



"""simple docstring"""







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:  int			     =				"""none"""
UpperCAmelCase:  Optional[int]			     =				"""none"""


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase      ):
		_lowercase				: Dict     =   value.split(__UpperCAmelCase      )
		return len(__UpperCAmelCase      ) > 1 and any((len(__UpperCAmelCase      ) == 3 for x in split)      )


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase      ):
		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"""      )
		_lowercase				: List[Any]     =   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  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase      ):
		if answer is None:
				return None
		try:
				_lowercase				: int     =   convert_to_float(__UpperCAmelCase      )
				if isinstance(__UpperCAmelCase   ,				__UpperCAmelCase      ) and math.isnan(__UpperCAmelCase      ):
						return None
				return value
		except ValueError:
				return answer.lower()


UpperCAmelCase:  Any			     =				{
    """text""": lambda x: x,
    """real""": convert_to_float,
}





class   UpperCamelCase	(     enum.Enum       ):




	"""simple docstring"""
	SCREAMING_SNAKE_CASE_							:       Optional[Any]						       =  0
	SCREAMING_SNAKE_CASE_							:       List[str]						       =  1
	SCREAMING_SNAKE_CASE_							:       Dict						       =  2
	SCREAMING_SNAKE_CASE_							:       int						       =  3
	SCREAMING_SNAKE_CASE_							:       Any						       =  4
	SCREAMING_SNAKE_CASE_							:       List[Any]						       =  5







class   UpperCamelCase	(     enum.Enum       ):




	"""simple docstring"""
	SCREAMING_SNAKE_CASE_							:       Optional[Any]						       =  0
	SCREAMING_SNAKE_CASE_							:       Dict						       =  1
	SCREAMING_SNAKE_CASE_							:       Optional[int]						       =  2







@dataclasses.dataclass
class   UpperCamelCase	:




	"""simple docstring"""
	SCREAMING_SNAKE_CASE_							:       Text
	SCREAMING_SNAKE_CASE_							:       _Operator
	SCREAMING_SNAKE_CASE_							:       Any







UpperCAmelCase:  List[str]			     =				re.compile(r"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase      ):
		return list(_TOKENIZER.findall(x.lower()      )      )


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      ):
		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  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      ):
		_lowercase				: Optional[int]     =   table["""types"""]
		return _TYPE_CONVERTER[types[column]](__UpperCAmelCase      )


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase      ):
		return isinstance(__UpperCAmelCase   ,				__UpperCAmelCase      )


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      ):
		for cond in conditions:
				_lowercase				: Optional[Any]     =   row[cond.column]

				_lowercase				: List[Any]     =   _parse_value(__UpperCAmelCase   ,				cond.column   ,				cond.cmp_value      )

				if _is_string(__UpperCAmelCase      ) and _is_string(__UpperCAmelCase      ):
						_lowercase				: List[str]     =   _normalize_for_match(__UpperCAmelCase      )
						_lowercase				: Any     =   _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  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      ):
		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.
		_lowercase				: int     =   [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  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase      ):
		_lowercase				: Tuple     =   sql_query["""agg"""]
		if aggregation_op_index >= 3:
				_lowercase				: Tuple     =   _Aggregation(__UpperCAmelCase      )
		else:
				_lowercase				: Optional[Any]     =   _Aggregation.NONE

		_lowercase				: str     =   sql_query["""sel"""]
		_lowercase				: Tuple     =   [
		    _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"""]      )
		]

		_lowercase				: Optional[Any]     =   []
		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):
				_lowercase				: Tuple     =   {2: min, 1: max}
				_lowercase				: Union[str, Any]     =   [(table["""rows"""][i][j], index) for index, (i, j) in enumerate(__UpperCAmelCase      )]
				_lowercase				: List[str]     =   functools.reduce(operators[sql_query["""agg"""]]   ,				__UpperCAmelCase      )

				_lowercase				: Dict     =   [indices[reduced[1]]]
				return ret, _Aggregation.NONE

		return indices, aggregation_op


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      ):
		if float_answer is not None:
				return [str(__UpperCAmelCase      )]
		return [str(table["""real_rows"""][r][c]      ) for r, c in answer_coordinates]


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase      ):
		_lowercase     ,  _lowercase				: Union[str, Any]     =   _get_answer_coordinates(__UpperCAmelCase   ,				__UpperCAmelCase      )
		_lowercase				: List[Any]     =   _get_float_answer(__UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      )
		_lowercase				: Optional[Any]     =   _get_answer_text(__UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      )
		# keep the original data the same with TaPas
		if len(__UpperCAmelCase      ) == 0:
				_lowercase				: Dict     =   [EMPTY_ANSWER]
		return answer_text








from collections import defaultdict

def       A_   (						__a  :					str		):

				"""simple docstring"""
				a__					   =		defaultdict(__a		)
				# Creating a dictionary containing count of each word
				for word in sentence.split():
								occurrence[word] += 1
				return occurrence


if __name__ == "__main__":
	for word, count in word_occurrence("""INPUT STRING""").items():
		print(f"""{word}: {count}""")

