rule and Matrix Inversion
• ✅ Comprehensive error handling
• ✅ Complete documentation and examples

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❤️ Acknowledgments

• Built with Python 3.8+
• Inspired by linear algebra education needs
• Thanks to all contributors and the open-source community

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🆘 Support

Need help? Have suggestions?

• 📝 Open an issue
• 📧 Email: [e-mail]

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Made with ❤️ for mathematics and Python enthusiasts

⭐ Star this repo if you find it helpful!