Deap is a module in Python that helps you create and work with genetic algorithms. Imagine you want to create a painting, but you don't know how to paint. Genetic algorithms are like a tool that helps you to create that painting without knowing how to paint.
The way that genetic algorithms work is by mimicking the process of natural selection. In nature, animals and plants have different traits that help them survive and pass on those traits to their offspring. In the same way, genetic algorithms start with a population of possible solutions to a problem (like painting), and then mix and match parts of those solutions to create new and better solutions.
Deap helps you with this process by providing tools to create populations of solutions, set up the parameters for your genetic algorithm, and evaluate the fitness of each solution, meaning how good or bad it is in solving your problem. Also, Deap offers different types of crossover and mutation operators, that mix and match the solutions and creates new and unique ones.
In summary, Deap is a tool that helps you create solutions to a problem by mimicking the natural selection process, allowing you to create unique and effective solutions without requiring you to have deep expertise in the problem domain.