




class _UpperCamelCase							:
			'''simple docstring'''







			def __init__(			self							: Union[str, Any]	)							->       Optional[Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      int				     =       0
				SCREAMING_SNAKE_CASE   :      Any				     =       0
				SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       {}
			def 							__UpperCamelCase (			self							: str      ,      a							: List[Any]	)							->       int:

				"""simple docstring"""

				if vertex not in self.adjacency:
					SCREAMING_SNAKE_CASE   :      Any				     =       {}
					self.num_vertices += 1
			def 							__UpperCamelCase (			self							: int      ,      a							: Any      ,      a							: List[Any]      ,      a							: Union[str, Any]	)							->       str:

				"""simple docstring"""

				self.add_vertex(_a	)
				self.add_vertex(_a	)

				if head == tail:
					return

				SCREAMING_SNAKE_CASE   :      Optional[int]				     =       weight
				SCREAMING_SNAKE_CASE   :      int				     =       weight
			def 							__UpperCamelCase (			self							: List[str]	)							->       List[str]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      List[str]				     =       self.get_edges()
				for edge in edges:
					SCREAMING_SNAKE_CASE   :      Tuple				     =       edge
					edges.remove((tail, head, weight)	)
				for i in range(len(_a	)	):
					SCREAMING_SNAKE_CASE   :      Optional[int]				     =       list(edges[i]	)

				edges.sort(key=lambda a	: e[2]	)
				for i in range(len(_a	) - 1	):
					if edges[i][2] >= edges[i + 1][2]:
						SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       edges[i][2] + 1
				for edge in edges:
					SCREAMING_SNAKE_CASE   :      Any				     =       edge
					SCREAMING_SNAKE_CASE   :      Any				     =       weight
					SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       weight
			def __str__(			self							: Optional[int]	)							->       Optional[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      Any				     =       """"""
				for tail in self.adjacency:
					for head in self.adjacency[tail]:
						SCREAMING_SNAKE_CASE   :      str				     =       self.adjacency[head][tail]
						string += F"{head} -> {tail} == {weight}\n"
				return string.rstrip("\n"	)
			def 							__UpperCamelCase (			self							: Dict	)							->       Tuple:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      str				     =       []
				for tail in self.adjacency:
					for head in self.adjacency[tail]:
						output.append((tail, head, self.adjacency[head][tail])	)
				return output
			def 							__UpperCamelCase (			self							: Any	)							->       str:

				"""simple docstring"""

				return self.adjacency.keys()
			@staticmethod
			def 							__UpperCamelCase (			a							: List[Any]=None      ,      a							: List[str]=None	)							->       Any:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      str				     =       Graph()
				if vertices is None:
					SCREAMING_SNAKE_CASE   :      List[Any]				     =       []
				if edges is None:
					SCREAMING_SNAKE_CASE   :      Optional[int]				     =       []
				for vertex in vertices:
					g.add_vertex(_a	)
				for edge in edges:
					g.add_edge(*_a	)
				return g






			class _UpperCamelCase							:
						'''simple docstring'''







						def __init__(			self							: Dict	)							->       Optional[Any]:

							"""simple docstring"""

							SCREAMING_SNAKE_CASE   :      int				     =       {}
							SCREAMING_SNAKE_CASE   :      List[str]				     =       {}
						def __len__(			self							: str	)							->       Optional[int]:

							"""simple docstring"""

							return len(self.parent	)
						def 							__UpperCamelCase (			self							: int      ,      a							: Dict	)							->       Union[str, Any]:

							"""simple docstring"""

							if item in self.parent:
								return self.find(_a	)

							SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       item
							SCREAMING_SNAKE_CASE   :      Any				     =       0
							return item
						def 							__UpperCamelCase (			self							: Optional[Any]      ,      a							: Union[str, Any]	)							->       Tuple:

							"""simple docstring"""

							if item not in self.parent:
								return self.make_set(_a	)
							if item != self.parent[item]:
								SCREAMING_SNAKE_CASE   :      Tuple				     =       self.find(self.parent[item]	)
							return self.parent[item]






						def 							__UpperCamelCase (			self							: Optional[Any]      ,      a							: str      ,      a							: List[Any]	)							->       Optional[int]:

							"""simple docstring"""

							SCREAMING_SNAKE_CASE   :      int				     =       self.find(_a	)
							SCREAMING_SNAKE_CASE   :      Any				     =       self.find(_a	)

							if roota == roota:
								return roota

							if self.rank[roota] > self.rank[roota]:
								SCREAMING_SNAKE_CASE   :      Optional[int]				     =       roota
								return roota

							if self.rank[roota] < self.rank[roota]:
								SCREAMING_SNAKE_CASE   :      Optional[int]				     =       roota
								return roota

							if self.rank[roota] == self.rank[roota]:
								self.rank[roota] += 1
								SCREAMING_SNAKE_CASE   :      Optional[int]				     =       roota
								return roota
							return None

			@staticmethod
			def 							__UpperCamelCase (			a							: str	)							->       int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      List[Any]				     =       graph.num_vertices

				SCREAMING_SNAKE_CASE   :      Optional[int]				     =       Graph.UnionFind()
				SCREAMING_SNAKE_CASE   :      List[str]				     =       []
				while num_components > 1:
					SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       {}
					for vertex in graph.get_vertices():
						SCREAMING_SNAKE_CASE   :      List[Any]				     =       -1

					SCREAMING_SNAKE_CASE   :      List[str]				     =       graph.get_edges()
					for edge in edges:
						SCREAMING_SNAKE_CASE   :      Any				     =       edge
						edges.remove((tail, head, weight)	)
					for edge in edges:
						SCREAMING_SNAKE_CASE   :      int				     =       edge
						SCREAMING_SNAKE_CASE   :      Tuple				     =       union_find.find(_a	)
						SCREAMING_SNAKE_CASE   :      str				     =       union_find.find(_a	)
						if seta != seta:
							if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
								SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       [head, tail, weight]

							if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
								SCREAMING_SNAKE_CASE   :      List[str]				     =       [head, tail, weight]
					for vertex in cheap_edge:
						if cheap_edge[vertex] != -1:
							SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       cheap_edge[vertex]
							if union_find.find(_a	) != union_find.find(_a	):
								union_find.union(_a      ,      _a	)
								mst_edges.append(cheap_edge[vertex]	)
								SCREAMING_SNAKE_CASE   :      Any				     =       num_components - 1
				SCREAMING_SNAKE_CASE   :      List[str]				     =       Graph.build(edges=_a	)
				return mst


import itertools
from dataclasses import dataclass
from typing import List, Optional

import pyarrow as pa
import pyarrow.parquet as pq

import datasets
from datasets.table import table_cast


a_						     =    datasets.utils.logging.get_logger(__name__)






@dataclass
class _UpperCamelCase							(							datasets.BuilderConfig   ):
			'''simple docstring'''







			lowerCamelCase__           =10000
			lowerCamelCase__           =None
			lowerCamelCase__           =None






class _UpperCamelCase							(							datasets.ArrowBasedBuilder   ):
			'''simple docstring'''







			lowerCamelCase__           =ParquetConfig
			def 							__UpperCamelCase (			self							: str	)							->       str:

				"""simple docstring"""

				return datasets.DatasetInfo(features=self.config.features	)
			def 							__UpperCamelCase (			self							: Dict      ,      a							: List[Any]	)							->       Tuple:

				"""simple docstring"""

				if not self.config.data_files:
					raise ValueError(F"At least one data file must be specified, but got data_files={self.config.data_files}"	)
				SCREAMING_SNAKE_CASE   :      Tuple				     =       dl_manager.download_and_extract(self.config.data_files	)
				if isinstance(a      ,      (str, list, tuple)	):
					SCREAMING_SNAKE_CASE   :      Dict				     =       data_files
					if isinstance(a      ,      a	):
						SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       [files]
					# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
					SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       [dl_manager.iter_files(a	) for file in files]
					return [datasets.SplitGenerator(name=datasets.Split.TRAIN      ,      gen_kwargs={"files": files}	)]
				SCREAMING_SNAKE_CASE   :      str				     =       []
				for split_name, files in data_files.items():
					if isinstance(a      ,      a	):
						SCREAMING_SNAKE_CASE   :      Optional[int]				     =       [files]
					# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
					SCREAMING_SNAKE_CASE   :      Tuple				     =       [dl_manager.iter_files(a	) for file in files]
					# Infer features is they are stoed in the arrow schema
					if self.info.features is None:
						for file in itertools.chain.from_iterable(a	):
							with open(a      ,      "rb"	) as f:
								SCREAMING_SNAKE_CASE   :      Dict				     =       datasets.Features.from_arrow_schema(pq.read_schema(a	)	)
							break
					splits.append(datasets.SplitGenerator(name=a      ,      gen_kwargs={"files": files}	)	)
				return splits
			def 							__UpperCamelCase (			self							: Dict      ,      a							: pa.Table	)							->       pa.Table:

				"""simple docstring"""

				if self.info.features is not None:
					# more expensive cast to support nested features with keys in a different order
					# allows str <-> int/float or str to Audio for example
					SCREAMING_SNAKE_CASE   :      str				     =       table_cast(a      ,      self.info.features.arrow_schema	)
				return pa_table






			def 							__UpperCamelCase (			self							: List[str]      ,      a							: Optional[Any]	)							->       Optional[Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      Any				     =       self.info.features.arrow_schema if self.info.features is not None else None
				if self.info.features is not None and self.config.columns is not None:
					if sorted(field.name for field in schema	) != sorted(self.config.columns	):
						raise ValueError(
						    F"Tried to load parquet data with columns '{self.config.columns}' with mismatching features '{self.info.features}'"	)
				for file_idx, file in enumerate(itertools.chain.from_iterable(a	)	):
					with open(a      ,      "rb"	) as f:
						SCREAMING_SNAKE_CASE   :      Optional[int]				     =       pq.ParquetFile(a	)
						try:
							for batch_idx, record_batch in enumerate(
							    parquet_file.iter_batches(batch_size=self.config.batch_size      ,      columns=self.config.columns	)	):
								SCREAMING_SNAKE_CASE   :      int				     =       pa.Table.from_batches([record_batch]	)
								# Uncomment for debugging (will print the Arrow table size and elements)
								# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
								# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
								yield F"{file_idx}_{batch_idx}", self._cast_table(a	)
						except ValueError as e:
							logger.error(F"Failed to read file '{file}' with error {type(a	)}: {e}"	)
							raise