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project in python based on PyQT6 framework implementing the visualization of a shortest path search

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Ilshat-Akhmetov/PathFinderVisualization

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Shortest path finding visualization

This projects implements various method to find a shorted path from one point in a grid to another. It was developed using PyQT6 framework for GUI applications and python version 3.8.7.

In this program one can set sell values as non-negative floats/ints or bc. Here bc stands for blocked cell. It means that a path cannot go through a bc cell.

Current implementation supports four ways to find the shortest path: dfs, bfs, dijkstra and A-star and can work properly with any grid with size up to 15x15 cells.

In the future I have plans to modify the current implementation, adding possibility to load grid from a file and making grid and main window more adjustable and convenient for a user.

How to use it?

Just make sure you have a proper version of PyQT6 from requirements.txt and execute:

python3 main.py

You will get the window where you have to input cell values. Each cell value means the cost a path should pay to go through the cell. If you set cell value as bc then the cell will be unpassable.

The button Create grid will generate you grid with a number of rows and cols according to the input boxes and fill grid with default value.

Note that regardless of what you see the program assumes that cell values at start point (bottom left) and end point (top right) are equal to zero.

a grid created

After you set your grid you should select the way you want to use for searching the shortest path from bottom left to top right cell and press search path. You will get this:

the shortest path had been found

Then you have to clear the results pressing Create grid if you want to find the sortest path with another method/grid.

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project in python based on PyQT6 framework implementing the visualization of a shortest path search

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