
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


lowerCamelCase__				:     int			       =							"""none"""
lowerCamelCase__				:     Any			       =							"""none"""

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Dict    ,    __UpperCAmelCase		:			str							)      ->				Optional[int]:
      SCREAMING_SNAKE_CASE_					=    value.split(__UpperCAmelCase							)
      return len(__UpperCAmelCase							) > 1 and any((len(__UpperCAmelCase							) == 3 for x in split)							)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			int							)      ->				Optional[int]:
      if isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							):
            return value
      if isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							):
            return float(__UpperCAmelCase							)
      if not isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							):
            raise ValueError('Argument value is not a string. Can\'t parse it as float'							)
      SCREAMING_SNAKE_CASE_					=    value

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

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Optional[Any]							)      ->				Optional[Any]:
      if answer is None:
            return None
      try:
            SCREAMING_SNAKE_CASE_					=    convert_to_float(__UpperCAmelCase							)
            if isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							) and math.isnan(__UpperCAmelCase							):
                  return None
            return value
      except ValueError:
            return answer.lower()


lowerCamelCase__				:     Dict			       =							{
    """text""": lambda x: x,
    """real""": convert_to_float,
}





class  lowerCamelCase_							(   enum.Enum      ):


 '''simple docstring'''







 lowercase_       					=					0
 lowercase_       					=					1
 lowercase_       					=					2
 lowercase_       					=					3
 lowercase_       					=					4
 lowercase_       					=					5





class  lowerCamelCase_							(   enum.Enum      ):


 '''simple docstring'''







 lowercase_       					=					0
 lowercase_       					=					1
 lowercase_       					=					2





@dataclasses.dataclass
class  lowerCamelCase_							:


 '''simple docstring'''







 lowercase_       					=					42
 lowercase_       					=					42
 lowercase_       					=					42


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

def       UpperCAmelCase_							(   __UpperCAmelCase		:			List[str]							)      ->				Optional[int]:
      return list(_TOKENIZER.findall(x.lower()							)							)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Optional[int]    ,    __UpperCAmelCase		:			List[Any]    ,    __UpperCAmelCase		:			Tuple							)      ->				int:
      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       UpperCAmelCase_							(   __UpperCAmelCase		:			Dict    ,    __UpperCAmelCase		:			Optional[Any]    ,    __UpperCAmelCase		:			List[Any]							)      ->				Tuple:
      SCREAMING_SNAKE_CASE_					=    table['types']
      return _TYPE_CONVERTER[types[column]](__UpperCAmelCase							)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Optional[Any]							)      ->				Tuple:
      return isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Optional[Any]    ,    __UpperCAmelCase		:			Dict    ,    __UpperCAmelCase		:			List[str]							)      ->				Tuple:
      for cond in conditions:
            SCREAMING_SNAKE_CASE_					=    row[cond.column]

            SCREAMING_SNAKE_CASE_					=    _parse_value(__UpperCAmelCase    ,    cond.column    ,    cond.cmp_value							)

            if _is_string(__UpperCAmelCase							) and _is_string(__UpperCAmelCase							):
                  SCREAMING_SNAKE_CASE_					=    _normalize_for_match(__UpperCAmelCase							)
                  SCREAMING_SNAKE_CASE_					=    _normalize_for_match(__UpperCAmelCase							)

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

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

def       UpperCAmelCase_							(   __UpperCAmelCase		:			List[str]    ,    __UpperCAmelCase		:			Dict    ,    __UpperCAmelCase		:			List[str]							)      ->				Any:
      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(__UpperCAmelCase							)							)

      # If we have just one answer, if float returns it or try a conversion.
      SCREAMING_SNAKE_CASE_					=    [table['rows'][i][j] for (i, j) in answer_coordinates]
      if len(__UpperCAmelCase							) == 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(__UpperCAmelCase    ,    (int, float)							) for v in values)							):
            return None

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

def       UpperCAmelCase_							(   __UpperCAmelCase		:			List[Any]    ,    __UpperCAmelCase		:			Union[str, Any]							)      ->				Any:
      SCREAMING_SNAKE_CASE_					=    sql_query['agg']
      if aggregation_op_index >= 3:
            SCREAMING_SNAKE_CASE_					=    _Aggregation(__UpperCAmelCase							)
      else:
            SCREAMING_SNAKE_CASE_					=    _Aggregation.NONE

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

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

      if not indices:
            return [], aggregation_op

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

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

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

      return indices, aggregation_op

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Optional[Any]    ,    __UpperCAmelCase		:			List[Any]    ,    __UpperCAmelCase		:			str							)      ->				Tuple:
      if float_answer is not None:
            return [str(__UpperCAmelCase							)]
      return [str(table['real_rows'][r][c]							) for r, c in answer_coordinates]





def       UpperCAmelCase_							(   __UpperCAmelCase		:			int    ,    __UpperCAmelCase		:			List[str]							)      ->				List[Any]:
      SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					=    _get_answer_coordinates(__UpperCAmelCase    ,    __UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_					=    _get_float_answer(__UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_					=    _get_answer_text(__UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase							)
      # keep the original data the same with TaPas
      if len(__UpperCAmelCase							) == 0:
            SCREAMING_SNAKE_CASE_					=    [EMPTY_ANSWER]
      return answer_text





import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases





class  lowerCamelCase_							(   _SCREAMING_SNAKE_CASE      ):


 '''simple docstring'''







 def    lowerCAmelCase_						(							self						:	List[str]       ,       _lowerCAmelCase						:	Tuple       ,       _lowerCAmelCase						:	Any=False		):
       SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					=    (
           filename_skip_take['filename'],
           filename_skip_take['skip'] if 'skip' in filename_skip_take else None,
           filename_skip_take['take'] if 'take' in filename_skip_take else None,
       )
       open(os.path.join(_lowerCAmelCase		)       ,       'wb'		).close()
       SCREAMING_SNAKE_CASE_					=    pa.Table.from_pydict({'filename': [Path(_lowerCAmelCase		).name] * 100}		)
       if take == -1:
             SCREAMING_SNAKE_CASE_					=    len(_lowerCAmelCase		) - skip
       if skip is not None and take is not None:
             SCREAMING_SNAKE_CASE_					=    pa_table.slice(_lowerCAmelCase       ,       _lowerCAmelCase		)
       return pa_table





class  lowerCamelCase_							(   _SCREAMING_SNAKE_CASE      ):


 '''simple docstring'''







 def    lowerCAmelCase_						(							self						:	str		):
       SCREAMING_SNAKE_CASE_					=    'my_name'
       SCREAMING_SNAKE_CASE_					=    SplitInfo(name='train'       ,       num_examples=100		)
       SCREAMING_SNAKE_CASE_					=    SplitInfo(name='test'       ,       num_examples=100		)
       SCREAMING_SNAKE_CASE_					=    [train_info, test_info]
       SCREAMING_SNAKE_CASE_					=    SplitDict()
       split_dict.add(_lowerCAmelCase		)
       split_dict.add(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    DatasetInfo(splits=_lowerCAmelCase		)

       with tempfile.TemporaryDirectory() as tmp_dir:
             SCREAMING_SNAKE_CASE_					=    ReaderTest(_lowerCAmelCase       ,       _lowerCAmelCase		)

             SCREAMING_SNAKE_CASE_					=    'test[:33%]'
             SCREAMING_SNAKE_CASE_					=    Dataset(**reader.read(_lowerCAmelCase       ,       _lowerCAmelCase       ,       _lowerCAmelCase		)		)
             self.assertEqual(dset['filename'][0]       ,       F"{name}-test"		)
             self.assertEqual(dset.num_rows       ,       33		)
             self.assertEqual(dset.num_columns       ,       1		)

             SCREAMING_SNAKE_CASE_					=    ['train', 'test[:33%]']
             SCREAMING_SNAKE_CASE_					=    [Split.TRAIN, ReadInstruction.from_spec('test[:33%]'		)]
             for instructions in [instructionsa, instructionsa]:
                   SCREAMING_SNAKE_CASE_					=    [reader.read(_lowerCAmelCase       ,       _lowerCAmelCase       ,       _lowerCAmelCase		) for instr in instructions]
                   SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					=    (Dataset(**_lowerCAmelCase		) for dataset_kwargs in datasets_kwargs)
                   self.assertEqual(train_dset['filename'][0]       ,       F"{name}-train"		)
                   self.assertEqual(train_dset.num_rows       ,       100		)
                   self.assertEqual(train_dset.num_columns       ,       1		)
                   self.assertIsInstance(train_dset.split       ,       _lowerCAmelCase		)
                   self.assertEqual(str(train_dset.split		)       ,       'train'		)
                   self.assertEqual(test_dset['filename'][0]       ,       F"{name}-test"		)
                   self.assertEqual(test_dset.num_rows       ,       33		)
                   self.assertEqual(test_dset.num_columns       ,       1		)
                   self.assertIsInstance(test_dset.split       ,       _lowerCAmelCase		)
                   self.assertEqual(str(test_dset.split		)       ,       'test[:33%]'		)
                   del train_dset, test_dset



 def    lowerCAmelCase_						(							self						:	Tuple		):
       SCREAMING_SNAKE_CASE_					=    'my_name'
       SCREAMING_SNAKE_CASE_					=    SplitInfo(name='train'       ,       num_examples=1_000       ,       shard_lengths=[100] * 10		)
       SCREAMING_SNAKE_CASE_					=    [train_info]
       SCREAMING_SNAKE_CASE_					=    SplitDict()
       split_dict.add(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    DatasetInfo(splits=_lowerCAmelCase		)

       with tempfile.TemporaryDirectory() as tmp_dir:
             SCREAMING_SNAKE_CASE_					=    ReaderTest(_lowerCAmelCase       ,       _lowerCAmelCase		)

             SCREAMING_SNAKE_CASE_					=    'train[:33%]'
             SCREAMING_SNAKE_CASE_					=    Dataset(**reader.read(_lowerCAmelCase       ,       _lowerCAmelCase       ,       _lowerCAmelCase		)		)
             self.assertEqual(dset['filename'][0]       ,       F"{name}-train-00000-of-00010"		)
             self.assertEqual(dset['filename'][-1]       ,       F"{name}-train-00003-of-00010"		)
             self.assertEqual(dset.num_rows       ,       330		)
             self.assertEqual(dset.num_columns       ,       1		)




 def    lowerCAmelCase_						(							self						:	Optional[Any]		):
       SCREAMING_SNAKE_CASE_					=    SplitInfo(name='train'       ,       num_examples=100		)
       SCREAMING_SNAKE_CASE_					=    SplitInfo(name='test'       ,       num_examples=100		)
       SCREAMING_SNAKE_CASE_					=    SplitDict()
       split_dict.add(_lowerCAmelCase		)
       split_dict.add(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_					=    DatasetInfo(splits=_lowerCAmelCase		)

       with tempfile.TemporaryDirectory() as tmp_dir:
             SCREAMING_SNAKE_CASE_					=    ReaderTest(_lowerCAmelCase       ,       _lowerCAmelCase		)

             SCREAMING_SNAKE_CASE_					=    [
                 {'filename': os.path.join(_lowerCAmelCase       ,       'train'		)},
                 {'filename': os.path.join(_lowerCAmelCase       ,       'test'		), 'skip': 10, 'take': 10},
             ]
             SCREAMING_SNAKE_CASE_					=    Dataset(**reader.read_files(_lowerCAmelCase       ,       original_instructions='train+test[10:20]'		)		)
             self.assertEqual(dset.num_rows       ,       110		)
             self.assertEqual(dset.num_columns       ,       1		)
             del dset


@pytest.mark.parametrize('in_memory'    ,    [False, True]							)
def       UpperCAmelCase_							(   __UpperCAmelCase		:			List[str]    ,    __UpperCAmelCase		:			Optional[int]    ,    __UpperCAmelCase		:			int							)      ->				str:
      SCREAMING_SNAKE_CASE_					=    arrow_file
      with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
            SCREAMING_SNAKE_CASE_					=    ArrowReader.read_table(__UpperCAmelCase    ,    in_memory=__UpperCAmelCase							)
      assert table.shape == dataset.data.shape
      assert set(table.column_names							) == set(dataset.data.column_names							)
      assert dict(table.to_pydict()							) == dict(dataset.data.to_pydict()							)  # to_pydict returns OrderedDict

@pytest.mark.parametrize('in_memory'    ,    [False, True]							)
def       UpperCAmelCase_							(   __UpperCAmelCase		:			Union[str, Any]    ,    __UpperCAmelCase		:			List[str]    ,    __UpperCAmelCase		:			Tuple							)      ->				Dict:
      SCREAMING_SNAKE_CASE_					=    arrow_file
      SCREAMING_SNAKE_CASE_					=    ArrowReader(''    ,    __UpperCAmelCase							)
      with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
            SCREAMING_SNAKE_CASE_					=    reader.read_files([{'filename': filename}]    ,    in_memory=__UpperCAmelCase							)
      assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
      SCREAMING_SNAKE_CASE_					=    dataset_kwargs['arrow_table']
      assert table.shape == dataset.data.shape
      assert set(table.column_names							) == set(dataset.data.column_names							)
      assert dict(table.to_pydict()							) == dict(dataset.data.to_pydict()							)  # to_pydict returns OrderedDict

def       UpperCAmelCase_							(   )      ->				str:
      assert ReadInstruction('train'    ,    to=10    ,    unit='abs'							).to_spec() == "train[:10]"
      assert ReadInstruction('train'    ,    from_=-80    ,    to=10    ,    unit='%'							).to_spec() == "train[-80%:10%]"

      SCREAMING_SNAKE_CASE_					=    'train+test'
      assert ReadInstruction.from_spec(__UpperCAmelCase							).to_spec() == spec_train_test

      SCREAMING_SNAKE_CASE_					=    'train[2:10]'
      assert ReadInstruction.from_spec(__UpperCAmelCase							).to_spec() == spec_train_abs

      SCREAMING_SNAKE_CASE_					=    'train[15%:-20%]'
      assert ReadInstruction.from_spec(__UpperCAmelCase							).to_spec() == spec_train_pct

      SCREAMING_SNAKE_CASE_					=    'train[:10%](closest)'
      assert ReadInstruction.from_spec(__UpperCAmelCase							).to_spec() == "train[:10%]"

      SCREAMING_SNAKE_CASE_					=    'train[:10%](pct1_dropremainder)'
      assert ReadInstruction.from_spec(__UpperCAmelCase							).to_spec() == spec_train_pct_rounding

      SCREAMING_SNAKE_CASE_					=    'train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)'
      assert ReadInstruction.from_spec(__UpperCAmelCase							).to_spec() == spec_train_test_pct_rounding

def       UpperCAmelCase_							(   )      ->				Optional[Any]:
      SCREAMING_SNAKE_CASE_					=    'dummy'
      SCREAMING_SNAKE_CASE_					=    [SplitInfo(name='train'    ,    num_examples=1_00							)]
      SCREAMING_SNAKE_CASE_					=    'train[:33%]'
      SCREAMING_SNAKE_CASE_					=    'arrow'
      SCREAMING_SNAKE_CASE_					=    'prefix'

      SCREAMING_SNAKE_CASE_					=    make_file_instructions(__UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase							)
      assert isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							)
      assert file_instructions.num_examples == 33
      assert file_instructions.file_instructions == [
          {"filename": os.path.join(__UpperCAmelCase    ,    f"{name}-train.arrow"							), "skip": 0, "take": 33}
      ]

      SCREAMING_SNAKE_CASE_					=    [SplitInfo(name='train'    ,    num_examples=1_00    ,    shard_lengths=[10] * 10							)]
      SCREAMING_SNAKE_CASE_					=    make_file_instructions(__UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase							)
      assert isinstance(__UpperCAmelCase    ,    __UpperCAmelCase							)
      assert file_instructions.num_examples == 33
      assert file_instructions.file_instructions == [
          {"filename": os.path.join(__UpperCAmelCase    ,    f"{name}-train-00000-of-00010.arrow"							), "skip": 0, "take": -1},
          {"filename": os.path.join(__UpperCAmelCase    ,    f"{name}-train-00001-of-00010.arrow"							), "skip": 0, "take": -1},
          {"filename": os.path.join(__UpperCAmelCase    ,    f"{name}-train-00002-of-00010.arrow"							), "skip": 0, "take": -1},
          {"filename": os.path.join(__UpperCAmelCase    ,    f"{name}-train-00003-of-00010.arrow"							), "skip": 0, "take": 3},
      ]





@pytest.mark.parametrize('name, expected_exception'    ,    [(None, TypeError), ('', ValueError)]							)
def       UpperCAmelCase_							(   __UpperCAmelCase		:			Any    ,    __UpperCAmelCase		:			List[str]							)      ->				Optional[Any]:
      SCREAMING_SNAKE_CASE_					=    [SplitInfo(name='train'    ,    num_examples=1_00							)]
      SCREAMING_SNAKE_CASE_					=    'train'
      SCREAMING_SNAKE_CASE_					=    'arrow'
      SCREAMING_SNAKE_CASE_					=    'prefix_path'
      with pytest.raises(__UpperCAmelCase							):
            SCREAMING_SNAKE_CASE_					=    make_file_instructions(__UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase    ,    __UpperCAmelCase							)