import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


A     :  Dict					     =       logging.get_logger(__name__)


class   lowerCamelCase					:
  """simple docstring"""







  lowerCamelCase__     =						None



@experimental
def      a__ (		__UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase				):
      if ParallelBackendConfig.backend_name is None:
            return _map_with_multiprocessing_pool(
                __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase				)

      return _map_with_joblib(__UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase				)


def      a__ (		__UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase				):
      SCREAMING_SNAKE_CASE_          =  num_proc if num_proc <= len(__UpperCamelCase				) else len(__UpperCamelCase				)
      SCREAMING_SNAKE_CASE_          =  []  # We organize the splits ourselve (contiguous splits)
      for index in range(__UpperCamelCase				):
            SCREAMING_SNAKE_CASE_          =  len(__UpperCamelCase				) // num_proc
            SCREAMING_SNAKE_CASE_          =  len(__UpperCamelCase				) % num_proc
            SCREAMING_SNAKE_CASE_          =  div * index + min(__UpperCamelCase     ,      __UpperCamelCase				)
            SCREAMING_SNAKE_CASE_          =  start + div + (1 if index < mod else 0)
            split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)				)

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

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

      return mapped


def      a__ (		__UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase				):
      # 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=__UpperCamelCase				):
            return joblib.Parallel()(
                joblib.delayed(__UpperCamelCase				)((function, obj, types, None, True, None)				) for obj in iterable				)





@experimental
@contextlib.contextmanager
def      a__ (		__UpperCamelCase				):
      SCREAMING_SNAKE_CASE_          =  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_          =  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

A     :  Dict					     =       TypeVar("T")


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







  def __init__(							self :       Optional[int]  ,     __magic_name__ :       bool = True   )  ->	None:
        SCREAMING_SNAKE_CASE_          =  {}  # dictionary of lists
        SCREAMING_SNAKE_CASE_          =  directed







  def    __A     (							self :       Dict  ,     __magic_name__ :       T  ,     __magic_name__ :       T   )  ->	GraphAdjacencyList[T]:

        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(__magic_name__   )
                    self.adj_list[destination_vertex].append(__magic_name__   )
              # 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(__magic_name__   )
                    SCREAMING_SNAKE_CASE_          =  [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(__magic_name__   )
                    SCREAMING_SNAKE_CASE_          =  [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:
                    SCREAMING_SNAKE_CASE_          =  [destination_vertex]
                    SCREAMING_SNAKE_CASE_          =  [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(__magic_name__   )
              # 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(__magic_name__   )
                    SCREAMING_SNAKE_CASE_          =  []
              # 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:
                    SCREAMING_SNAKE_CASE_          =  [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:
                    SCREAMING_SNAKE_CASE_          =  [destination_vertex]
                    SCREAMING_SNAKE_CASE_          =  []

        return self







  def __repr__(							self :       int   )  ->	str:
        return pformat(self.adj_list   )


