# EasyGA - A general solution to Genetic Algorithms The project has just started ## Installation: Run the rolling to install: ```Python pip3 install EasyGA ``` To use the package: ```python import EasyGA ``` ## All you need to get started: ```python import random import EasyGA # The user defined gene function def user_gene_function(): return random.randint(1, 100) # The user defined Fitness Function def user_fitness_function(): pass # Standard user size requirements Population_size = 10 Chromosome_length = 10 # Create the Genetic algorithm ga = EasyGA.GA(Population_size, Chromosome_length,user_gene_function) ga.initialize() ``` ## Getting your genes and chromosomes from the population: ```Python # Looking to print the first Chromosome ga.population.chromosomes[0].print_chromosome() # Looking to print one gene in chromosome 0 ga.population.chromosomes[0].genes[0].print_value() # Looking to get the data of a chromosome my_chromosome = ga.population.chromosomes[0].get_chromosome() print(f"my_chromosome: {my_chromosome}") # Looking to get the data of one gene in the chromosome my_gene = ga.population.chromosomes[0].genes[0].get_value() print(f"my_gene: {my_gene}") ``` # Ouput: ```Python [99],[30],[59],[77],[68],[57],[14],[92],[85],[27] 99 my_chromosome: [, , , , , , , , , ] my_gene: 99 ``` # Developing EasyGA: Download the repository to some folder - If you never used git. Look up a youtube tutorial. It will all make sense. ``` git clone https://github.com/danielwilczak101/EasyGA.git ``` Then install the repositroy using this command: ``` pip install -e . ``` # Working on developing a devel branch: To install EASY, along with the tools you need to develop and run tests, run the following in your virtual env: ```bash $ pip install -e .[devel] ```