
'''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


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

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




@dataclass
class   UpperCAmelCase_					(		datasets.BuilderConfig			):






						'''simple docstring'''






						_lowercase		:				str									=       ","
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				Optional[Union[int, List[int], str]]									=       "infer"
						_lowercase		:				Optional[List[str]]									=       None
						_lowercase		:				Optional[List[str]]									=       None
						_lowercase		:				Optional[Union[int, str, List[int], List[str]]]									=       None
						_lowercase		:				Optional[Union[List[int], List[str]]]									=       None
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				bool									=       True
						_lowercase		:				Optional[Literal["c", "python", "pyarrow"]]									=       None
						_lowercase		:				Dict[Union[int, str], Callable[[Any], Any]]									=       None
						_lowercase		:				Optional[list]									=       None
						_lowercase		:				Optional[list]									=       None
						_lowercase		:				bool									=       False
						_lowercase		:				Optional[Union[int, List[int]]]									=       None
						_lowercase		:				Optional[int]									=       None
						_lowercase		:				Optional[Union[str, List[str]]]									=       None
						_lowercase		:				bool									=       True
						_lowercase		:				bool									=       True
						_lowercase		:				bool									=       False
						_lowercase		:				bool									=       True
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				str									=       "."
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				str									=       '"'
						_lowercase		:				int									=       0
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				bool									=       True
						_lowercase		:				bool									=       True
						_lowercase		:				int									=       0
						_lowercase		:				bool									=       True
						_lowercase		:				bool									=       False
						_lowercase		:				Optional[str]									=       None
						_lowercase		:				int									=       1_0_0_0_0
						_lowercase		:				Optional[datasets.Features]									=       None
						_lowercase		:				Optional[str]									=       "strict"
						_lowercase		:				Literal["error", "warn", "skip"]									=       "error"
						_lowercase		:				Optional[str]									=       None




						def  _lowercase     ( self				):

												"""simple docstring"""



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




						@property
						def  _lowercase     ( self				):

												"""simple docstring"""



												_lowerCAmelCase  						=			{
												    """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()   ,       _lowercase				):
																								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			):






						'''simple docstring'''






						_lowercase		:				Tuple									=       CsvConfig




						def  _lowercase     ( self				):

												"""simple docstring"""



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




						def  _lowercase     ( self   ,       _lowercase				):

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




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



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




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			self.config.features.arrow_schema if self.config.features else None
												# dtype allows reading an int column as str
												_lowerCAmelCase  						=			(
												    {
												        name: dtype.to_pandas_dtype() if not require_storage_cast(_lowercase				) 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(_lowercase				)				):
																		_lowerCAmelCase  						=			pd.read_csv(_lowercase   ,       iterator=_lowercase   ,       dtype=_lowercase   ,       **self.config.pd_read_csv_kwargs				)
																		try:
																								for batch_idx, df in enumerate(_lowercase				):
																														_lowerCAmelCase  						=			pa.Table.from_pandas(_lowercase				)
																														# 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(_lowercase				)
																		except ValueError as e:
																								logger.error(F'Failed to read file \'{file}\' with error {type(_lowercase				)}: {e}'				)
																								raise


'''simple docstring'''



# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

_lowercase    =		"""2.13.1"""

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("""3.7"""):
						raise ImportWarning(
						    """To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."""
						)

if version.parse(pyarrow.__version__).major < 8:
						raise ImportWarning(
						    """To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"""
						    """If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."""
						)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

_lowercase    =		concatenate_datasets
_lowercase    =		DownloadConfig
_lowercase    =		DownloadManager
_lowercase    =		DownloadMode
_lowercase    =		DownloadConfig
_lowercase    =		DownloadMode
_lowercase    =		DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager
