





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

a		:				Union[str, Any]  			=    ['''names''', '''prefix''']
a		:				Any  			=    ['''warn_bad_lines''', '''error_bad_lines''', '''mangle_dupe_cols''']
a		:				Any  			=    ['''encoding_errors''', '''on_bad_lines''']
a		:				List[str]  			=    ['''date_format''']


@dataclass
class  __UpperCamelCase       (		datasets.BuilderConfig		):
							lowerCamelCase     :      str         =","
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      Optional[Union[int, List[int], str]]         ="infer"
							lowerCamelCase     :      Optional[List[str]]         =None
							lowerCamelCase     :      Optional[List[str]]         =None
							lowerCamelCase     :      Optional[Union[int, str, List[int], List[str]]]         =None
							lowerCamelCase     :      Optional[Union[List[int], List[str]]]         =None
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      Optional[Literal["c", "python", "pyarrow"]]         =None
							lowerCamelCase     :      Dict[Union[int, str], Callable[[Any], Any]]         =None
							lowerCamelCase     :      Optional[list]         =None
							lowerCamelCase     :      Optional[list]         =None
							lowerCamelCase     :      bool         =False
							lowerCamelCase     :      Optional[Union[int, List[int]]]         =None
							lowerCamelCase     :      Optional[int]         =None
							lowerCamelCase     :      Optional[Union[str, List[str]]]         =None
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      bool         =False
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      str         ="."
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      str         ='"'
							lowerCamelCase     :      int         =0
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      int         =0
							lowerCamelCase     :      bool         =True
							lowerCamelCase     :      bool         =False
							lowerCamelCase     :      Optional[str]         =None
							lowerCamelCase     :      int         =1_0000
							lowerCamelCase     :      Optional[datasets.Features]         =None
							lowerCamelCase     :      Optional[str]         ="strict"
							lowerCamelCase     :      Literal["error", "warn", "skip"]         ="error"
							lowerCamelCase     :      Optional[str]         =None






							def 					__a     (     self   )			->				Dict:
								if self.delimiter is not None:
									a   :	int			=       self.delimiter
								if self.column_names is not None:
									a   :	Any			=       self.column_names






							@property
							def 					__a     (     self   )			->				List[str]:
								a   :	Dict			=       {
								    "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  __UpperCamelCase       (		datasets.ArrowBasedBuilder		):
							lowerCamelCase     :      Union[str, Any]         =CsvConfig






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






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






							def 					__a     (     self   ,      lowerCAmelCase__   )			->				pa.Table:
								if self.config.features is not None:
									a   :	Optional[Any]			=       self.config.features.arrow_schema
									if all(not require_storage_cast(lowerCAmelCase__   ) for feature in self.config.features.values()   ):
										# cheaper cast
										a   :	Dict			=       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
										a   :	Union[str, Any]			=       table_cast(lowerCAmelCase__   ,      lowerCAmelCase__   )
								return pa_table






							def 					__a     (     self   ,      lowerCAmelCase__   )			->				Any:
								a   :	Tuple			=       self.config.features.arrow_schema if self.config.features else None
								# dtype allows reading an int column as str
								a   :	Any			=       (
								    {
								        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__   )   ):
									a   :	Tuple			=       pd.read_csv(lowerCAmelCase__   ,      iterator=lowerCAmelCase__   ,      dtype=lowerCAmelCase__   ,      **self.config.pd_read_csv_kwargs   )
									try:
										for batch_idx, df in enumerate(lowerCAmelCase__   ):
											a   :	Any			=       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









"""simple docstring"""




a		:				str  			=    8.314_4598






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					float					, _lowercase		:					float      )				->float:






	'''simple docstring'''






	if temperature < 0:
		raise Exception("Temperature cannot be less than 0 K"      )
	if molar_mass <= 0:
		raise Exception("Molar mass cannot be less than or equal to 0 kg/mol"      )
	else:
		return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
		import doctest

		# run doctest
		doctest.testmod()

		# example
		a		:				Any  			=    300
		a		:				Dict  			=    28
		a		:				Dict  			=    rms_speed_of_molecule(temperature, molar_mass)
		print(F'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')


