






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


_UpperCAmelCase				:	Optional[Any]    						=    '''none'''
_UpperCAmelCase				:	Any    						=    '''none'''






def    UpperCAmelCase__	(						lowerCamelCase  : List[Any] ,lowerCamelCase  : List[Any]						):
   lowerCamelCase											=value.split(snake_case__						)
   return len(snake_case__						) > 1 and any((len(snake_case__						) == 3 for x in split)						)






def    UpperCAmelCase__	(						lowerCamelCase  : Optional[int]						):
   if isinstance(snake_case__ ,snake_case__						):
      return value
   if isinstance(snake_case__ ,snake_case__						):
      return float(snake_case__						)
   if not isinstance(snake_case__ ,snake_case__						):
      raise ValueError("""Argument value is not a string. Can\'t parse it as float"""						)
   lowerCamelCase											=value

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






def    UpperCAmelCase__	(						lowerCamelCase  : Union[str, Any]						):
   if answer is None:
      return None
   try:
      lowerCamelCase											=convert_to_float(snake_case__						)
      if isinstance(snake_case__ ,snake_case__						) and math.isnan(snake_case__						):
         return None
      return value
   except ValueError:
      return answer.lower()


_UpperCAmelCase				:	List[Any]    						=    {
    '''text''': lambda x: x,
    '''real''': convert_to_float,
}


class 		lowerCAmelCase_							(     enum.Enum   ):
     __lowerCamelCase					:						List[str]     =    0
     __lowerCamelCase					:						Dict     =    1
     __lowerCamelCase					:						Tuple     =    2
     __lowerCamelCase					:						List[str]     =    3
     __lowerCamelCase					:						List[Any]     =    4
     __lowerCamelCase					:						Dict     =    5




class 		lowerCAmelCase_							(     enum.Enum   ):
     __lowerCamelCase					:						Tuple     =    0
     __lowerCamelCase					:						List[Any]     =    1
     __lowerCamelCase					:						Dict     =    2




@dataclasses.dataclass
class 		lowerCAmelCase_							:
     __lowerCamelCase					:						Text
     __lowerCamelCase					:						_Operator
     __lowerCamelCase					:						Any




_UpperCAmelCase				:	str    						=    re.compile(R'\w+|[^\w\s]+', re.UNICODE | re.MULTILINE | re.DOTALL)






def    UpperCAmelCase__	(						lowerCamelCase  : Dict						):
   return list(_TOKENIZER.findall(x.lower()						)						)






def    UpperCAmelCase__	(						lowerCamelCase  : str ,lowerCamelCase  : Dict ,lowerCamelCase  : Tuple						):
   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__	(						lowerCamelCase  : Tuple ,lowerCamelCase  : Union[str, Any] ,lowerCamelCase  : Any						):
   lowerCamelCase											=table["""types"""]
   return _TYPE_CONVERTER[types[column]](snake_case__						)






def    UpperCAmelCase__	(						lowerCamelCase  : int						):
   return isinstance(snake_case__ ,snake_case__						)






def    UpperCAmelCase__	(						lowerCamelCase  : Optional[Any] ,lowerCamelCase  : List[Any] ,lowerCamelCase  : Any						):
   for cond in conditions:
      lowerCamelCase											=row[cond.column]

      lowerCamelCase											=_parse_value(snake_case__ ,cond.column ,cond.cmp_value						)

      if _is_string(snake_case__						) and _is_string(snake_case__						):
         lowerCamelCase											=_normalize_for_match(snake_case__						)
         lowerCamelCase											=_normalize_for_match(snake_case__						)

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

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






def    UpperCAmelCase__	(						lowerCamelCase  : List[str] ,lowerCamelCase  : Dict ,lowerCamelCase  : List[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(snake_case__						)						)

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

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






def    UpperCAmelCase__	(						lowerCamelCase  : int ,lowerCamelCase  : Any						):
   lowerCamelCase											=sql_query["""agg"""]
   if aggregation_op_index >= 3:
      lowerCamelCase											=_Aggregation(snake_case__						)
   else:
      lowerCamelCase											=_Aggregation.NONE

   lowerCamelCase											=sql_query["""sel"""]
   lowerCamelCase											=[
       _Condition(snake_case__ ,_Operator(snake_case__						) ,snake_case__						)
       for column, operator, cmp_value in zip(
           sql_query["""conds"""]["""column_index"""] ,sql_query["""conds"""]["""operator_index"""] ,sql_query["""conds"""]["""condition"""]						)
   ]

   lowerCamelCase											=[]
   for row in range(len(table["""rows"""]						)						):
      if _respect_conditions(snake_case__ ,table["""rows"""][row] ,snake_case__						):
         indices.append((row, target_column)						)

   if not indices:
      return [], aggregation_op

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

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

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

   return indices, aggregation_op






def    UpperCAmelCase__	(						lowerCamelCase  : Tuple ,lowerCamelCase  : Union[str, Any] ,lowerCamelCase  : str						):
   if float_answer is not None:
      return [str(snake_case__						)]
   return [str(table["""real_rows"""][r][c]						) for r, c in answer_coordinates]







def    UpperCAmelCase__	(						lowerCamelCase  : Optional[Any] ,lowerCamelCase  : List[str]						):
   lowerCamelCase							,					lowerCamelCase											=_get_answer_coordinates(snake_case__ ,snake_case__						)
   lowerCamelCase											=_get_float_answer(snake_case__ ,snake_case__ ,snake_case__						)
   lowerCamelCase											=_get_answer_text(snake_case__ ,snake_case__ ,snake_case__						)
   # keep the original data the same with TaPas
   if len(snake_case__						) == 0:
      lowerCamelCase											=[EMPTY_ANSWER]
   return answer_text







from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier

# Load iris file
_UpperCAmelCase				:	Optional[int]    						=    load_iris()
iris.keys()


print(f"Target names: \n {iris.target_names} ")
print(f"\n Features: \n {iris.feature_names}")

# Train set e Test set
_UpperCAmelCase						,						_UpperCAmelCase						,						_UpperCAmelCase						,						_UpperCAmelCase				:	List[Any]    						=    train_test_split(
    iris['data'], iris['target'], random_state=4
)

# KNN

_UpperCAmelCase				:	Optional[int]    						=    KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)

# new array to test
_UpperCAmelCase				:	List[Any]    						=    [[1, 2, 1, 4], [2, 3, 4, 5]]

_UpperCAmelCase				:	Tuple    						=    knn.predict(X_new)

print(
    f"\nNew array: \n {X_new}\n\nTarget Names Prediction: \n"
    f" {iris['target_names'][prediction]}"
)