




from __future__ import annotations

from typing import Any


class 							__UpperCamelCase			:





				'''simple docstring'''



				def __init__( self       , UpperCAmelCase_						):
											lowerCAmelCase   =		num_of_nodes
											lowerCAmelCase   =		[]
											lowerCAmelCase   =		{}



				def       __snake_case		( self       , UpperCAmelCase_       , UpperCAmelCase_       , UpperCAmelCase_						):
											self.m_edges.append([u_node, v_node, weight]						)



				def       __snake_case		( self       , UpperCAmelCase_						):

											if self.m_component[u_node] == u_node:
																		return u_node
											return self.find_component(self.m_component[u_node]						)



				def       __snake_case		( self       , UpperCAmelCase_						):

											if self.m_component[u_node] != u_node:
																		for k in self.m_component:
																									lowerCAmelCase   =		self.find_component(UpperCAmelCase_						)



				def       __snake_case		( self       , UpperCAmelCase_       , UpperCAmelCase_       , UpperCAmelCase_						):

											if component_size[u_node] <= component_size[v_node]:
																		lowerCAmelCase   =		v_node
																		component_size[v_node] += component_size[u_node]
																		self.set_component(UpperCAmelCase_						)

											elif component_size[u_node] >= component_size[v_node]:
																		lowerCAmelCase   =		self.find_component(UpperCAmelCase_						)
																		component_size[u_node] += component_size[v_node]
																		self.set_component(UpperCAmelCase_						)






				def       __snake_case		( self						):
											lowerCAmelCase   =		[]
											lowerCAmelCase   =		0

											lowerCAmelCase   =		[-1] * self.m_num_of_nodes

											# A list of components (initialized to all of the nodes)
											for node in range(self.m_num_of_nodes						):
																		self.m_component.update({node: node}						)
																		component_size.append(1						)

											lowerCAmelCase   =		self.m_num_of_nodes

											while num_of_components > 1:
																		for edge in self.m_edges:
																									lowerCAmelCase   ,     lowerCAmelCase   ,     lowerCAmelCase   =		edge

																									lowerCAmelCase   =		self.m_component[u]
																									lowerCAmelCase   =		self.m_component[v]

																									if u_component != v_component:

																																for component in (u_component, v_component):
																																							if (
																																							    minimum_weight_edge[component] == -1
																																							    or minimum_weight_edge[component][2] > w
																																							):
																																														lowerCAmelCase   =		[u, v, w]

																		for edge in minimum_weight_edge:
																									if isinstance(UpperCAmelCase_       , UpperCAmelCase_						):
																																lowerCAmelCase   ,     lowerCAmelCase   ,     lowerCAmelCase   =		edge

																																lowerCAmelCase   =		self.m_component[u]
																																lowerCAmelCase   =		self.m_component[v]

																																if u_component != v_component:
																																							mst_weight += w
																																							self.union(UpperCAmelCase_       , UpperCAmelCase_       , UpperCAmelCase_						)
																																							print(F"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""						)
																																							num_of_components -= 1

																		lowerCAmelCase   =		[-1] * self.m_num_of_nodes
											print(F"""The total weight of the minimal spanning tree is: {mst_weight}"""						)




def       UpperCAmelCase       (     ):
							pass


if __name__ == "__main__":
		import doctest

		doctest.testmod()









import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


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


@dataclass
class 							__UpperCamelCase			( datasets.BuilderConfig  ):





				'''simple docstring'''



				__a							: Optional[datasets.Features]										=None
				__a							: str										="utf-8"
				__a							: Optional[str]										=None
				__a							: Optional[str]										=None
				__a							: bool										=True  # deprecated
				__a							: Optional[int]										=None  # deprecated
				__a							: int										=1_0 << 2_0  # 10MB
				__a							: Optional[bool]										=None




class 							__UpperCamelCase			( datasets.ArrowBasedBuilder  ):





				'''simple docstring'''



				__a							: str										=JsonConfig



				def       __snake_case		( self						):
											if self.config.block_size is not None:
																		logger.warning('''The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead'''						)
																		lowerCAmelCase   =		self.config.block_size
											if self.config.use_threads is not True:
																		logger.warning(
																		    '''The JSON loader parameter `use_threads` is deprecated and doesn\'t have any effect anymore.'''						)
											if self.config.newlines_in_values is not None:
																		raise ValueError('''The JSON loader parameter `newlines_in_values` is no longer supported'''						)
											return datasets.DatasetInfo(features=self.config.features						)



				def       __snake_case		( self       , UpperCAmelCase_						):
											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}"""						)
											lowerCAmelCase   =		dl_manager.download_and_extract(self.config.data_files						)
											if isinstance(UpperCAmelCase_       , (str, list, tuple)						):
																		lowerCAmelCase   =		data_files
																		if isinstance(UpperCAmelCase_       , UpperCAmelCase_						):
																									lowerCAmelCase   =		[files]
																		lowerCAmelCase   =		[dl_manager.iter_files(UpperCAmelCase_						) for file in files]
																		return [datasets.SplitGenerator(name=datasets.Split.TRAIN       , gen_kwargs={'''files''': files}						)]
											lowerCAmelCase   =		[]
											for split_name, files in data_files.items():
																		if isinstance(UpperCAmelCase_       , UpperCAmelCase_						):
																									lowerCAmelCase   =		[files]
																		lowerCAmelCase   =		[dl_manager.iter_files(UpperCAmelCase_						) for file in files]
																		splits.append(datasets.SplitGenerator(name=UpperCAmelCase_       , gen_kwargs={'''files''': files}						)						)
											return splits



				def       __snake_case		( self       , UpperCAmelCase_						):
											if self.config.features is not None:
																		# adding missing columns
																		for column_name in set(self.config.features						) - set(pa_table.column_names						):
																									lowerCAmelCase   =		self.config.features.arrow_schema.field(UpperCAmelCase_						).type
																									lowerCAmelCase   =		pa_table.append_column(UpperCAmelCase_       , pa.array([None] * len(UpperCAmelCase_						)       , type=UpperCAmelCase_						)						)
																		# more expensive cast to support nested structures with keys in a different order
																		# allows str <-> int/float or str to Audio for example
																		lowerCAmelCase   =		table_cast(UpperCAmelCase_       , self.config.features.arrow_schema						)
											return pa_table






				def       __snake_case		( self       , UpperCAmelCase_						):
											for file_idx, file in enumerate(itertools.chain.from_iterable(UpperCAmelCase_						)						):
																		# If the file is one json object and if we need to look at the list of items in one specific field
																		if self.config.field is not None:
																									with open(UpperCAmelCase_       , encoding=self.config.encoding       , errors=self.config.encoding_errors						) as f:
																																lowerCAmelCase   =		json.load(UpperCAmelCase_						)

																									# We keep only the field we are interested in
																									lowerCAmelCase   =		dataset[self.config.field]

																									# We accept two format: a list of dicts or a dict of lists
																									if isinstance(UpperCAmelCase_       , (list, tuple)						):
																																lowerCAmelCase   =		set().union(*[row.keys() for row in dataset]						)
																																lowerCAmelCase   =		{col: [row.get(UpperCAmelCase_						) for row in dataset] for col in keys}
																									else:
																																lowerCAmelCase   =		dataset
																									lowerCAmelCase   =		pa.Table.from_pydict(UpperCAmelCase_						)
																									yield file_idx, self._cast_table(UpperCAmelCase_						)

																		# If the file has one json object per line
																		else:
																									with open(UpperCAmelCase_       , '''rb'''						) as f:
																																lowerCAmelCase   =		0
																																# Use block_size equal to the chunk size divided by 32 to leverage multithreading
																																# Set a default minimum value of 16kB if the chunk size is really small
																																lowerCAmelCase   =		max(self.config.chunksize // 32       , 16 << 10						)
																																lowerCAmelCase   =		(
																																    self.config.encoding_errors if self.config.encoding_errors is not None else '''strict'''
																																)
																																while True:
																																							lowerCAmelCase   =		f.read(self.config.chunksize						)
																																							if not batch:
																																														break
																																							# Finish current line
																																							try:
																																														batch += f.readline()
																																							except (AttributeError, io.UnsupportedOperation):
																																														batch += readline(UpperCAmelCase_						)
																																							# PyArrow only accepts utf-8 encoded bytes
																																							if self.config.encoding != "utf-8":
																																														lowerCAmelCase   =		batch.decode(self.config.encoding       , errors=UpperCAmelCase_						).encode('''utf-8'''						)
																																							try:
																																														while True:
																																																					try:
																																																												lowerCAmelCase   =		paj.read_json(
																																																												    io.BytesIO(UpperCAmelCase_						)       , read_options=paj.ReadOptions(block_size=UpperCAmelCase_						)						)
																																																												break
																																																					except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																																																												if (
																																																												    isinstance(UpperCAmelCase_       , pa.ArrowInvalid						)
																																																												    and "straddling" not in str(UpperCAmelCase_						)
																																																												    or block_size > len(UpperCAmelCase_						)
																																																												):
																																																																			raise
																																																												else:
																																																																			# Increase the block size in case it was too small.
																																																																			# The block size will be reset for the next file.
																																																																			logger.debug(
																																																																			    F"""Batch of {len(UpperCAmelCase_						)} bytes couldn't be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}."""						)
																																																																			block_size *= 2
																																							except pa.ArrowInvalid as e:
																																														try:
																																																					with open(
																																																					    UpperCAmelCase_       , encoding=self.config.encoding       , errors=self.config.encoding_errors						) as f:
																																																												lowerCAmelCase   =		json.load(UpperCAmelCase_						)
																																														except json.JSONDecodeError:
																																																					logger.error(F"""Failed to read file '{file}' with error {type(UpperCAmelCase_						)}: {e}"""						)
																																																					raise e
																																														# If possible, parse the file as a list of json objects and exit the loop
																																														if isinstance(UpperCAmelCase_       , UpperCAmelCase_						):  # list is the only sequence type supported in JSON
																																																					try:
																																																												lowerCAmelCase   =		set().union(*[row.keys() for row in dataset]						)
																																																												lowerCAmelCase   =		{col: [row.get(UpperCAmelCase_						) for row in dataset] for col in keys}
																																																												lowerCAmelCase   =		pa.Table.from_pydict(UpperCAmelCase_						)
																																																					except (pa.ArrowInvalid, AttributeError) as e:
																																																												logger.error(F"""Failed to read file '{file}' with error {type(UpperCAmelCase_						)}: {e}"""						)
																																																												raise ValueError(F"""Not able to read records in the JSON file at {file}."""						) from None
																																																					yield file_idx, self._cast_table(UpperCAmelCase_						)
																																																					break
																																														else:
																																																					logger.error(F"""Failed to read file '{file}' with error {type(UpperCAmelCase_						)}: {e}"""						)
																																																					raise ValueError(
																																																					    F"""Not able to read records in the JSON file at {file}. """
																																																					    F"""You should probably indicate the field of the JSON file containing your records. """
																																																					    F"""This JSON file contain the following fields: {str(list(dataset.keys()						)						)}. """
																																																					    F"""Select the correct one and provide it as `field='XXX'` to the dataset loading method. """						) from None
                        # 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 (file_idx, batch_idx), self._cast_table(UpperCAmelCase_						)
																																							batch_idx += 1



