The KAGraph package offers a powerful and intuitive way to work with directed, weighted graphs in Python. It utilizes adjacency lists to efficiently represent graph structures, providing users with a broad range of functionalities for graph manipulation and analysis.
To get started with KAGraph, you can easily install it using pip:
pip install KAGraphHere's a quick example to show you how to create a graph, add edges, and use some of the available methods:
from KAGraph import KAGraph
# Initialize the Graph
print("\nCreating graph...\n")
graph = KAGraph()
print("Graph created\n")
# Add edges to the graph
graph.new_edge('A', 'B', 10)
print("Added edge A-B with cost 10")
graph.new_edge('B', 'C', 20)
print("Added edge B-C with cost 20\n")
# Display the graph
print("Displaying graph")
graph.view_all()
print("------------\nGraph displayed\n")
# Query the cost of a path
print("Querying cost of direct edge A-C\n")
print(graph.getCost('A', 'C'))
print("Edge cost queried\n")To populate your graph with data from a file, you can follow the pattern shown below. This example assumes you have a text file (data.txt) where the first line indicates the number of nodes and edges, and each subsequent line represents an edge with an origin node, a destiny node, and a weight.
3 3
A B 10
B C 20
A C 15
This file indicates there are 3 nodes and 3 edges in the graph. Each of the following lines describes an edge between two nodes and its weight.
Here's how you can read data.txt and load its contents into your graph:
from KAGraph import KAGraph
# Initialize your graph
graph = KAGraph()
# Load data from file
with open("data.txt") as file:
lines = file.readlines()
nodes, edges = lines[0].split() # The first line contains counts of nodes and edges (unused here, but could be useful for validation)
for i in range(1, len(lines)): # Read each edge and add it to the graph, skip the first line with counts
origin, destiny, weight = lines[i].split()
graph.new_edge(origin, destiny, int(weight)) # Ensure weight is an integerNow your graph is populated with the data from data.txt
- Add Edges: Create a new connection between two nodes with a specified weight using
new_edge(origin, destiny, weight). - Remove Edges: Eliminate a connection between two nodes with
remove_edge(origin, destiny). - Remove Nodes: Remove a node along with all its connected edges using
remove_node(node).
- Find Shortest Path: Discover the shortest path between two nodes with
find_shortest_path(start, end), which returns the sequence of nodes representing the path. - Get Cost: Retrieve the cost of traveling from one node to another with
getCost(origin, destiny).
- View All Edges: Print a comprehensive list of all edges and their respective weights with
view_all(). - Get Connections: Output all outgoing connections from a specified node using
getConnections(origin). - Get Incoming Nodes: List all nodes with edges leading to a specified node with
getFromNode(node). - Get Outgoing Nodes: List all nodes directly reachable from a specified node with
getToNode(node).
from KAGraph import KAGraph
# Initialize a new Graph instance
graph = KAGraph
# Add multiple edges
graph.new_edge('X', 'Y', 7)
graph.new_edge('Y', 'Z', 3)
# Remove an edge
graph.remove_edge('X', 'Y')
# Remove a node and its associated edges
graph.remove_node('Z')# Find the shortest path between two nodes
path = graph.find_shortest_path('A', 'D')
print("Shortest Path:", path)
# Determine the cost of a specific path
cost = graph.getCost('A', 'D')
print("Path Cost:", cost)Contributions to KAGraph are welcome! Feel free to fork the repository, make your changes, and submit a pull request. For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License - see the LICENSE file for details.