






'''simple docstring'''




import argparse
import os
import re


__lowerCamelCase   :					Optional[int]   							=					'''src/transformers'''

# Pattern that looks at the indentation in a line.
__lowerCamelCase   :					List[Any]   							=					re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
__lowerCamelCase   :					List[Any]   							=					re.compile(R'''^\s*"([^"]+)":''')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
__lowerCamelCase   :					Optional[Any]   							=					re.compile(R'''^\s*_import_structure\["([^"]+)"\]''')
# Pattern that matches `"key",` and puts `key` in group 0.
__lowerCamelCase   :					List[str]   							=					re.compile(R'''^\s*"([^"]+)",\s*$''')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
__lowerCamelCase   :					Dict   							=					re.compile(R'''\[([^\]]+)\]''')

def 	__UpperCAmelCase       ( __magic_name__						)->    Optional[Any]:



			"""simple docstring"""



			snake_case_				:					Optional[Any]   =       _re_indent.search(__magic_name__						)
			return "" if search is None else search.groups()[0]

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__=""     ,__magic_name__=None     ,__magic_name__=None						)->    Optional[Any]:



			"""simple docstring"""



			snake_case_				:					Optional[int]   =       0
			snake_case_				:					Optional[int]   =       code.split("\n"						)
			if start_prompt is not None:
						while not lines[index].startswith(__magic_name__						):
									index += 1
						snake_case_				:					str   =       ["\n".join(lines[:index]						)]
			else:
						snake_case_				:					Dict   =       []

			# We split into blocks until we get to the `end_prompt` (or the end of the block).
			snake_case_				:					Optional[Any]   =       [lines[index]]
			index += 1
			while index < len(__magic_name__						) and (end_prompt is None or not lines[index].startswith(__magic_name__						)):
						if len(lines[index]						) > 0 and get_indent(lines[index]						) == indent_level:
									if len(__magic_name__						) > 0 and get_indent(current_block[-1]						).startswith(indent_level + " "						):
												current_block.append(lines[index]						)
												blocks.append("\n".join(__magic_name__						)						)
												if index < len(__magic_name__						) - 1:
															snake_case_				:					str   =       [lines[index + 1]]
															index += 1
												else:
															snake_case_				:					Tuple   =       []
									else:
												blocks.append("\n".join(__magic_name__						)						)
												snake_case_				:					Any   =       [lines[index]]
						else:
									current_block.append(lines[index]						)
						index += 1

			# Adds current block if it's nonempty.
			if len(__magic_name__						) > 0:
						blocks.append("\n".join(__magic_name__						)						)

			# Add final block after end_prompt if provided.
			if end_prompt is not None and index < len(__magic_name__						):
						blocks.append("\n".join(lines[index:]						)						)

			return blocks

def 	__UpperCAmelCase       ( __magic_name__						)->    Union[str, Any]:



			"""simple docstring"""



			def _inner(__magic_name__						):
						return key(__magic_name__						).lower().replace("_"     ,""						)

			return _inner

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__=None						)->    Dict:



			"""simple docstring"""



			def noop(__magic_name__						):
						return x

			if key is None:
						snake_case_				:					Dict   =       noop
			# Constants are all uppercase, they go first.
			snake_case_				:					Dict   =       [obj for obj in objects if key(__magic_name__						).isupper()]
			# Classes are not all uppercase but start with a capital, they go second.
			snake_case_				:					Dict   =       [obj for obj in objects if key(__magic_name__						)[0].isupper() and not key(__magic_name__						).isupper()]
			# Functions begin with a lowercase, they go last.
			snake_case_				:					str   =       [obj for obj in objects if not key(__magic_name__						)[0].isupper()]

			snake_case_				:					List[Any]   =       ignore_underscore(__magic_name__						)
			return sorted(__magic_name__     ,key=__magic_name__						) + sorted(__magic_name__     ,key=__magic_name__						) + sorted(__magic_name__     ,key=__magic_name__						)

def 	__UpperCAmelCase       ( __magic_name__						)->    Union[str, Any]:



			"""simple docstring"""



			def _replace(__magic_name__						):
						snake_case_				:					Any   =       match.groups()[0]
						if "," not in imports:
									return F'''[{imports}]'''
						snake_case_				:					Tuple   =       [part.strip().replace("\""     ,""						) for part in imports.split(","						)]
						# We will have a final empty element if the line finished with a comma.
						if len(keys[-1]						) == 0:
									snake_case_				:					Tuple   =       keys[:-1]
						return "[" + ", ".join([F'''"{k}"''' for k in sort_objects(__magic_name__						)]						) + "]"

			snake_case_				:					str   =       import_statement.split("\n"						)
			if len(__magic_name__						) > 3:
						# Here we have to sort internal imports that are on several lines (one per name):
						# key: [
						#     "object1",
						#     "object2",
						#     ...
						# ]

						# We may have to ignore one or two lines on each side.
						snake_case_				:					Tuple   =       2 if lines[1].strip() == "[" else 1
						snake_case_				:					Dict   =       [(i, _re_strip_line.search(__magic_name__						).groups()[0]) for i, line in enumerate(lines[idx:-idx]						)]
						snake_case_				:					Optional[Any]   =       sort_objects(__magic_name__     ,key=lambda __magic_name__						: x[1]						)
						snake_case_				:					Optional[int]   =       [lines[x[0] + idx] for x in sorted_indices]
						return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]						)
			elif len(__magic_name__						) == 3:
						# Here we have to sort internal imports that are on one separate line:
						# key: [
						#     "object1", "object2", ...
						# ]
						if _re_bracket_content.search(lines[1]						) is not None:
									snake_case_				:					int   =       _re_bracket_content.sub(_replace     ,lines[1]						)
						else:
									snake_case_				:					str   =       [part.strip().replace("\""     ,""						) for part in lines[1].split(","						)]
									# We will have a final empty element if the line finished with a comma.
									if len(keys[-1]						) == 0:
												snake_case_				:					List[Any]   =       keys[:-1]
									snake_case_				:					List[Any]   =       get_indent(lines[1]						) + ", ".join([F'''"{k}"''' for k in sort_objects(__magic_name__						)]						)
						return "\n".join(__magic_name__						)
			else:
						# Finally we have to deal with imports fitting on one line
						snake_case_				:					Optional[int]   =       _re_bracket_content.sub(_replace     ,__magic_name__						)
						return import_statement

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__=True						)->    Union[str, Any]:



			"""simple docstring"""



			with open(__magic_name__     ,encoding="utf-8"						) as f:
						snake_case_				:					List[Any]   =       f.read()

			if "_import_structure" not in code:
						return

			# Blocks of indent level 0
			snake_case_				:					List[Any]   =       split_code_in_indented_blocks(
			    __magic_name__     ,start_prompt="_import_structure = {"     ,end_prompt="if TYPE_CHECKING:"						)

			# We ignore block 0 (everything untils start_prompt) and the last block (everything after end_prompt).
			for block_idx in range(1     ,len(__magic_name__						) - 1						):
						# Check if the block contains some `_import_structure`s thingy to sort.
						snake_case_				:					List[str]   =       main_blocks[block_idx]
						snake_case_				:					str   =       block.split("\n"						)

						# Get to the start of the imports.
						snake_case_				:					Optional[Any]   =       0
						while line_idx < len(__magic_name__						) and "_import_structure" not in block_lines[line_idx]:
									# Skip dummy import blocks
									if "import dummy" in block_lines[line_idx]:
												snake_case_				:					str   =       len(__magic_name__						)
									else:
												line_idx += 1
						if line_idx >= len(__magic_name__						):
									continue

						# Ignore beginning and last line: they don't contain anything.
						snake_case_				:					Optional[Any]   =       "\n".join(block_lines[line_idx:-1]						)
						snake_case_				:					Optional[Any]   =       get_indent(block_lines[1]						)
						# Slit the internal block into blocks of indent level 1.
						snake_case_				:					Union[str, Any]   =       split_code_in_indented_blocks(__magic_name__     ,indent_level=__magic_name__						)
						# We have two categories of import key: list or _import_structure[key].append/extend
						snake_case_				:					Dict   =       _re_direct_key if "_import_structure = {" in block_lines[0] else _re_indirect_key
						# Grab the keys, but there is a trap: some lines are empty or just comments.
						snake_case_				:					List[str]   =       [(pattern.search(__magic_name__						).groups()[0] if pattern.search(__magic_name__						) is not None else None) for b in internal_blocks]
						# We only sort the lines with a key.
						snake_case_				:					Dict   =       [(i, key) for i, key in enumerate(__magic_name__						) if key is not None]
						snake_case_				:					str   =       [x[0] for x in sorted(__magic_name__     ,key=lambda __magic_name__						: x[1]						)]

						# We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
						snake_case_				:					Optional[Any]   =       0
						snake_case_				:					Any   =       []
						for i in range(len(__magic_name__						)						):
									if keys[i] is None:
												reorderded_blocks.append(internal_blocks[i]						)
									else:
												snake_case_				:					List[Any]   =       sort_objects_in_import(internal_blocks[sorted_indices[count]]						)
												reorderded_blocks.append(__magic_name__						)
												count += 1

        # And we put our main block back together with its first and last line.
						snake_case_				:					Optional[Any]   =       "\n".join(block_lines[:line_idx] + reorderded_blocks + [block_lines[-1]]						)

			if code != "\n".join(__magic_name__						):
						if check_only:
									return True
						else:
									print(F'''Overwriting {file}.'''						)
									with open(__magic_name__     ,"w"     ,encoding="utf-8"						) as f:
												f.write("\n".join(__magic_name__						)						)

def 	__UpperCAmelCase       ( __magic_name__=True						)->    Optional[int]:



			"""simple docstring"""



			snake_case_				:					Dict   =       []
			for root, _, files in os.walk(__magic_name__						):
						if "__init__.py" in files:
									snake_case_				:					Union[str, Any]   =       sort_imports(os.path.join(__magic_name__     ,"__init__.py"						)     ,check_only=__magic_name__						)
									if result:
												snake_case_				:					Optional[int]   =       [os.path.join(__magic_name__     ,"__init__.py"						)]
			if len(__magic_name__						) > 0:
						raise ValueError(F'''Would overwrite {len(__magic_name__						)} files, run `make style`.'''						)


if __name__ == "__main__":
		__lowerCamelCase   :					Optional[Any]   							=					argparse.ArgumentParser()
		parser.add_argument('''--check_only''', action='''store_true''', help='''Whether to only check or fix style.''')
		__lowerCamelCase   :					Any   							=					parser.parse_args()

		sort_imports_in_all_inits(check_only=args.check_only)












'''simple docstring'''




import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


__lowerCamelCase   :					Optional[Any]   							=					datasets.utils.logging.get_logger(__name__)

__lowerCamelCase   :					List[str]   							=					['''names''', '''prefix''']
__lowerCamelCase   :					int   							=					['''warn_bad_lines''', '''error_bad_lines''', '''mangle_dupe_cols''']
__lowerCamelCase   :					str   							=					['''encoding_errors''', '''on_bad_lines''']
__lowerCamelCase   :					Optional[Any]   							=					['''date_format''']







@dataclass
class    A_	(datasets.BuilderConfig							):
							"""simple docstring"""




							a__   		=	","
							a__   		=	None
							a__   		=	"infer"
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	True
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	False
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	True
							a__   		=	True
							a__   		=	False
							a__   		=	True
							a__   		=	None
							a__   		=	"."
							a__   		=	None
							a__   		=	'"'
							a__   		=	0
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	None
							a__   		=	True
							a__   		=	True
							a__   		=	0
							a__   		=	True
							a__   		=	False
							a__   		=	None
							a__   		=	10000
							a__   		=	None
							a__   		=	"strict"
							a__   		=	"error"
							a__   		=	None

							def 							_A	(		self			:List[str]				)				->  Any:


										'''simple docstring'''




										if self.delimiter is not None:
													snake_case_				:					Tuple   =       self.delimiter
										if self.column_names is not None:
													snake_case_				:					List[Any]   =       self.column_names






							@property
							def 							_A	(		self			:Optional[Any]				)				->  int:


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       {
										    "sep": self.sep,
										    "header": self.header,
										    "names": self.names,
										    "index_col": self.index_col,
										    "usecols": self.usecols,
										    "prefix": self.prefix,
										    "mangle_dupe_cols": self.mangle_dupe_cols,
										    "engine": self.engine,
										    "converters": self.converters,
										    "true_values": self.true_values,
										    "false_values": self.false_values,
										    "skipinitialspace": self.skipinitialspace,
										    "skiprows": self.skiprows,
										    "nrows": self.nrows,
										    "na_values": self.na_values,
										    "keep_default_na": self.keep_default_na,
										    "na_filter": self.na_filter,
										    "verbose": self.verbose,
										    "skip_blank_lines": self.skip_blank_lines,
										    "thousands": self.thousands,
										    "decimal": self.decimal,
										    "lineterminator": self.lineterminator,
										    "quotechar": self.quotechar,
										    "quoting": self.quoting,
										    "escapechar": self.escapechar,
										    "comment": self.comment,
										    "encoding": self.encoding,
										    "dialect": self.dialect,
										    "error_bad_lines": self.error_bad_lines,
										    "warn_bad_lines": self.warn_bad_lines,
										    "skipfooter": self.skipfooter,
										    "doublequote": self.doublequote,
										    "memory_map": self.memory_map,
										    "float_precision": self.float_precision,
										    "chunksize": self.chunksize,
										    "encoding_errors": self.encoding_errors,
										    "on_bad_lines": self.on_bad_lines,
										    "date_format": self.date_format,
										}

										# some kwargs must not be passed if they don't have a default value
										# some others are deprecated and we can also not pass them if they are the default value
										for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
													if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()       ,							lowerCAmelCase__				):
																del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
										if not (datasets.config.PANDAS_VERSION.major >= 2):
													for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
																del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
										if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
													for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
																del pd_read_csv_kwargs[pd_read_csv_parameter]

										return pd_read_csv_kwargs







class    A_	(datasets.ArrowBasedBuilder							):
							"""simple docstring"""




							a__   		=	CsvConfig

							def 							_A	(		self			:Optional[Any]				)				->  Optional[Any]:


										'''simple docstring'''




										return datasets.DatasetInfo(features=self.config.features				)

							def 							_A	(		self			:Tuple       ,							lowerCAmelCase__			:Dict				)				->  List[Any]:


										'''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}'''				)
										snake_case_				:					Optional[Any]   =       dl_manager.download_and_extract(self.config.data_files				)
										if isinstance(lowerCAmelCase__       ,							(str, list, tuple)				):
													snake_case_				:					int   =       data_files
													if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				):
																snake_case_				:					List[str]   =       [files]
													snake_case_				:					Tuple   =       [dl_manager.iter_files(lowerCAmelCase__				) for file in files]
													return [datasets.SplitGenerator(name=datasets.Split.TRAIN       ,							gen_kwargs={"files": files}				)]
										snake_case_				:					str   =       []
										for split_name, files in data_files.items():
													if isinstance(lowerCAmelCase__       ,							lowerCAmelCase__				):
																snake_case_				:					str   =       [files]
													snake_case_				:					Any   =       [dl_manager.iter_files(lowerCAmelCase__				) for file in files]
													splits.append(datasets.SplitGenerator(name=lowerCAmelCase__       ,							gen_kwargs={"files": files}				)				)
										return splits

							def 							_A	(		self			:List[Any]       ,							lowerCAmelCase__			:pa.Table				)				->  pa.Table:


										'''simple docstring'''




										if self.config.features is not None:
													snake_case_				:					int   =       self.config.features.arrow_schema
													if all(not require_storage_cast(lowerCAmelCase__				) for feature in self.config.features.values()				):
																# cheaper cast
																snake_case_				:					Optional[Any]   =       pa.Table.from_arrays([pa_table[field.name] for field in schema]       ,							schema=lowerCAmelCase__				)
													else:
																# more expensive cast; allows str <-> int/float or str to Audio for example
																snake_case_				:					Dict   =       table_cast(lowerCAmelCase__       ,							lowerCAmelCase__				)
										return pa_table






							def 							_A	(		self			:Dict       ,							lowerCAmelCase__			:Union[str, Any]				)				->  Optional[int]:


										'''simple docstring'''




										snake_case_				:					Tuple   =       self.config.features.arrow_schema if self.config.features else None
										# dtype allows reading an int column as str
										snake_case_				:					str   =       (
										    {
										        name: dtype.to_pandas_dtype() if not require_storage_cast(lowerCAmelCase__				) else object
										        for name, dtype, feature in zip(schema.names       ,							schema.types       ,							self.config.features.values()				)
										    }
										    if schema is not None
										    else None
										)
										for file_idx, file in enumerate(itertools.chain.from_iterable(lowerCAmelCase__				)				):
													snake_case_				:					Tuple   =       pd.read_csv(lowerCAmelCase__       ,							iterator=lowerCAmelCase__       ,							dtype=lowerCAmelCase__       ,							**self.config.pd_read_csv_kwargs				)
													try:
																for batch_idx, df in enumerate(lowerCAmelCase__				):
																			snake_case_				:					Optional[int]   =       pa.Table.from_pandas(lowerCAmelCase__				)
																			# 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(lowerCAmelCase__				)
													except ValueError as e:
																logger.error(F'''Failed to read file \'{file}\' with error {type(lowerCAmelCase__				)}: {e}'''				)
																raise




