import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


SCREAMING_SNAKE_CASE__		:       Any       						=       logging.get_logger(__name__)

class    snake_case       :
  lowercase_								=  None







@experimental
def      _a					(   lowercase__	:      Any  ,	lowercase__	:      Optional[int]  ,	lowercase__	:      Union[str, Any]  ,	lowercase__	:      Tuple  ,	lowercase__	:      Optional[Any]  ,	lowercase__	:      List[Any]  ,	lowercase__	:      str			):







     '''simple docstring'''


     if ParallelBackendConfig.backend_name is None:
          return _map_with_multiprocessing_pool(
              lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__			)

     return _map_with_joblib(lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__  ,	lowercase__			)







def      _a					(   lowercase__	:      Any  ,	lowercase__	:      Dict  ,	lowercase__	:      str  ,	lowercase__	:      Optional[Any]  ,	lowercase__	:      Optional[Any]  ,	lowercase__	:      List[Any]  ,	lowercase__	:      Dict			):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__					:					Optional[Any]      =		num_proc if num_proc <= len(lowercase__			) else len(lowercase__			)
     SCREAMING_SNAKE_CASE__					:					Dict      =		[]  # We organize the splits ourselve (contiguous splits)
     for index in range(lowercase__			):
          SCREAMING_SNAKE_CASE__					:					List[Any]      =		len(lowercase__			) // num_proc
          SCREAMING_SNAKE_CASE__					:					Dict      =		len(lowercase__			) % num_proc
          SCREAMING_SNAKE_CASE__					:					List[str]      =		div * index + min(lowercase__  ,	lowercase__			)
          SCREAMING_SNAKE_CASE__					:					Union[str, Any]      =		start + div + (1 if index < mod else 0)
          split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)			)

     if len(lowercase__			) != sum(len(i[1]			) for i in split_kwds			):
          raise ValueError(
              f'''Error dividing inputs iterable among processes. '''
              f'''Total number of objects {len(lowercase__			)}, '''
              f'''length: {sum(len(i[1]			) for i in split_kwds			)}'''			)

     logger.info(
         f'''Spawning {num_proc} processes for {len(lowercase__			)} objects in slices of {[len(i[1]			) for i in split_kwds]}'''			)
     SCREAMING_SNAKE_CASE__      ,				SCREAMING_SNAKE_CASE__					:					str      =		None, None
     if not disable_tqdm:
          SCREAMING_SNAKE_CASE__      ,				SCREAMING_SNAKE_CASE__					:					Dict      =		(RLock(),), tqdm.set_lock
     with Pool(lowercase__  ,	initargs=lowercase__  ,	initializer=lowercase__			) as pool:
          SCREAMING_SNAKE_CASE__					:					Union[str, Any]      =		pool.map(lowercase__  ,	lowercase__			)
     logger.info(f'''Finished {num_proc} processes'''			)
     SCREAMING_SNAKE_CASE__					:					Tuple      =		[obj for proc_res in mapped for obj in proc_res]
     logger.info(f'''Unpacked {len(lowercase__			)} objects'''			)

     return mapped







def      _a					(   lowercase__	:      List[str]  ,	lowercase__	:      str  ,	lowercase__	:      List[str]  ,	lowercase__	:      List[Any]  ,	lowercase__	:      Union[str, Any]  ,	lowercase__	:      List[str]  ,	lowercase__	:      Optional[Any]			):







     '''simple docstring'''


     import joblib

     with joblib.parallel_backend(ParallelBackendConfig.backend_name  ,	n_jobs=lowercase__			):
          return joblib.Parallel()(
              joblib.delayed(lowercase__			)((function, obj, types, None, True, None)			) for obj in iterable			)







@experimental
@contextlib.contextmanager
def      _a					(   lowercase__	:      str			):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__					:					List[Any]      =		backend_name

     if backend_name == "spark":
          from joblibspark import register_spark

          register_spark()

          # TODO: call create_cache_and_write_probe if "download" in steps
          # TODO: raise NotImplementedError when Dataset.map etc is called

     try:
          yield
     finally:
          SCREAMING_SNAKE_CASE__					:					Tuple      =		None










import numpy as np


class        __magic_name__	:





     """simple docstring"""



     def __init__(				self							:List[str]	):





        '''simple docstring'''




        A_       :					Optional[int]        =      (0, 0)
        A_       :					Dict        =      None
        A_       :					Optional[Any]        =      0
        A_       :					Optional[Any]        =      0
        A_       :					List[Any]        =      0



     def __eq__(				self							:int      ,   snake_case							:str	):





        '''simple docstring'''




        return self.position == cell.position





     def     SCREAMING_SNAKE_CASE		(				self							:List[Any]	):





        '''simple docstring'''




        print(self.position	)




class        __magic_name__	:





     """simple docstring"""



     def __init__(				self							:Dict      ,   snake_case							:Optional[Any]=(5, 5)	):





        '''simple docstring'''




        A_       :					Optional[int]        =      np.zeros(snake_case	)
        A_       :					Tuple        =      world_size[0]
        A_       :					Optional[Any]        =      world_size[1]



     def     SCREAMING_SNAKE_CASE		(				self							:Optional[Any]	):





        '''simple docstring'''




        print(self.w	)





     def     SCREAMING_SNAKE_CASE		(				self							:Tuple      ,   snake_case							:int	):





        '''simple docstring'''




        A_       :					Optional[int]        =      [
            (-1, -1),
            (-1, 0),
            (-1, 1),
            (0, -1),
            (0, 1),
            (1, -1),
            (1, 0),
            (1, 1),
        ]
        A_       :					Union[str, Any]        =      cell.position[0]
        A_       :					int        =      cell.position[1]
        A_       :					Optional[int]        =      []
        for n in neughbour_cord:
           A_       :					List[str]        =      current_x + n[0]
           A_       :					Optional[Any]        =      current_y + n[1]
           if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
              A_       :					List[Any]        =      Cell()
              A_       :					Tuple        =      (x, y)
              A_       :					List[Any]        =      cell
              neighbours.append(snake_case	)
        return neighbours




def   __snake_case    (       _lowerCAmelCase			:			List[str]					,					_lowerCAmelCase			:			Optional[Any]					,					_lowerCAmelCase			:			str						)			->    str:
   A_       :					Optional[Any]        =      []
   A_       :					Tuple        =      []
   _open.append(_lowerCAmelCase						)

   while _open:
      A_       :					List[Any]        =      np.argmin([n.f for n in _open]						)
      A_       :					Optional[Any]        =      _open[min_f]
      _closed.append(_open.pop(_lowerCAmelCase						)						)
      if current == goal:
         break
      for n in world.get_neigbours(_lowerCAmelCase						):
         for c in _closed:
            if c == n:
               continue
         A_       :					int        =      current.g + 1
         A_   ,    A_       :					List[str]        =      n.position
         A_   ,    A_       :					Any        =      goal.position
         A_       :					Optional[Any]        =      (ya - ya) ** 2 + (xa - xa) ** 2
         A_       :					Optional[Any]        =      n.h + n.g

         for c in _open:
            if c == n and c.f < n.f:
               continue
         _open.append(_lowerCAmelCase						)
   A_       :					Optional[int]        =      []
   while current.parent is not None:
      path.append(current.position						)
      A_       :					List[Any]        =      current.parent
   path.append(current.position						)
   return path[::-1]


if __name__ == "__main__":
 _lowerCAmelCase				:   Union[str, Any]						       =						Gridworld()
 # Start position and goal
 _lowerCAmelCase				:   Tuple						       =						Cell()
 _lowerCAmelCase				:   str						       =						(0, 0)
 _lowerCAmelCase				:   Union[str, Any]						       =						Cell()
 _lowerCAmelCase				:   List[str]						       =						(4, 4)
 print(F'''path from {start.position} to {goal.position}''')
 _lowerCAmelCase				:   Union[str, Any]						       =						astar(world, start, goal)
 #   Just for visual reasons.
 for i in s:
  _lowerCAmelCase				:   Any						       =						1
 print(world.w)
