Genetic_algorithm_chapter_1.py

import random
import datetime

geneSet = " abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!."
target = "Hello World!"

random.seed()
startTime = datetime.datetime.now()

#generate a random string from the gene set.
def generate_parent(length):
    genes = []
    while len(genes) < length:
        sampleSize = min(length-len(genes), len(geneSet))
        genes.extend(random.sample(geneSet, sampleSize))
    return ''.join(genes)

bestParent = generate_parent(len(target))

def get_fitness(guess):
    return sum(1 for expected, actual in zip(target, guess)
               if expected == actual)

bestFitness = get_fitness(bestParent)

def mutate(parent):
    index = random.randrange(0, len(parent))
    childGenes = list(parent)
    newGene, alternate = random.sample(geneSet, 2)
    childGenes[index] = alternate \
        if newGene == childGenes[index] \
        else newGene
    return ''.join(childGenes)

def display(guess):
    timeDiff = datetime.datetime.now() - startTime
    fitness = get_fitness(guess)
    print("{0}\t{1}\t{2}".format(guess, fitness, str(timeDiff)))

display(bestParent)

while True:
    child = mutate(bestParent)
    childFitness = get_fitness(child)
    if bestFitness >= childFitness:
        continue
    display(child)
    if childFitness >= len(bestParent):
        break
    bestFitness = childFitness
    bestParent = child