slav-eeik-datastructures 1.1

Simple datastructures library with documentation.

Python DataStructures by slav_EEik

About the project

This is a simple datastructures and algorithms library. It is also published on PyPi.

You can see the automatically-generated documentation on GitHub Pages.

Here are all implemented datastructures:

• Lists

  • Singly Linked List
  • Doubly Linked List
  • Static Array

• Linear Structures

  • Stack
  • Queue
  • Deque

• Heaps

  • Min Heap
  • Priority Queue

• Trees and Tree Nodes

  • Binary Tree
  • Huffman Tree
  • Balancing Tree
  • Binary Search Tree
  • Red Black Tree
  • 2-3 Tree
  • Segment Tree
  • AVL Tree
  • Trie

• Graphs

  • Adjacency List
  • Adjacency Matrix

Note: trees.nodes.BinaryNode and trees.nodes.BalancedNode don't have their trees, so you can use them. It is not recommended to use all other nodes without their trees.

Here are all implemented algorithms:

• Sorting Algorithms:

  • Heap Sort
  • Bubble Sort
  • Quick Sort
  • Merge Sort
  • Insertion Sort
  • Selection sort

• String search algorithms:

  • Brute Force Search
  • Rabin-Karp Algorithm

• Tree Algorithms:

  • Tree balancing
  • Huffman Coding

• Graphs Algorithms:

  • Dijkstra algorithm
  • Bellman-Ford's algorithm
  • A* Algorithm
  • Breadth First Search
  • Depth First Search

Modules

Installation

pip install --upgrade pip
pip install slav-eeik-datastructures

Examples

Here are some examples of using the library:

from datastructures.linear import Stack, SinglyLinkedList


s = Stack()
s.push("First item")
s.push("Second item")
print(s.pop()) # Second item
print(s.peek()) # First item
print(s.peek()) # First item

l = SinglyLinkedList()
l.build([1, 2, 3, 4, 5, 6, 7, 8])
print(l[4]) # 5
l.delete_at(4)
print(l) # 1 -> 2 -> 3 -> 4 -> 6 -> 7 -> 8

from datastructures.sorts import merge_sort, quicksort, heap_sort


arr = [5, 4, 6, 1, 7, 10, -5, 9]
print(merge_sort(arr))              # [-5, 1, 4, 5, 6, 7, 9, 10]
print(quicksort(arr, reverse=True)) # [10, 9, 7, 6, 5, 4, 1, -5]
print(arr)                          # [5, 4, 6, 1, 7, 10, -5, 9]
heap_sort(arr, inplace=True)
print(arr)                          # [-5, 1, 4, 5, 6, 7, 9, 10]

from datastructures.graphs import ListAdjacency as Graph


g = Graph(6, False)
g.add_edge(0, 1, 1)
g.add_edge(0, 2, 5)
g.add_edge(1, 3, 2)
g.add_edge(2, 3, 3)

distance, path = g.dijkstra(0, 3)
print(distance)                             # 3
print(path)                                 # [0, 1, 3]
print(list(g.breadth_first_traversal(0)))   # [0, 2, 1, 3]

from datastructures.trees.trees import AVLTree


t = AVLTree()
t.build([9, 3, 5, 2, 9, 8, 2, 3, 4, 1])
print(t)    # BinaryTree(['Node(1)', 'Node(2)', 'Node(3)', 'Node(4)', 'Node(5)', 'Node(8)', 'Node(9)'])
t.insert(6)
print(t)    # BinaryTree(['Node(1)', 'Node(2)', 'Node(3)', 'Node(4)', 'Node(5)', 'Node(6)', 'Node(8)', 'Node(9)'])
print(t.find_min()) # 1
print(list(t.root.preorder_traversal())) # [Node(5), Node(3), Node(2), Node(1), Node(4), Node(8), Node(6), Node(9)]

License

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

Contacts

For any inquiries, please reach out to the project maintainer on GitHub or Telegram.