| Name | backtracker JSON |
| Version |
0.0.7
JSON |
| download |
| home_page | |
| Summary | Backtracking Python package |
| upload_time | 2024-01-19 00:41:55 |
| maintainer | |
| docs_url | None |
| author | Ryan Najafi |
| requires_python | |
| license | |
| keywords |
python
backtracker
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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# BackTracker Class
The BackTracker class is a Python implementation of the backtracking algorithm, designed for solving problems where a sequence of decisions leads to a solution. This generic framework can be adapted to various problems, such as puzzles, crosswords, combinatorial problems, etc.
This is based on [Steven Skiena](https://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture15.pdf).
GitHub Page: https://github.com/ryan-najafi/backtracker
## Features
Generic backtracking implementation.
Customizable for a wide range of problems.
Allows defining problem-specific solution processing, candidate generation, and move making/unmaking.
## Installation
pip install backtracker==0.0.7
## Usage
To use the BackTracker class, you need to define functions for:
Checking if a current state is a solution (is_solution).
Processing a complete solution (process_solution).
Generating candidate moves (get_candidates).
Making a move (make_move).
Unmaking a move (unmake_move).
Here's an example demonstrating how to use the BackTracker class to generate combinations of elements:
```
from backtracker import backtracker as bt
from backtracker import BackTracker
a = []
level = 0
def is_solution(a, k, input):
return len(a) == len(input)
def process_solution(a, k, input):
result = []
for i, item in enumerate(a):
if item:
result.append(input[i])
return ''.join(result)
def get_candidates(a, k, input):
return [False, True]
def make_move(a, k, input, c):
a.append(c)
def unmake_move(a, k, input, c):
a.pop()
input = list('abc')
back_tracker = BackTracker(a=a, level=0, input=input,
is_solution=is_solution,
process_solution=process_solution,
get_candidates=get_candidates,
make_move=make_move,
unmake_move=unmake_move)
for sol in back_tracker.get_next_solution():
print(sol)
```
In this example, the BackTracker class is used to generate all combinations of the elements in the list 'abc'. The is_solution, process_solution, get_candidates, make_move, and unmake_move functions are defined to suit this specific problem.
## Contributing
Contributions to enhance BackTracker are welcome. Please adhere to the standard Python coding guidelines.
## License
This project is open-source and available under the MIT License.
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"description": "# BackTracker Class\nThe BackTracker class is a Python implementation of the backtracking algorithm, designed for solving problems where a sequence of decisions leads to a solution. This generic framework can be adapted to various problems, such as puzzles, crosswords, combinatorial problems, etc.\n\nThis is based on [Steven Skiena](https://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture15.pdf).\n\nGitHub Page: https://github.com/ryan-najafi/backtracker\n\n\n## Features\nGeneric backtracking implementation.\nCustomizable for a wide range of problems.\nAllows defining problem-specific solution processing, candidate generation, and move making/unmaking.\n\n## Installation\npip install backtracker==0.0.7\n\n## Usage\nTo use the BackTracker class, you need to define functions for:\n\nChecking if a current state is a solution (is_solution).\nProcessing a complete solution (process_solution).\nGenerating candidate moves (get_candidates).\nMaking a move (make_move).\nUnmaking a move (unmake_move).\n\nHere's an example demonstrating how to use the BackTracker class to generate combinations of elements:\n\n```\nfrom backtracker import backtracker as bt\n\nfrom backtracker import BackTracker\n\na = []\nlevel = 0\n\ndef is_solution(a, k, input):\n return len(a) == len(input)\n\ndef process_solution(a, k, input):\n result = []\n for i, item in enumerate(a):\n if item:\n result.append(input[i])\n return ''.join(result)\n\ndef get_candidates(a, k, input):\n return [False, True]\n\ndef make_move(a, k, input, c):\n a.append(c)\n\ndef unmake_move(a, k, input, c):\n a.pop()\n\ninput = list('abc')\nback_tracker = BackTracker(a=a, level=0, input=input, \n is_solution=is_solution, \n process_solution=process_solution, \n get_candidates=get_candidates, \n make_move=make_move, \n unmake_move=unmake_move)\n\nfor sol in back_tracker.get_next_solution():\n print(sol)\n \n```\n\n\nIn this example, the BackTracker class is used to generate all combinations of the elements in the list 'abc'. The is_solution, process_solution, get_candidates, make_move, and unmake_move functions are defined to suit this specific problem.\n\n## Contributing\nContributions to enhance BackTracker are welcome. Please adhere to the standard Python coding guidelines.\n\n## License\nThis project is open-source and available under the MIT License.\n\n",
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