from random import choice, randint

OPLIST = [lambda x, y: x + y,
          lambda x, y: x - y,
          lambda x, y: x * y
          ]

OPTRANS = ['add', 'sub', 'mul']

class Entity:
    def __init__(self, size, desiredValue):
        self.desiredValue = desiredValue
        self.genomeX = [choice(OPLIST) for _ in range(size)]
        self.genomeY = [randint(0, 10) for _ in range(size)]
        for op, val in zip(self.genomeX, self.genomeY):
            print(OPTRANS[OPLIST.index(op)],val)

    def sequence(self):
        value = 0
        for op, val in zip(self.genomeX, self.genomeY):
            try:
                value = op(value, val)
            except ZeroDivisionError:
                value = value
        fitness = abs(self.desiredValue - value)
        return (value, fitness)

    def evolve(self, size, runs):
        _, startingFitness = self.sequence()
        print('Starting',runs,'runs of evolution @',size,'stepsize.\nStarting with a fitness of:',startingFitness)
        j = 0
        fitness = 1
        for _ in range(runs):
            if fitness == 0: break
            j += 1
            for val, i in zip(self.genomeY, range(len(self.genomeY))):
                _, baseFitness = self.sequence()
                if baseFitness > 0:
                    self.genomeY[i] += size
                    _, fitness = self.sequence()
                    if fitness > baseFitness:
                        self.genomeY[i] -= size * 2
                        _, newFitness = self.sequence()
                        if newFitness > fitness:
                            self.genomeY[i] += size

        _, endFitness = self.sequence()
        print('Ended with a fitness of:',endFitness,'after',j,'runs.\nPrinting genome below:')
        for op, val in zip(self.genomeX, self.genomeY):
            print(OPTRANS[OPLIST.index(op)],val)

e = Entity(10, 1966)

e.evolve(1, 10000)