






def 	__UpperCAmelCase       ( __magic_name__ = 100_0000						)->    int:



			"""simple docstring"""



			snake_case_				:					Any   =       set(range(3     ,__magic_name__     ,2						)						)
			primes.add(2						)
			for p in range(3     ,__magic_name__     ,2						):
						if p not in primes:
									continue
						primes.difference_update(set(range(p * p     ,__magic_name__     ,__magic_name__						)						)						)

			snake_case_				:					Optional[Any]   =       [float(__magic_name__						) for n in range(limit + 1						)]

			for p in primes:
						for n in range(__magic_name__     ,limit + 1     ,__magic_name__						):
									phi[n] *= 1 - 1 / p

			return int(sum(phi[2:]						)						)


if __name__ == "__main__":
		print(f'''{solution() = }''')












'''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




