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Commit 1ce9311

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Merge pull request #239 from Faris-A-Nasir/main
Added Dijkstra's Algorithmn
2 parents a5bba48 + f99f3a9 commit 1ce9311

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‎D/Dijkstra's Algorithm/dijkstra.py

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import heapq
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def dijkstra(graph, start):
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# Initialize distances and predecessors
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distances = {vertex: float('infinity') for vertex in graph}
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distances[start] = 0
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predecessors = {}
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# Priority queue to keep track of vertices to visit
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vertices_to_visit = [(0, start)]
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while vertices_to_visit:
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current_distance, current_vertex = heapq.heappop(vertices_to_visit)
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# If the current distance is larger than the stored distance, skip it
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if current_distance > distances[current_vertex]:
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continue
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for neighbor, weight in graph[current_vertex].items():
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distance = current_distance + weight
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if distance < distances[neighbor]:
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distances[neighbor] = distance
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predecessors[neighbor] = current_vertex
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heapq.heappush(vertices_to_visit, (distance, neighbor))
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return distances, predecessors
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# Example graph as an adjacency dictionary
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graph = {
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'A': {'B': 1, 'C': 4},
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'B': {'A': 1, 'C': 2, 'D': 5},
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'C': {'A': 4, 'B': 2, 'D': 1},
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'D': {'B': 5, 'C': 1}
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}
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start_vertex = 'A'
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distances, predecessors = dijkstra(graph, start_vertex)
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# Print the shortest distances and paths from the start vertex
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for vertex, distance in distances.items():
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path = [vertex]
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while vertex != start_vertex:
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vertex = predecessors[vertex]
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path.insert(0, vertex)
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print(f'Shortest path to {vertex}: {path}, Distance: {distance}')

‎D/Dijkstra's Algorithm/readme.md

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# Dijkstra's Algorithm in Python
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This Python program implements Dijkstra's Algorithm to find the shortest path from a specified source vertex to all other vertices in a weighted graph. Dijkstra's Algorithm is a fundamental algorithm for finding the shortest paths in a graph, and it is commonly used in various applications, such as routing and network optimization.
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## Table of Contents
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- [Requirements](#requirements)
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- [Algorithm Overview](#algorithm-overview)
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- [Contributing](#contributing)
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## Requirements
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To run this program, you need:
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- Python 3.x
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No additional external libraries are required.
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‎text.py

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import random
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# Define lists of words and phrases to use in the generator
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nouns = ["cat", "dog", "house", "car", "book"]
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verbs = ["runs", "jumps", "sleeps", "eats", "reads"]
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adjectives = ["happy", "fast", "green", "loud", "big"]
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adverbs = ["quickly", "loudly", "slowly", "gently", "suddenly"]
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def generate_random_text():
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sentence = f"{random.choice(nouns)} {random.choice(verbs)} {random.choice(adverbs)} {random.choice(adjectives)}."
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return sentence
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# Generate and print random text
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for _ in range(5):
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random_text = generate_random_text()
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print(random_text)

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