

import multiprocessing
from typing import TYPE_CHECKING, Optional, Union

from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream


if TYPE_CHECKING:
					import sqlitea

					import sqlalchemy






class        A_		(       SCREAMING_SNAKE_CASE				):
							def __init__(		self		:			Tuple   ,SCREAMING_SNAKE_CASE__		:			Union[str, Any]   ,SCREAMING_SNAKE_CASE__		:			Optional[Any]   ,SCREAMING_SNAKE_CASE__		:			List[Any] = None   ,SCREAMING_SNAKE_CASE__		:			List[Any] = None   ,SCREAMING_SNAKE_CASE__		:			Optional[int] = False   ,**SCREAMING_SNAKE_CASE__		:			List[str]   ,):
								super().__init__(features=SCREAMING_SNAKE_CASE__   ,cache_dir=SCREAMING_SNAKE_CASE__   ,keep_in_memory=SCREAMING_SNAKE_CASE__   ,**SCREAMING_SNAKE_CASE__)
								__lowerCamelCase				:				Optional[int]					       = Sql(
								    cache_dir=SCREAMING_SNAKE_CASE__   ,features=SCREAMING_SNAKE_CASE__   ,sql=SCREAMING_SNAKE_CASE__   ,con=SCREAMING_SNAKE_CASE__   ,**SCREAMING_SNAKE_CASE__   ,)


							def     lowerCAmelCase     (		self		:			Union[str, Any]):
								__lowerCamelCase				:				Any					       = None
								__lowerCamelCase				:				int					       = None
								__lowerCamelCase				:				Dict					       = None
								__lowerCamelCase				:				Optional[int]					       = None

								self.builder.download_and_prepare(
								    download_config=SCREAMING_SNAKE_CASE__   ,download_mode=SCREAMING_SNAKE_CASE__   ,verification_mode=SCREAMING_SNAKE_CASE__   ,base_path=SCREAMING_SNAKE_CASE__   ,)

								# Build dataset for splits
								__lowerCamelCase				:				Tuple					       = self.builder.as_dataset(
								    split='train'   ,verification_mode=SCREAMING_SNAKE_CASE__   ,in_memory=self.keep_in_memory)
								return dataset






class        A_		:
							def __init__(		self		:			List[str]   ,SCREAMING_SNAKE_CASE__		:			str   ,SCREAMING_SNAKE_CASE__		:			Any   ,SCREAMING_SNAKE_CASE__		:			List[str]   ,SCREAMING_SNAKE_CASE__		:			List[Any] = None   ,SCREAMING_SNAKE_CASE__		:			int = None   ,**SCREAMING_SNAKE_CASE__		:			List[str]   ,):
								if num_proc is not None and num_proc <= 0:
									raise ValueError(F"num_proc {num_proc} must be an integer > 0.")

								__lowerCamelCase				:				Optional[Any]					       = dataset
								__lowerCamelCase				:				Union[str, Any]					       = name
								__lowerCamelCase				:				Optional[int]					       = con
								__lowerCamelCase				:				Optional[int]					       = batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
								__lowerCamelCase				:				Any					       = num_proc
								__lowerCamelCase				:				List[str]					       = to_sql_kwargs
							def     lowerCAmelCase     (		self		:			List[Any]):
								__lowerCamelCase				:				str					       = self.to_sql_kwargs.pop('sql'   ,SCREAMING_SNAKE_CASE__)
								__lowerCamelCase				:				List[str]					       = self.to_sql_kwargs.pop('con'   ,SCREAMING_SNAKE_CASE__)
								__lowerCamelCase				:				Union[str, Any]					       = self.to_sql_kwargs.pop('index'   ,SCREAMING_SNAKE_CASE__)

								__lowerCamelCase				:				Dict					       = self._write(index=SCREAMING_SNAKE_CASE__   ,**self.to_sql_kwargs)
								return written
							def     lowerCAmelCase     (		self		:			List[Any]   ,SCREAMING_SNAKE_CASE__		:			List[str]):
								__lowerCamelCase       , __lowerCamelCase       , __lowerCamelCase				:				int					       = args
								__lowerCamelCase				:				Optional[Any]					       = {**to_sql_kwargs, 'if_exists': 'append'} if offset > 0 else to_sql_kwargs
								__lowerCamelCase				:				Union[str, Any]					       = query_table(
								    table=self.dataset.data   ,key=slice(SCREAMING_SNAKE_CASE__   ,offset + self.batch_size)   ,indices=self.dataset._indices   ,)
								__lowerCamelCase				:				Tuple					       = batch.to_pandas()
								__lowerCamelCase				:				int					       = df.to_sql(self.name   ,self.con   ,index=SCREAMING_SNAKE_CASE__   ,**SCREAMING_SNAKE_CASE__)
								return num_rows or len(SCREAMING_SNAKE_CASE__)


							def     lowerCAmelCase     (		self		:			Any   ,SCREAMING_SNAKE_CASE__		:			str   ,**SCREAMING_SNAKE_CASE__		:			List[Any]):
								__lowerCamelCase				:				List[str]					       = 0

								if self.num_proc is None or self.num_proc == 1:
									for offset in logging.tqdm(
									    range(0   ,len(self.dataset)   ,self.batch_size)   ,unit='ba'   ,disable=not logging.is_progress_bar_enabled()   ,desc='Creating SQL from Arrow format'   ,):
										written += self._batch_sql((offset, index, to_sql_kwargs))
								else:
									__lowerCamelCase       , __lowerCamelCase				:				Dict					       = len(self.dataset), self.batch_size
									with multiprocessing.Pool(self.num_proc) as pool:
										for num_rows in logging.tqdm(
										    pool.imap(
										        self._batch_sql   ,[(offset, index, to_sql_kwargs) for offset in range(0   ,SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__)]   ,)   ,total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size   ,unit='ba'   ,disable=not logging.is_progress_bar_enabled()   ,desc='Creating SQL from Arrow format'   ,):
											written += num_rows

								return written








import heapq as hq
import math
from collections.abc import Iterator







class       lowerCamelCase__   :





     def __init__(self		,     UpperCAmelCase       )     ->   Any:
      _lowercase							      =str(id_       )
      _lowercase							      =None
      _lowercase							      =None
      _lowercase							      =[]
      _lowercase							      ={}  # {vertex:distance}





     def __lt__(self		,     UpperCAmelCase       )     ->   List[str]:
      return self.key < other.key





     def __repr__(self       )     ->   str:
      return self.id





     def      __A					(self		,     UpperCAmelCase       )     ->   Dict:
      self.neighbors.append(UpperCAmelCase       )





     def      __A					(self		,     UpperCAmelCase		,     UpperCAmelCase       )     ->   Optional[Any]:
      _lowercase							      =weight



def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case						)     ->			List[str]:







 """simple docstring"""


 graph[a - 1].add_neighbor(graph[b - 1]						)
 graph[b - 1].add_neighbor(graph[a - 1]						)
 # add the edges:
 graph[a - 1].add_edge(graph[b - 1]     ,						__snake_case						)
 graph[b - 1].add_edge(graph[a - 1]     ,						__snake_case						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			list:







 """simple docstring"""


 _lowercase							      =[]
 for u in graph:
  _lowercase							      =math.inf
  _lowercase							      =None
 _lowercase							      =0
 _lowercase							      =graph[:]
 while q:
  _lowercase							      =min(__snake_case						)
  q.remove(__snake_case						)
  for v in u.neighbors:
   if (v in q) and (u.edges[v.id] < v.key):
    _lowercase							      =u
    _lowercase							      =u.edges[v.id]
 for i in range(1     ,						len(__snake_case						)						):
  a.append((int(graph[i].id						) + 1, int(graph[i].pi.id						) + 1)						)
 return a
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			Iterator[tuple]:







 """simple docstring"""


 for u in graph:
  _lowercase							      =math.inf
  _lowercase							      =None
 _lowercase							      =0

 _lowercase							      =list(__snake_case						)
 hq.heapify(__snake_case						)

 while h:
  _lowercase							      =hq.heappop(__snake_case						)
  for v in u.neighbors:
   if (v in h) and (u.edges[v.id] < v.key):
    _lowercase							      =u
    _lowercase							      =u.edges[v.id]
    hq.heapify(__snake_case						)

 for i in range(1     ,						len(__snake_case						)						):
  yield (int(graph[i].id						) + 1, int(graph[i].pi.id						) + 1)
def 				UpperCAmelCase_					(							)     ->			None:







 """simple docstring"""




if __name__ == "__main__":
  import doctest

  doctest.testmod()

