معرفی شرکت ها
EasyGA-1.6.1
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
EasyGA is a python package designed to provide an easy-to-use Genetic Algorithm. The package is designed to work right out of the box, while also allowing the user to customize features as they see fit.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | EasyGA-1.6.1 |
| نام | EasyGA |
| نسخه کتابخانه | 1.6.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Daniel Wilczak, Jack Nguyen, Ryley Griffith, Jared Curtis, Matthew Chase Oxamendi |
| ایمیل نویسنده | danielwilczak101@gmail.com |
| آدرس صفحه اصلی | https://github.com/danielwilczak101/EasyGA |
| آدرس اینترنتی | https://pypi.org/project/EasyGA/ |
| مجوز | - |
# EasyGA - Genetic Algorithms made Easy
EasyGA is a python package designed to provide an easy-to-use Genetic Algorithm. The package is designed to work right out of the box, while also allowing the user to customize features as they see fit.
## Check out our [Wiki](https://github.com/danielwilczak101/EasyGA/wiki) or [Youtube](https://www.youtube.com/watch?v=jbuDKwIiYBw) for more information.
## Installation:
Run python's pip3 to install:
```Python
pip3 install EasyGA
```
## Getting started with EasyGA(Basic Example):
```Python
import EasyGA
# Create the Genetic algorithm
ga = EasyGA.GA()
# Evolve the whole genetic algorithm until termination has been reached
ga.evolve()
# Print out the current generation and the population
ga.print_generation()
ga.print_population()
```
### Output:
```bash
Current Generation : 15
Current population:
Chromosome - 0 [7][4][4][5][3][5][5][8][3][7] / Fitness = 3
Chromosome - 1 [7][4][4][5][3][5][5][8][3][7] / Fitness = 3
Chromosome - 2 [7][4][4][5][3][5][5][8][3][7] / Fitness = 3
Chromosome - 3 [7][4][4][5][3][5][5][8][3][7] / Fitness = 3
Chromosome - 4 [7][2][4][5][3][5][5][8][3][7] / Fitness = 3
Chromosome - 5 [7][2][4][5][3][5][5][8][3][7] / Fitness = 3
Chromosome - 6 [5][8][8][6][10][10][5][7][2][7] / Fitness = 2
Chromosome - 7 [5][8][8][6][10][10][5][7][2][7] / Fitness = 2
Chromosome - 8 [5][8][8][6][10][10][5][7][2][7] / Fitness = 2
Chromosome - 9 [7][2][8][10][3][5][5][8][1][7] / Fitness = 2
```
## Getting started with EasyGA (Password Cracker Example):
```Python
import EasyGA
import random
ga = EasyGA.GA()
word = input("Please enter a word: \n")
# Basic Attributes
ga.chromosome_length = len(word)
ga.fitness_goal = len(word)
# Size Attributes
ga.population_size = 50
ga.generation_goal = 10000
# User definded fitness
def password_fitness(chromosome):
return sum(1 for gene, letter
in zip(chromosome, word)
if gene.value == letter
)
ga.fitness_function_impl = password_fitness
# What the genes will look like.
ga.gene_impl = lambda: random.choice(["A","a","B","b","C","c","D","d","E","e",
"F","f","G","g","H","h","I","i","J","j",
"K","k","L","l","M","m","N","n","O","o",
"P","p","Q","q","R","r","S","s","T","t",
"U","u","V","v","W","w","X","x","Y","y",
"Z","z"," "])
# Evolve the gentic algorithm
ga.evolve()
# Print out the current generation and the population
ga.print_generation()
ga.print_population()
# Show graph of progress
ga.graph.highest_value_chromosome()
ga.graph.show()
```
## Ouput:
```
Please enter a word:
EasyGA
Current Generation : 44
Chromosome - 0 [E][a][s][y][G][A] / Fitness = 6
Chromosome - 1 [E][a][s][Y][G][A] / Fitness = 5
Chromosome - 2 [E][a][s][O][G][A] / Fitness = 5
Chromosome - 3 [E][a][s][Y][G][A] / Fitness = 5
Chromosome - 4 [E][a][s][c][G][A] / Fitness = 5
Chromosome - 5 [E][a][s][c][G][A] / Fitness = 5
Chromosome - 6 [E][a][s][y][Z][A] / Fitness = 5
Chromosome - 7 [E][a][s][Y][G][A] / Fitness = 5
Chromosome - 8 [E][a][s][y][Z][A] / Fitness = 5
Chromosome - 9 [E][a][s][Y][G][A] / Fitness = 5
```
![]()
<img width="500px" src="https://raw.githubusercontent.com/danielwilczak101/EasyGA/media/images/password_cracker_results.png" />
## Issues
We would love to know if your having any issues. Please start a new issue on the [Issues Page](https://github.com/danielwilczak101/EasyGA/issues).
## Local System Approach
Download the repository to some folder on your computer.
```
https://github.com/danielwilczak101/EasyGA/archive/master.zip
```
Use the run.py file inside the EasyGA folder to run your code. This is a local version of the package.
## Check out our [wiki](https://github.com/danielwilczak101/EasyGA/wiki) for more information.
نیازمندی
| مقدار | نام |
|---|---|
| ~=3.3.2 | matplotlib |
| ~=3.4 | pyserial |
| >=3.7 | pytest |
| >=0.8.7 | tabulate |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl EasyGA-1.6.1:
pip install EasyGA-1.6.1.whl
نصب پکیج tar.gz EasyGA-1.6.1:
pip install EasyGA-1.6.1.tar.gz