Pygorithm module in Python

0 0 2 minutes read

Pygorithm module is a Python module written purely in Python and for educational purposes only. One can get the code, time complexities and much more by just importing the required algorithm. It is a good way to start learning Python programming and understanding concepts. Pygorithm module can also help to learn the implementation of all major algorithms in Python language.

To install Pygorithm module:

pip3 install pygorithm

Example:

# import the required data structure 
from pygorithm.data_structures import stack 
  
  
# create a stack with default stack size 10 
myStack = stack.Stack() 
  
# push elements into the stack 
myStack.push(2) 
myStack.push(5) 
myStack.push(9) 
myStack.push(10) 
  
# print the contents of stack 
print(myStack) 
  
# pop elements from stack 
myStack.pop() 
print(myStack) 
  
# peek element in stack 
print(myStack.peek()) 
  
# size of stack 
print(myStack.size()) 

Output:

To see all the available functions in a module, just type help() with the module name as argument.

# Help on package pygorithm.data_structures 
help(data_structures) 

Output:

NAME
    pygorithm.data_structures - Collection of data structure examples

PACKAGE CONTENTS
    graph
    heap
    linked_list
    quadtree
    queue
    stack
    tree
    trie

DATA
    __all__ = ['graph', 'heap', 'linked_list', 'queue', 'stack', 'tree', '...

To get code for any of these data_structures using get_code().

# to get code for BinarySearchTree 
BStree = tree.BinarySearchTree.get_code() 
  
print(BStree) 

Output:

class BinarySearchTree(object):
   
    def __init__(self):
        self.root = None

    def insert(self, data):
        """
        inserts a node in the tree
        """
        if self.root:
            return self.root.insert(data)
        else:
            self.root = BSTNode(data)
            return True

    def delete(self, data):
        """
        deletes the node with the specified data from the tree
        """
        if self.root is not None:
            return self.root.delete(data)

    def find(self, data):
        if self.root:
            return self.root.find(data)
        else:
            return False

    def preorder(self):
        """
        finding the preorder of the tree
        """
        if self.root is not None:
            return self.root.preorder(self.root)

    def inorder(self):
        """
        finding the inorder of the tree
        """
        if self.root is not None:
            return self.root.inorder(self.root)

    def postorder(self):
        """
        finding the postorder of the tree
        """
        if self.root is not None:
            return self.root.postorder(self.root)
    
    @staticmethod
    def get_code():
        """
        returns the code of the current class
        """
        return inspect.getsource(BinarySearchTree)

To get complexities for the following scripts:

# create a stack with default stack size 10 
Bsort = sorting.bubble_sort.time_complexities() 

Output:

Best Case: O(n), Average Case: O(n ^ 2), Worst Case: O(n ^ 2).

For Improved Bubble Sort:
Best Case: O(n); Average Case: O(n * (n - 1) / 4); Worst Case: O(n ^ 2)

Quick Link to source code of Pygorithm