1. The structure of the library is changed and some methods defined in the pygad.py module are moved to the pygad.utils, pygad.helper, and pygad.visualize submodules.
2. The pygad.utils.parent_selection module has a class named ParentSelection where all the parent selection operators exist. The pygad.GA class extends this class.
3. The pygad.utils.crossover module has a class named Crossover where all the crossover operators exist. The pygad.GA class extends this class.
4. The pygad.utils.mutation module has a class named Mutation where all the mutation operators exist. The pygad.GA class extends this class.
5. The pygad.helper.unique module has a class named Unique some helper methods exist to solve duplicate genes and make sure every gene is unique. The pygad.GA class extends this class.
6. The pygad.visualize.plot module has a class named Plot where all the methods that create plots exist. The pygad.GA class extends this class.

...
class GA(utils.parent_selection.ParentSelection, 
         utils.crossover.Crossover, 
         utils.mutation.Mutation, 
         helper.unique.Unique,
         visualize.plot.Plot):
...

1. Support of using the logging module to log the outputs to both the console and text file instead of using the print() function. This is by assigning the logging.Logger to the new logger parameter. Check the [Logging Outputs](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#logging-outputs) for more information.
2. A new instance attribute called logger to save the logger.
3. The function/method passed to the fitness_func parameter accepts a new parameter that refers to the instance of the pygad.GA class. Check this for an example: [Use Functions and Methods to Build Fitness Function and Callbacks](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#use-functions-and-methods-to-build-fitness-and-callbacks). #163
4. Update the documentation to include an example of using functions and methods to calculate the fitness and build callbacks. Check this for more details: [Use Functions and Methods to Build Fitness Function and Callbacks](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#use-functions-and-methods-to-build-fitness-and-callbacks). #92 (comment)
5. Validate the value passed to the initial_population parameter.
6. Validate the type and length of the pop_fitness parameter of the best_solution() method.
7. Some edits in the documentation. #106
8. Fix an issue when building the initial population as (some) genes have their value taken from the mutation range (defined by the parameters random_mutation_min_val and random_mutation_max_val) instead of using the parameters init_range_low and init_range_high.
9. The summary() method returns the summary as a single-line string. Just log/print the returned string it to see it properly.
10. The callback_generation parameter is removed. Use the on_generation parameter instead.
11. There was an issue when using the parallel_processing parameter with Keras and PyTorch. As Keras/PyTorch are not thread-safe, the predict() method gives incorrect and weird results when more than 1 thread is used. #145 ahmedfgad/TorchGA#5 ahmedfgad/KerasGA#6. Thanks to this [StackOverflow answer](https://stackoverflow.com/a/75606666/5426539).
12. Replace numpy.float by float in the 2 parent selection operators roulette wheel and stochastic universal. #168