






"""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


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

_UpperCamelCase					      =  ["""names""", """prefix"""]
_UpperCamelCase					      =  ["""warn_bad_lines""", """error_bad_lines""", """mangle_dupe_cols"""]
_UpperCamelCase					      =  ["""encoding_errors""", """on_bad_lines"""]
_UpperCamelCase					      =  ["""date_format"""]







@dataclass
class  lowerCamelCase__ (	datasets.BuilderConfig			):
    SCREAMING_SNAKE_CASE		=      ","
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      "infer"
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      False
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      False
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      "."
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      '"'
    SCREAMING_SNAKE_CASE		=      0
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      0
    SCREAMING_SNAKE_CASE		=      True
    SCREAMING_SNAKE_CASE		=      False
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      10_000
    SCREAMING_SNAKE_CASE		=      None
    SCREAMING_SNAKE_CASE		=      "strict"
    SCREAMING_SNAKE_CASE		=      "error"
    SCREAMING_SNAKE_CASE		=      None






    def     _UpperCamelCase							(			self ):
          if self.delimiter is not None:
                UpperCAmelCase          =	self.delimiter
          if self.column_names is not None:
                UpperCAmelCase          =	self.column_names






    @property
    def     _UpperCamelCase							(			self ):
          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()     ,A ):
                      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  lowerCamelCase__ (	datasets.ArrowBasedBuilder			):
    SCREAMING_SNAKE_CASE		=      CsvConfig






    def     _UpperCamelCase							(			self ):
          return datasets.DatasetInfo(features=self.config.features )






    def     _UpperCamelCase							(			self     ,A ):
          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(A     ,(str, list, tuple) ):
                UpperCAmelCase          =	data_files
                if isinstance(A     ,A ):
                      UpperCAmelCase          =	[files]
                UpperCAmelCase          =	[dl_manager.iter_files(A ) 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(A     ,A ):
                      UpperCAmelCase          =	[files]
                UpperCAmelCase          =	[dl_manager.iter_files(A ) for file in files]
                splits.append(datasets.SplitGenerator(name=A     ,gen_kwargs={"""files""": files} ) )
          return splits






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






    def     _UpperCamelCase							(			self     ,A ):
          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(A ) 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(A ) ):
                UpperCAmelCase          =	pd.read_csv(A     ,iterator=A     ,dtype=A     ,**self.config.pd_read_csv_kwargs )
                try:
                      for batch_idx, df in enumerate(A ):
                            UpperCAmelCase          =	pa.Table.from_pandas(A )
                            # 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(A )
                except ValueError as e:
                      logger.error(F'''Failed to read file \'{file}\' with error {type(A )}: {e}''' )
                      raise











"""simple docstring"""







_UpperCamelCase					      =  [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_UpperCamelCase					      =  [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_UpperCamelCase					      =  {
    0: """Sunday""",
    1: """Monday""",
    2: """Tuesday""",
    3: """Wednesday""",
    4: """Thursday""",
    5: """Friday""",
    6: """Saturday""",
}

def _a			(		_snake_case				,	_snake_case				,	_snake_case							):







      """simple docstring"""






      assert len(str(_snake_case							)							) > 2, "year should be in YYYY format"
      assert 1 <= month <= 12, "month should be between 1 to 12"
      assert 1 <= day <= 31, "day should be between 1 to 31"

      # Doomsday algorithm:
      UpperCAmelCase          =	year // 100
      UpperCAmelCase          =	(5 * (century % 4) + 2) % 7
      UpperCAmelCase          =	year % 100
      UpperCAmelCase          =	centurian % 12
      UpperCAmelCase          =	(
          (centurian // 12) + centurian_m + (centurian_m // 4) + century_anchor
      ) % 7
      UpperCAmelCase          =	(
          DOOMSDAY_NOT_LEAP[month - 1]
          if (year % 4 != 0) or (centurian == 0 and (year % 400) == 0)
          else DOOMSDAY_LEAP[month - 1]
      )
      UpperCAmelCase          =	(dooms_day + day - day_anchor) % 7
      return WEEK_DAY_NAMES[week_day]


if __name__ == "__main__":
  import doctest

  doctest.testmod()



