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A basic python library that has modules for maths and algorithms

Project description

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Open Source Love PyPI version License: MIT Downloads

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A basic Python library that has modules for math functions, algorithms, and puzzles.

Installation

Use the package manager pip to install Algopylib.

pip install Algopylib 

Usage

import Algopylib.algo.check as ck

ck.is_power_of_2(32) # returns True 
ck.is_even(3) # returns False 

Package Structure

├── Algopylib
│   ├── algo
│      ├── __init__.py
│      ├── binary.py
│      ├── check.py
│      └── sort.py
│   ├── math
│      ├── __init__.py
│      ├── combinatorics.py
│      ├── gcd_lcm.py
│      ├── geometry.py
│      ├── matrix.py
│      ├── series.py
│      └── stat.py
│   └── puzzle
│       ├── __init__.py
│       ├── sudoku.py
│       └── tictaktoe.py
└── __init__.py

Contents

Algo

Implementation of simple Algorithms.

  • Binary
    • Binary sum
  • Check
    • Is power of 2
    • Is power of N
    • Is square
    • Is palindrome
    • Is subsequence
    • Is even
    • Is odd
    • Is prime
  • Sort
    • Bubble sort
    • Insertion sort

Math

Implementation of useful Math functions.

  • Combinatorics
    • Factorial
    • nCr
    • nPr
  • GCD LCM
    • GCD
    • LCM
    • Trailing zeroes
    • GCD using bitwise operator
  • Geometry
    • Distance
    • Is collinear
    • Equation of line
    • Is inside circle
    • Area of triangle
  • Matrix
    • Determinant of 2x2 matrix
    • Determinant of 3x3 matrix
    • Inverse of 2x2 matrix
    • Inverse of 3x3 matrix
  • Series
    • Nth term of AP
    • Nth term of GP
    • Sum of AP
    • Sum of GP
  • Statistics
    • Mean
    • Float mean
    • Geometric mean
    • Harmonic mean
    • Median
    • Low and high median
    • Median-grouped
    • Mode
    • Multimode
    • Quantiles
    • Population variance
    • Sample variance
    • Population standard deviation
    • Sample Standard deviation
    • Sample covariance

Puzzle

Implementation of simple Puzzles.


Setup for devs

For Windows,

  1. Use pip install virtualenv
  2. Run virtualenv nameofvenv in terminal
  3. Activate that virtualenv (different for different os)
  4. Run pip install -r requirements.txt in terminal (virtualenv should be activated)
  5. To compile library, run python setup.py sdist bdist_wheel in terminal

For other OS,

  1. Use pip install virtualenv
  2. Run virtualenv nameofvenv in terminal
  3. Activate that virtualenv
  4. Run following command in terminal,
    • python -m pip install -upgrade pip
    • pip install wheel
    • pip install twine
    • pip install mypy
  5. To compile library, run python setup.py sdist bdist_wheel in terminal

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.

License

MIT

Project details


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