Introduction

Features

• Arithmetic Operations: Addition, subtraction, multiplication, and division.
• Algebraic Operations: Solving simple linear equations.

Important steps

1. Step 1: Set Up the Project Structure: First, set up your directory structure:

                               MathLib/
                               ├── mathlib/
                               │   ├── __init__.py
                               │   ├── arithmetic.py
                               │   ├── algebra.py
                               │   ├── complex_numbers.py
                               │   ├── logarithmic.py
                               │   ├── matrix_operations.py
                               │   ├── power_roots.py
                               │   ├── random_utils.py
                               │   ├── statistics.py
                               │   ├── trigonometry.py
                               │   └── utility.py
                               ├── tests/
                               │   ├── test_arithmetic.py
                               │   ├── test_algebra.py
                               │   ├── test_complex_numbers.py
                               │   ├── test_logarithmic.py
                               │   ├── test_matrix_operations.py
                               │   ├── test_power_roots.py
                               │   ├── test_random_utils.py
                               │   ├── test_statistics.py
                               │   ├── test_trigonometry.py
                               │   └── test_utility.py
                               ├── setup.py
                               ├── README.md
                               └── LICENSE
                           

2. Step 2: Write the Package Code: mathlib/__init__.py This file makes the mathlib directory a package.

   
                                   # mathlib/__init__.py
   
                                   from .arithmetic import add, subtract, multiply, divide, power
                                   from .algebra import solve_linear, solve_quadratic
                                   from .trigonometry import sin, cos, tan, arcsin, arccos, arctan
                                   from .statistics import mean, median, variance, standard_deviation
                                   from .matrix_operations import matrix_addition, matrix_multiplication, matrix_determinant, matrix_inverse
                                   from .complex_numbers import complex_addition, complex_subtraction, complex_multiplication, complex_division, complex_magnitude, complex_phase
                                   from .random_utils import random_integer, random_float
                                   from .utility import factorial, gcd, lcm
                                   
                                   __all__ = [
                                       'add', 'subtract', 'multiply', 'divide', 'power',
                                       'solve_linear', 'solve_quadratic',
                                       'sin', 'cos', 'tan', 'arcsin', 'arccos', 'arctan',
                                       'mean', 'median', 'variance', 'standard_deviation',
                                       'matrix_addition', 'matrix_multiplication', 'matrix_determinant', 'matrix_inverse',
                                       'complex_addition', 'complex_subtraction', 'complex_multiplication', 'complex_division', 'complex_magnitude', 'complex_phase',
                                       'random_integer', 'random_float',
                                       'factorial', 'gcd', 'lcm'
                                   ]
                               

   Next Create the python files for various kind of mathematical functions.
3. Step 3: Write Tests: To ensure your package functions as expected, it's essential to write some basic tests. Pytest is a powerful tool for this purpose and is widely recommended for Python projects. It helps you write simple and scalable test cases to validate your code.
4. Step 4: Set Up the Package Metadata: setup.py

   
                                   # setup.py
   
                                   from setuptools import setup, find_packages
                                   
                                   setup(
                                       name='mathlib',
                                       version='0.1',
                                       packages=find_packages(),
                                       description='A simple math library with basic operations',
                                       long_description=open('README.md').read(),
                                       long_description_content_type='text/markdown',
                                       author='Arun Kumar Pandey',
                                       author_email='arunp77@gmail.com',
                                       url='https://github.com/arunp77/mathlib-package.git',
                                       license='MIT',
                                       install_requires=[],
                                       classifiers=[
                                           'Programming Language :: Python :: 3',
                                           'License :: OSI Approved :: MIT License',
                                           'Operating System :: OS Independent',
                                       ],
                                   )                                
                               

   This setup.py file is used to install the package using pip. It includes metadata.
5. Step 5: Testing: To run the tests for this project, use pytest:

   pytest tests/

   This will run the test suite located in the tests directory, ensuring that all functions work as expected.
6. Step 6: Installation: You can install MathLib directly from the source code:

   git clone https://github.com/arunp77/Data-engineering-tools.git

   go to the cloned directory and then install it using:

   pip install -e . -v

   It can also be installed using pip and is available at pypi link and at npm link. The docker container is available at docker image.
7. Github link: Complete python source code is available at: Github.