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https://github.com/brean/python-pathfinding
Implementation of common pathfinding algorithms
https://github.com/brean/python-pathfinding
algorithm obstacle pathfinding pathfinding-algorithm python python-pathfinding python3
Last synced: about 9 hours ago
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Implementation of common pathfinding algorithms
- Host: GitHub
- URL: https://github.com/brean/python-pathfinding
- Owner: brean
- License: mit
- Created: 2015-03-23T07:17:56.000Z (almost 10 years ago)
- Default Branch: main
- Last Pushed: 2024-01-17T17:11:45.000Z (11 months ago)
- Last Synced: 2024-04-25T10:14:51.804Z (8 months ago)
- Topics: algorithm, obstacle, pathfinding, pathfinding-algorithm, python, python-pathfinding, python3
- Language: Python
- Homepage: https://brean.github.io/svelte-pyscript-pathfinding
- Size: 186 KB
- Stars: 284
- Watchers: 13
- Forks: 58
- Open Issues: 19
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# python-pathfinding
Pathfinding algorithms for python 3.
Currently there are 7 path-finders bundled in this library, namely:
- A\*
- Dijkstra
- Best-First
- Bi-directional A\*
- Breadth First Search (BFS)
- Iterative Deeping A\* (IDA\*)
- Minimum Spanning Tree (MSP)
Dijkstra and A\* take the weight of the fields on the map into account.
_If you are still using python 2 take a look at the (unmaintained) [python2-branch](https://github.com/brean/python-pathfinding/tree/python2)._
## Installation
This library is provided by pypi, so you can just install the current stable version using pip:
```python
pip install pathfinding
```
see [pathfinding on pypi](https://pypi.org/project/pathfinding/)
## Usage examples
For usage examples with detailed descriptions take a look at the [docs](docs/) folder, also take a look at the [test/](test/) folder for more examples, e.g. how to use pandas
## Rerun the algorithm
While running the pathfinding algorithm it might set values on the nodes. Depending on your path finding algorithm things like calculated distances or visited flags might be stored on them. So if you want to run the algorithm in a loop you need to clean the grid first (see `Grid.cleanup`). Please note that because cleanup looks at all nodes of the grid it might be an operation that can take a bit of time!
## Implementation details
All pathfinding algorithms in this library are inheriting the Finder class. It has some common functionality that can be overwritten by the implementation of a path finding algorithm.
The normal process works like this:
1. You call `find_path` on one of your finder implementations.
1. `init_find` instantiates the `open_list` and resets all values and counters.
1. The main loop starts on the `open_list`. This list gets filled with all nodes that will be processed next (e.g. all current neighbors that are walkable). For this you need to implement `check_neighbors` in your own finder implementation.
1. For example in A\*s implementation of `check_neighbors` you first want to get the next node closest from the current starting point from the open list. the `next_node` method in Finder does this by giving you the node with a minimum `f`-value from the open list, it closes it and removes it from the `open_list`.
1. if this node is not the end node we go on and get its neighbors by calling `find_neighbors`. This just calls `grid.neighbors` for most algorithms.
1. If none of the neighbors are the end node we want to process the neighbors to calculate their distances in `process_node`
1. `process_node` calculates the cost `f` from the start to the current node using the `calc_cost` method and the cost after calculating `h` from `apply_heuristic`.
1. finally `process_node` updates the open list so `find_path` can run `check_neighbors` on it in the next node in the next iteration of the main loop.
flow:
```pseudo
find_path
init_find # (re)set global values and open list
check_neighbors # for every node in open list
next_node # closest node to start in open list
find_neighbors # get neighbors
process_node # calculate new cost for neighboring node
```
## Testing
You can run the tests locally using pytest. Take a look at the `test`-folder
You can follow below steps to setup your virtual environment and run the tests.
```bash
# Go to repo
cd python-pathfinding
# Setup virtual env and activate it - Mac/Linux for windows use source venv/Scripts/activate
python3 -m venv venv
source venv/bin/activate
# Install test requirements
pip install -r test/requirements.txt
# Run all the tests
pytest
```
## Contributing
Please use the [issue tracker](https://github.com/brean/python-pathfinding/issues) to submit bug reports and feature requests. Please use merge requests as described [here](/CONTRIBUTING.md) to add/adapt functionality.
## License
python-pathfinding is distributed under the [MIT license](https://opensource.org/licenses/MIT).
## Maintainer
Andreas Bresser, [email protected]
## Authors / Contributers
Authors and contributers are [listed on github](https://github.com/brean/python-pathfinding/graphs/contributors).
Inspired by [Pathfinding.JS](https://github.com/qiao/PathFinding.js)