"""simple docstring"""




from __future__ import annotations

import random

# Maximum size of the population.  Bigger could be faster but is more memory expensive.
_a				:		Dict	   =       200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be smaller than N_POPULATION.
_a				:		List[str]	   =       50
# Probability that an element of a generation can mutate, changing one of its genes.
# This will guarantee that all genes will be used during evolution.
_a				:		str	   =       0.4
# Just a seed to improve randomness required by the algorithm.
random.seed(random.randint(0, 1_000))





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	str      ,_lowerCamelCase						:	str     )	->				Any:
		_lowerCAmelCase						:	int        =					len([g for position, g in enumerate(_lowerCamelCase     ) if g == main_target[position]]     )
		return (item, float(_lowerCamelCase     ))





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	str      ,_lowerCamelCase						:	str     )	->				Dict:
		_lowerCAmelCase						:	Any        =					random.randint(0      ,len(_lowerCamelCase     ) - 1     )
		_lowerCAmelCase						:	Tuple        =					parent_a[:random_slice] + parent_a[random_slice:]
		_lowerCAmelCase						:	List[str]        =					parent_a[:random_slice] + parent_a[random_slice:]
		return (child_a, child_a)





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	str      ,_lowerCamelCase						:	list[str]     )	->				Union[str, Any]:
		_lowerCAmelCase						:	str        =					list(_lowerCamelCase     )
		if random.uniform(0      ,1     ) < MUTATION_PROBABILITY:
				_lowerCAmelCase						:	Union[str, Any]        =					random.choice(_lowerCamelCase     )
		return "".join(_lowerCamelCase     )





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	tuple[str, float]      ,_lowerCamelCase						:	list[tuple[str, float]]      ,_lowerCamelCase						:	list[str]      ,)	->				List[str]:
		_lowerCAmelCase						:	List[Any]        =					[]
		# Generate more children proportionally to the fitness score.
		_lowerCAmelCase						:	Dict        =					int(parent_a[1] * 100     ) + 1
		_lowerCAmelCase						:	Tuple        =					10 if child_n >= 10 else child_n
		for _ in range(_lowerCamelCase     ):
				_lowerCAmelCase						:	List[str]        =					population_score[random.randint(0      ,_lowerCamelCase     )][0]

				_lowerCAmelCase						:	Dict        =					crossover(parent_a[0]      ,_lowerCamelCase     )
				# Append new string to the population list.
				pop.append(mutate(_lowerCamelCase      ,_lowerCamelCase     )     )
				pop.append(mutate(_lowerCamelCase      ,_lowerCamelCase     )     )
		return pop





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	str      ,_lowerCamelCase						:	list[str]      ,_lowerCamelCase						:	bool = True     )	->				Union[str, Any]:

		# Verify if N_POPULATION is bigger than N_SELECTED
		if N_POPULATION < N_SELECTED:
				_lowerCAmelCase						:	Any        =					f"{N_POPULATION} must be bigger than {N_SELECTED}"
				raise ValueError(_lowerCamelCase     )
		# Verify that the target contains no genes besides the ones inside genes variable.
		_lowerCAmelCase						:	int        =					sorted({c for c in target if c not in genes}     )
		if not_in_genes_list:
				_lowerCAmelCase						:	str        =					f"{not_in_genes_list} is not in genes list, evolution cannot converge"
				raise ValueError(_lowerCamelCase     )

		# Generate random starting population.
		_lowerCAmelCase						:	Tuple        =					[]
		for _ in range(_lowerCamelCase     ):
				population.append("""""".join([random.choice(_lowerCamelCase     ) for i in range(len(_lowerCamelCase     )     )]     )     )

		# Just some logs to know what the algorithms is doing.
		_lowerCAmelCase						:	Any        =					0, 0

		# This loop will end when we find a perfect match for our target.
		while True:
				generation += 1
				total_population += len(_lowerCamelCase     )

				# Random population created. Now it's time to evaluate.

				# Adding a bit of concurrency can make everything faster,
				#
				# import concurrent.futures
				# population_score: list[tuple[str, float]] = []
				# with concurrent.futures.ThreadPoolExecutor(
				#                                   max_workers=NUM_WORKERS) as executor:
				#     futures = {executor.submit(evaluate, item) for item in population}
				#     concurrent.futures.wait(futures)
				#     population_score = [item.result() for item in futures]
				#
				# but with a simple algorithm like this, it will probably be slower.
				# We just need to call evaluate for every item inside the population.
				_lowerCAmelCase						:	Dict        =					[evaluate(_lowerCamelCase      ,_lowerCamelCase     ) for item in population]

				# Check if there is a matching evolution.
				_lowerCAmelCase						:	Any        =					sorted(_lowerCamelCase      ,key=lambda _lowerCamelCase     : x[1]      ,reverse=_lowerCamelCase     )
				if population_score[0][0] == target:
						return (generation, total_population, population_score[0][0])

				# Print the best result every 10 generation.
				# Just to know that the algorithm is working.
				if debug and generation % 10 == 0:
						print(
						    f"\nGeneration: {generation}"
						    f"\nTotal Population:{total_population}"
						    f"\nBest score: {population_score[0][1]}"
						    f"\nBest string: {population_score[0][0]}"     )

				# Flush the old population, keeping some of the best evolutions.
				# Keeping this avoid regression of evolution.
				_lowerCAmelCase						:	Optional[int]        =					population[: int(N_POPULATION / 3     )]
				population.clear()
				population.extend(_lowerCamelCase     )
				# Normalize population score to be between 0 and 1.
				_lowerCAmelCase						:	List[str]        =					[
				    (item, score / len(_lowerCamelCase     )) for item, score in population_score
				]

				# This is selection
				for i in range(_lowerCamelCase     ):
						population.extend(select(population_score[int(_lowerCamelCase     )]      ,_lowerCamelCase      ,_lowerCamelCase     )     )
						# Check if the population has already reached the maximum value and if so,
						# break the cycle.  If this check is disabled, the algorithm will take
						# forever to compute large strings, but will also calculate small strings in
						# a far fewer generations.
						if len(_lowerCamelCase     ) > N_POPULATION:
								break


if __name__ == "__main__":
					_a				:		List[Any]	   =       (
					    'This is a genetic algorithm to evaluate, combine, evolve, and mutate a string!'
					)
					_a				:		Any	   =       list(
					    ' ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklm'
					    'nopqrstuvwxyz.,;!?+-*#@^\'èéòà€ù=)(&%$£/\\'
					)
					_a   ,       _a   ,       _a				:		List[str]	   =       basic(target_str, genes_list)
					print(
					    F"""\nGeneration: {generation}\nTotal Population: {population}\nTarget: {target}"""
					)





"""simple docstring"""




from ..utils import DummyObject, requires_backends
class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      int		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      str		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[int]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      str		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Union[str, Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[int]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[str]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Any		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      str		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Tuple		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      str		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Tuple		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      str		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Tuple		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      str		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Dict		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Dict		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Union[str, Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Tuple		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[int]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[Any]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      int		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Dict		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[str]		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )







class 						__A							(			metaclass=SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      int		 =		["sentencepiece"]






     def __init__(		self    ,					*a__    ,					**a__  ):
       requires_backends(self    ,					["""sentencepiece"""]  )




