



"""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


__A      :							List[Any]   =      datasets.utils.logging.get_logger(__name__)

__A      :							List[str]   =      ["names", "prefix"]
__A      :							Union[str, Any]   =      ["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
__A      :							int   =      ["encoding_errors", "on_bad_lines"]
__A      :							List[Any]   =      ["date_format"]
@dataclass
class 	_a       (    datasets.BuilderConfig):
			"""simple docstring"""
			UpperCamelCase__						=		","
			UpperCamelCase__						=		None
			UpperCamelCase__						=		"infer"
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		True
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		False
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		True
			UpperCamelCase__						=		True
			UpperCamelCase__						=		False
			UpperCamelCase__						=		True
			UpperCamelCase__						=		None
			UpperCamelCase__						=		"."
			UpperCamelCase__						=		None
			UpperCamelCase__						=		'"'
			UpperCamelCase__						=		0
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		None
			UpperCamelCase__						=		True
			UpperCamelCase__						=		True
			UpperCamelCase__						=		0
			UpperCamelCase__						=		True
			UpperCamelCase__						=		False
			UpperCamelCase__						=		None
			UpperCamelCase__						=		10_000
			UpperCamelCase__						=		None
			UpperCamelCase__						=		"strict"
			UpperCamelCase__						=		"error"
			UpperCamelCase__						=		None



			def        lowercase__  (						self   :			Optional[int]      )->Dict:


							if self.delimiter is not None:
											_UpperCAmelCase							=			self.delimiter
							if self.column_names is not None:
											_UpperCAmelCase							=			self.column_names



			@property
			def        lowercase__  (						self   :			Dict      )->Union[str, Any]:
							_UpperCAmelCase							=			{
							    '''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"""
			UpperCamelCase__						=		CsvConfig



			def        lowercase__  (						self   :			str      )->Optional[Any]:
							return datasets.DatasetInfo(features=self.config.features      )



			def        lowercase__  (						self   :			int ,      __UpperCamelCase   :			Optional[Any]      )->Optional[Any]:


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



			def        lowercase__  (						self   :			Tuple ,      __UpperCamelCase   :			pa.Table      )->pa.Table:


							if self.config.features is not None:
											_UpperCAmelCase							=			self.config.features.arrow_schema
											if all(not require_storage_cast(lowerCamelCase__      ) for feature in self.config.features.values()      ):
															# cheaper cast
															_UpperCAmelCase							=			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
															_UpperCAmelCase							=			table_cast(lowerCamelCase__ ,      lowerCamelCase__      )
							return pa_table



			def        lowercase__  (						self   :			Any ,      __UpperCamelCase   :			List[Any]      )->Dict:
							_UpperCAmelCase							=			self.config.features.arrow_schema if self.config.features else None
							# dtype allows reading an int column as str
							_UpperCAmelCase							=			(
							    {
							        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__      )      ):
											_UpperCAmelCase							=			pd.read_csv(lowerCamelCase__ ,      iterator=lowerCamelCase__ ,      dtype=lowerCamelCase__ ,      **self.config.pd_read_csv_kwargs      )
											try:
															for batch_idx, df in enumerate(lowerCamelCase__      ):
																			_UpperCAmelCase							=			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










import math
import unittest



def    __lowercase   (      _SCREAMING_SNAKE_CASE	) ->   bool:


      '''simple docstring'''


      assert isinstance(_SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	) and (
          number >= 0
      ), "'number' must been an int and positive"

      if 1 < number < 4:
            # 2 and 3 are primes
            return True
      elif number < 2 or number % 2 == 0 or number % 3 == 0:
            # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
            return False

      # All primes number are in format of 6k +/- 1
      for i in range(5 ,						int(math.sqrt(_SCREAMING_SNAKE_CASE	) + 1	) ,						6	):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True

class 		UpperCamelCase__ (      unittest.TestCase   ):



     '''simple docstring'''

     def 				SCREAMING_SNAKE_CASE__  (							self						:    Dict       )     ->		Tuple:




           '''simple docstring'''


           self.assertTrue(is_prime(2       )       )
           self.assertTrue(is_prime(3       )       )
           self.assertTrue(is_prime(5       )       )
           self.assertTrue(is_prime(7       )       )
           self.assertTrue(is_prime(11       )       )
           self.assertTrue(is_prime(13       )       )
           self.assertTrue(is_prime(17       )       )
           self.assertTrue(is_prime(19       )       )
           self.assertTrue(is_prime(23       )       )
           self.assertTrue(is_prime(29       )       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Optional[int]       )     ->		Tuple:




           '''simple docstring'''


           with self.assertRaises(lowerCamelCase__       ):
                 is_prime(-19       )
           self.assertFalse(
               is_prime(0       )						,"""Zero doesn't have any positive factors, primes must have exactly two."""						,)
           self.assertFalse(
               is_prime(1       )						,"""One only has 1 positive factor, primes must have exactly two."""						,)
           self.assertFalse(is_prime(2 * 2       )       )
           self.assertFalse(is_prime(2 * 3       )       )
           self.assertFalse(is_prime(3 * 3       )       )
           self.assertFalse(is_prime(3 * 5       )       )
           self.assertFalse(is_prime(3 * 5 * 7       )       )


if __name__ == "__main__":
      unittest.main()


