https://github.com/r8vnhill/genyal
Genetic algorithm framework for python
https://github.com/r8vnhill/genyal
Last synced: 6 months ago
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Genetic algorithm framework for python
- Host: GitHub
- URL: https://github.com/r8vnhill/genyal
- Owner: r8vnhill
- Created: 2020-11-01T14:56:34.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2022-10-26T02:25:06.000Z (almost 3 years ago)
- Last Synced: 2025-03-19T22:16:24.958Z (7 months ago)
- Language: Python
- Size: 269 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE/LICENSE
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README
# Genyal: The friendly genetic algorithm framework
This work is licensed under a
[Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/)
__Genyal__ is a genetic algorithm framework aimed to be as simple to use as it can be.
Evolution is natural, so using evolutionary algorithms should feel natural as well.
One of the main benefits of evolutionary programming is making it simple to solve complicated
problems, and that's something that most implementations of this kind of algorithms seems to forget.
You'll find either, very simple implementations of genetic algorithms from scratch, or full fledged
libraries that are, by no means, something that someone with little experience in the field of
evolutionary programming can easily use; nothing in between.
_Genyal_ is that missing "in between", by providing a simple interface so users new to the topic
can learn and use it without need of being experts, and flexible enough so that people can adapt it
to more sophisticated scenarios.
## Usage
Just like using it, installing _Genyal_ should be a piece of cake (great, now I want cake).
To do so, you can get it directly from PyPi or, with pip:
```bash
pip install genyal
```
## Example: Guessing a word
Let's check a very simple example.
A program to guess a given word.
```python
import random
import string
from genyal.genotype import GeneFactory
from genyal.engine import GenyalEngine
def random_char():
return random.choice(string.ascii_lowercase)
gene_factory = GeneFactory[str]()
gene_factory.generator = random_char
# This is how the engine will select the fittest individuals
def fitness_fun(word: list[str]) -> float:
return sum([word[i] == "owo"[i] for i in range(0, 3)])
# This is the condition to stop the evolution
def target(genyal_engine: GenyalEngine) -> bool:
return "".join(genyal_engine.fittest.genes) == "owo"
engine = GenyalEngine(fitness_function=fitness_fun, terminating_function=target)
# We create an initial population of 16 words (Individuals) of 3 characters (genes)
# using our previously defined gene factory.
engine.create_population(16, 3, gene_factory)
engine.evolve()
print(f"Found solution in {engine.generation} generations")
print(
f"Fittest individual: \"{''.join(engine.fittest.genes)}\" with fitness: "
f"{engine.fittest.fitness}")
```
If you run the code it will print something like:
```
Found solution in 543 generations
Fittest individual: "owo" with fitness: 3
```
You can find the explanation of this code, along with other examples, at the project's
[wiki](https://github.com/islaterm/genyal/wiki)