






import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


_SCREAMING_SNAKE_CASE   =  logging.get_logger(__name__)






class 					SCREAMING_SNAKE_CASE_  :
       """simple docstring"""


       __lowerCAmelCase    :		Union[str, Any]					=None





@experimental
def        _snake_case   (_snake_case				:       Optional[Any]      ,    _snake_case				:       Dict      ,    _snake_case				:       str      ,    _snake_case				:       List[Any]      ,    _snake_case				:       Any      ,    _snake_case				:       str      ,    _snake_case				:       str)					->	Optional[Any]:
   if ParallelBackendConfig.backend_name is None:
      return _map_with_multiprocessing_pool(
          _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case)

   return _map_with_joblib(_snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case      ,    _snake_case)





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

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

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

   return mapped





def        _snake_case   (_snake_case				:       int      ,    _snake_case				:       Tuple      ,    _snake_case				:       Optional[Any]      ,    _snake_case				:       Optional[Any]      ,    _snake_case				:       Optional[int]      ,    _snake_case				:       Any      ,    _snake_case				:       int)					->	Optional[int]:
   # progress bar is not yet supported for _map_with_joblib, because tqdm couldn't accurately be applied to joblib,
   # and it requires monkey-patching joblib internal classes which is subject to change
   import joblib

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





@experimental
@contextlib.contextmanager
def        _snake_case   (_snake_case				:       str)					->	Any:
   _lowercase              =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:
      _lowercase              =None










# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

_SCREAMING_SNAKE_CASE   =  TypeVar("T")






class 					SCREAMING_SNAKE_CASE_  (       Generic[T] ):
       """simple docstring"""


       def __init__(				self	:List[Any],      snake_case	:bool = True):



          """simple docstring"""

          _lowercase              ={}  # dictionary of lists
          _lowercase              =directed





       def 				UpperCamelCase__						(				self	:Optional[Any],      snake_case	:T,      snake_case	:T):



          """simple docstring"""

          if not self.directed:  # For undirected graphs
             # if both source vertex and destination vertex are both present in the
             # adjacency list, add destination vertex to source vertex list of adjacent
             # vertices and add source vertex to destination vertex list of adjacent
             # vertices.
             if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                self.adj_list[source_vertex].append(snake_case)
                self.adj_list[destination_vertex].append(snake_case)
             # if only source vertex is present in adjacency list, add destination vertex
             # to source vertex list of adjacent vertices, then create a new vertex with
             # destination vertex as key and assign a list containing the source vertex
             # as it's first adjacent vertex.
             elif source_vertex in self.adj_list:
                self.adj_list[source_vertex].append(snake_case)
                _lowercase              =[source_vertex]
             # if only destination vertex is present in adjacency list, add source vertex
             # to destination vertex list of adjacent vertices, then create a new vertex
             # with source vertex as key and assign a list containing the source vertex
             # as it's first adjacent vertex.
             elif destination_vertex in self.adj_list:
                self.adj_list[destination_vertex].append(snake_case)
                _lowercase              =[destination_vertex]
             # if both source vertex and destination vertex are not present in adjacency
             # list, create a new vertex with source vertex as key and assign a list
             # containing the destination vertex as it's first adjacent vertex also
             # create a new vertex with destination vertex as key and assign a list
             # containing the source vertex as it's first adjacent vertex.
             else:
                _lowercase              =[destination_vertex]
                _lowercase              =[source_vertex]
          else:  # For directed graphs
             # if both source vertex and destination vertex are present in adjacency
             # list, add destination vertex to source vertex list of adjacent vertices.
             if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                self.adj_list[source_vertex].append(snake_case)
             # if only source vertex is present in adjacency list, add destination
             # vertex to source vertex list of adjacent vertices and create a new vertex
             # with destination vertex as key, which has no adjacent vertex
             elif source_vertex in self.adj_list:
                self.adj_list[source_vertex].append(snake_case)
                _lowercase              =[]
             # if only destination vertex is present in adjacency list, create a new
             # vertex with source vertex as key and assign a list containing destination
             # vertex as first adjacent vertex
             elif destination_vertex in self.adj_list:
                _lowercase              =[destination_vertex]
             # if both source vertex and destination vertex are not present in adjacency
             # list, create a new vertex with source vertex as key and a list containing
             # destination vertex as it's first adjacent vertex. Then create a new vertex
             # with destination vertex as key, which has no adjacent vertex
             else:
                _lowercase              =[destination_vertex]
                _lowercase              =[]

          return self





       def __repr__(				self	:Optional[int]):



          """simple docstring"""

          return pformat(self.adj_list)


