






import sys
from dataclasses import dataclass
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, 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


if TYPE_CHECKING:
		import sqlitea

		import sqlalchemy


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





@dataclass
class __lowerCamelCase				(   datasets.BuilderConfig):





	"""simple docstring"""






	UpperCamelCase__			=   None
	UpperCamelCase__			=   None
	UpperCamelCase__			=   None
	UpperCamelCase__			=   True
	UpperCamelCase__			=   None
	UpperCamelCase__			=   None
	UpperCamelCase__			=   None
	UpperCamelCase__			=   1_0000
	UpperCamelCase__			=   None

	def  UpperCamelCase					(							self					):
							"""simple docstring"""







							if self.sql is None:
													raise ValueError('sql must be specified'					)
							if self.con is None:
													raise ValueError('con must be specified'					)

	def  UpperCamelCase					(							self ,					UpperCAmelCase ,					UpperCAmelCase = None ,					):
							"""simple docstring"""







							_UpperCAmelCase             =    config_kwargs.copy()
							# We need to stringify the Selectable object to make its hash deterministic

							# The process of stringifying is explained here: http://docs.sqlalchemy.org/en/latest/faq/sqlexpressions.html
							_UpperCAmelCase             =    config_kwargs['sql']
							if not isinstance(UpperCAmelCase ,					UpperCAmelCase					):
													if datasets.config.SQLALCHEMY_AVAILABLE and "sqlalchemy" in sys.modules:
																			import sqlalchemy

																			if isinstance(UpperCAmelCase ,					sqlalchemy.sql.Selectable					):
																									_UpperCAmelCase             =    sqlalchemy.create_engine(config_kwargs['con'].split('://'					)[0] + '://'					)
																									_UpperCAmelCase             =    str(sql.compile(dialect=engine.dialect					)					)
																									_UpperCAmelCase             =    sql_str
																			else:
																									raise TypeError(
																									    F"""Supported types for 'sql' are string and sqlalchemy.sql.Selectable but got {type(UpperCAmelCase					)}: {sql}"""					)
													else:
																			raise TypeError(
																			    F"""Supported types for 'sql' are string and sqlalchemy.sql.Selectable but got {type(UpperCAmelCase					)}: {sql}"""					)
							_UpperCAmelCase             =    config_kwargs['con']
							if not isinstance(UpperCAmelCase ,					UpperCAmelCase					):
													_UpperCAmelCase             =    id(UpperCAmelCase					)
													logger.info(
													    F"""SQL connection 'con' of type {type(UpperCAmelCase					)} couldn't be hashed properly. To enable hashing, specify 'con' as URI string instead."""					)

							return super().create_config_id(UpperCAmelCase ,					custom_features=UpperCAmelCase					)

	@property
	def  UpperCamelCase					(							self					):
							"""simple docstring"""







							_UpperCAmelCase             =    {
							    'index_col': self.index_col,
							    'columns': self.columns,
							    'params': self.params,
							    'coerce_float': self.coerce_float,
							    'parse_dates': self.parse_dates,
							}
							return pd_read_sql_kwargs





class __lowerCamelCase				(   datasets.ArrowBasedBuilder):





	"""simple docstring"""






	UpperCamelCase__			=   SqlConfig

	def  UpperCamelCase					(							self					):
							"""simple docstring"""







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

	def  UpperCamelCase					(							self ,					UpperCAmelCase					):
							"""simple docstring"""







							return [datasets.SplitGenerator(name=datasets.Split.TRAIN ,					gen_kwargs={}					)]

	def  UpperCamelCase					(							self ,					UpperCAmelCase					):
							"""simple docstring"""







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

	def  UpperCamelCase					(							self					):
							"""simple docstring"""







							_UpperCAmelCase             =    self.config.chunksize
							_UpperCAmelCase             =    pd.read_sql(
							    self.config.sql ,					self.config.con ,					chunksize=UpperCAmelCase ,					**self.config.pd_read_sql_kwargs					)
							_UpperCAmelCase             =    [sql_reader] if chunksize is None else sql_reader
							for chunk_idx, df in enumerate(UpperCAmelCase					):
													_UpperCAmelCase             =    pa.Table.from_pandas(UpperCAmelCase					)
													yield chunk_idx, self._cast_table(UpperCAmelCase					)








import dataclasses
import enum
import functools
import math
import re

# The following script is adapted from the script of TaPas.
# Original: https://github.com/google-research/tapas/master/wikisql_utils.py
from typing import Any, List, Text


_a   			=						'''none'''
_a   			=						'''none'''


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase			)->						Any:





						"""simple docstring"""



						_UpperCAmelCase             =    value.split(__lowerCAmelCase			)
						return len(__lowerCAmelCase			) > 1 and any((len(__lowerCAmelCase			) == 3 for x in split)			)


def __A					(   __lowerCAmelCase			)->						List[str]:





						"""simple docstring"""



						if isinstance(__lowerCAmelCase				,	__lowerCAmelCase			):
												return value
						if isinstance(__lowerCAmelCase				,	__lowerCAmelCase			):
												return float(__lowerCAmelCase			)
						if not isinstance(__lowerCAmelCase				,	__lowerCAmelCase			):
												raise ValueError('Argument value is not a string. Can\'t parse it as float'			)
						_UpperCAmelCase             =    value

						try:
												# Example: 1,000.7
												if "." in sanitized and "," in sanitized:
																		return float(sanitized.replace(','				,	''			)			)
												# 1,000
												if "," in sanitized and _split_thousands(','				,	__lowerCAmelCase			):
																		return float(sanitized.replace(','				,	''			)			)
												# 5,5556
												if "," in sanitized and sanitized.count(','			) == 1 and not _split_thousands(','				,	__lowerCAmelCase			):
																		return float(sanitized.replace(','				,	'.'			)			)
												# 0.0.0.1
												if sanitized.count('.'			) > 1:
																		return float(sanitized.replace('.'				,	''			)			)
												# 0,0,0,1
												if sanitized.count(','			) > 1:
																		return float(sanitized.replace(','				,	''			)			)
												return float(__lowerCAmelCase			)
						except ValueError:
												# Avoid adding the sanitized value in the error message.
												raise ValueError('Unable to convert value to float'			)


def __A					(   __lowerCAmelCase			)->						Any:





						"""simple docstring"""



						if answer is None:
												return None
						try:
												_UpperCAmelCase             =    convert_to_float(__lowerCAmelCase			)
												if isinstance(__lowerCAmelCase				,	__lowerCAmelCase			) and math.isnan(__lowerCAmelCase			):
																		return None
												return value
						except ValueError:
												return answer.lower()


_a   			=						{
    '''text''': lambda x: x,
    '''real''': convert_to_float,
}





class __lowerCamelCase				(   enum.Enum):





	"""simple docstring"""






	UpperCamelCase__			=   0
	UpperCamelCase__			=   1
	UpperCamelCase__			=   2
	UpperCamelCase__			=   3
	UpperCamelCase__			=   4
	UpperCamelCase__			=   5





class __lowerCamelCase				(   enum.Enum):





	"""simple docstring"""






	UpperCamelCase__			=   0
	UpperCamelCase__			=   1
	UpperCamelCase__			=   2





@dataclasses.dataclass
class __lowerCamelCase				:





	"""simple docstring"""






	UpperCamelCase__			=   42
	UpperCamelCase__			=   42
	UpperCamelCase__			=   42



_a   			=						re.compile(r'''\w+|[^\w\s]+''', re.UNICODE | re.MULTILINE | re.DOTALL)


def __A					(   __lowerCAmelCase			)->						Optional[Any]:





						"""simple docstring"""



						return list(_TOKENIZER.findall(x.lower()			)			)


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)->						Any:





						"""simple docstring"""



						if operator == _Operator.EQUALS:
												return src == tgt
						elif operator == _Operator.GREATER:
												return src > tgt
						elif operator == _Operator.LESSER:
												return src < tgt
						raise ValueError(F"""Unknown operator: {operator}"""			)


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)->						str:





						"""simple docstring"""



						_UpperCAmelCase             =    table['types']
						return _TYPE_CONVERTER[types[column]](__lowerCAmelCase			)


def __A					(   __lowerCAmelCase			)->						str:





						"""simple docstring"""



						return isinstance(__lowerCAmelCase				,	__lowerCAmelCase			)


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)->						str:





						"""simple docstring"""



						for cond in conditions:
												_UpperCAmelCase             =    row[cond.column]

												_UpperCAmelCase             =    _parse_value(__lowerCAmelCase				,	cond.column				,	cond.cmp_value			)

												if _is_string(__lowerCAmelCase			) and _is_string(__lowerCAmelCase			):
																		_UpperCAmelCase             =    _normalize_for_match(__lowerCAmelCase			)
																		_UpperCAmelCase             =    _normalize_for_match(__lowerCAmelCase			)

												if not isinstance(__lowerCAmelCase				,	type(__lowerCAmelCase			)			):
																		raise ValueError('Type difference {} != {}'.format(type(__lowerCAmelCase			)				,	type(__lowerCAmelCase			)			)			)

												if not _compare(cond.operator				,	__lowerCAmelCase				,	__lowerCAmelCase			):
																		return False
						return True


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)->						str:





						"""simple docstring"""



						if not answer_coordinates:
												if aggregation_op == _Aggregation.COUNT:
																		return 0.0
												else:
																		return EMPTY_ANSWER_AGG

    # Count can support non numeric answers.
						if aggregation_op == _Aggregation.COUNT:
												return float(len(__lowerCAmelCase			)			)

						# If we have just one answer, if float returns it or try a conversion.
						_UpperCAmelCase             =    [table['rows'][i][j] for (i, j) in answer_coordinates]
						if len(__lowerCAmelCase			) == 1:
												try:
																		return convert_to_float(values[0]			)
												except ValueError as e:
																		if aggregation_op != _Aggregation.NONE:
																								raise e

						if aggregation_op == _Aggregation.NONE:
												return None

						# Other aggregation only support numeric values. Bail out if we have strings.
						if not all((isinstance(__lowerCAmelCase				,	(int, float)			) for v in values)			):
												return None

						if aggregation_op == _Aggregation.SUM:
												return float(sum(__lowerCAmelCase			)			)
						elif aggregation_op == _Aggregation.AVERAGE:
												return sum(__lowerCAmelCase			) / len(__lowerCAmelCase			)
						else:
												raise ValueError(F"""Unknown aggregation: {aggregation_op}"""			)


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase			)->						Any:





						"""simple docstring"""



						_UpperCAmelCase             =    sql_query['agg']
						if aggregation_op_index >= 3:
												_UpperCAmelCase             =    _Aggregation(__lowerCAmelCase			)
						else:
												_UpperCAmelCase             =    _Aggregation.NONE

						_UpperCAmelCase             =    sql_query['sel']
						_UpperCAmelCase             =    [
						    _Condition(__lowerCAmelCase				,	_Operator(__lowerCAmelCase			)				,	__lowerCAmelCase			)
						    for column, operator, cmp_value in zip(
						        sql_query['conds']['column_index']				,	sql_query['conds']['operator_index']				,	sql_query['conds']['condition']			)
						]

						_UpperCAmelCase             =    []
						for row in range(len(table['rows']			)			):
												if _respect_conditions(__lowerCAmelCase				,	table['rows'][row]				,	__lowerCAmelCase			):
																		indices.append((row, target_column)			)

						if not indices:
												return [], aggregation_op

						if len(__lowerCAmelCase			) == 1:
												return indices, aggregation_op

						# Parsing of MIN/MAX.
						if aggregation_op_index in (1, 2):
												_UpperCAmelCase             =    {2: min, 1: max}
												_UpperCAmelCase             =    [(table['rows'][i][j], index) for index, (i, j) in enumerate(__lowerCAmelCase			)]
												_UpperCAmelCase             =    functools.reduce(operators[sql_query['agg']]				,	__lowerCAmelCase			)

												_UpperCAmelCase             =    [indices[reduced[1]]]
												return ret, _Aggregation.NONE

						return indices, aggregation_op


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)->						Dict:





						"""simple docstring"""



						if float_answer is not None:
												return [str(__lowerCAmelCase			)]
						return [str(table['real_rows'][r][c]			) for r, c in answer_coordinates]


def __A					(   __lowerCAmelCase				,	__lowerCAmelCase			)->						List:





						"""simple docstring"""



						_UpperCAmelCase      ,				_UpperCAmelCase             =    _get_answer_coordinates(__lowerCAmelCase				,	__lowerCAmelCase			)
						_UpperCAmelCase             =    _get_float_answer(__lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)
						_UpperCAmelCase             =    _get_answer_text(__lowerCAmelCase				,	__lowerCAmelCase				,	__lowerCAmelCase			)
						# keep the original data the same with TaPas
						if len(__lowerCAmelCase			) == 0:
												_UpperCAmelCase             =    [EMPTY_ANSWER]
						return answer_text
