




'''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


A_ 			=		"none"
A_ 			=		"none"






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      Tuple:
      snake_case__					:      Optional[Any]  			=						value.split(__SCREAMING_SNAKE_CASE		)
      return len(__SCREAMING_SNAKE_CASE		) > 1 and any((len(__SCREAMING_SNAKE_CASE		) == 3 for x in split)		)






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      Union[str, Any]:
      if isinstance(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		):
            return value
      if isinstance(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		):
            return float(__SCREAMING_SNAKE_CASE		)
      if not isinstance(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		):
            raise ValueError('Argument value is not a string. Can\'t parse it as float'		)
      snake_case__					:      Optional[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(','							,			__SCREAMING_SNAKE_CASE		):
                  return float(sanitized.replace(','							,			''		)		)
            # 5,5556
            if "," in sanitized and sanitized.count(','		) == 1 and not _split_thousands(','							,			__SCREAMING_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(__SCREAMING_SNAKE_CASE		)
      except ValueError:
            # Avoid adding the sanitized value in the error message.
            raise ValueError('Unable to convert value to float'		)






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      Optional[int]:
      if answer is None:
            return None
      try:
            snake_case__					:      int  			=						convert_to_float(__SCREAMING_SNAKE_CASE		)
            if isinstance(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		) and math.isnan(__SCREAMING_SNAKE_CASE		):
                  return None
            return value
      except ValueError:
            return answer.lower()


A_ 			=		{
    "text": lambda x: x,
    "real": convert_to_float,
}






class 					lowercase_			(	enum.Enum       ):
     A_       							= 0
     A_       							= 1
     A_       							= 2
     A_       							= 3
     A_       							= 4
     A_       							= 5






class 					lowercase_			(	enum.Enum       ):
     A_       							= 0
     A_       							= 1
     A_       							= 2






@dataclasses.dataclass
class 					lowercase_			:
     A_       							= 42
     A_       							= 42
     A_       							= 42



A_ 			=		re.compile(R"\w+|[^\w\s]+", re.UNICODE | re.MULTILINE | re.DOTALL)






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      str:
      return list(_TOKENIZER.findall(x.lower()		)		)






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      Optional[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__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      Tuple:
      snake_case__					:      Tuple  			=						table['types']
      return _TYPE_CONVERTER[types[column]](__SCREAMING_SNAKE_CASE		)






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      Any:
      return isinstance(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      str:
      for cond in conditions:
            snake_case__					:      Dict  			=						row[cond.column]

            snake_case__					:      int  			=						_parse_value(__SCREAMING_SNAKE_CASE							,			cond.column							,			cond.cmp_value		)

            if _is_string(__SCREAMING_SNAKE_CASE		) and _is_string(__SCREAMING_SNAKE_CASE		):
                  snake_case__					:      Tuple  			=						_normalize_for_match(__SCREAMING_SNAKE_CASE		)
                  snake_case__					:      Optional[Any]  			=						_normalize_for_match(__SCREAMING_SNAKE_CASE		)

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

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






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      Optional[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(__SCREAMING_SNAKE_CASE		)		)

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

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






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      Optional[int]:
      snake_case__					:      Any  			=						sql_query['agg']
      if aggregation_op_index >= 3:
            snake_case__					:      List[str]  			=						_Aggregation(__SCREAMING_SNAKE_CASE		)
      else:
            snake_case__					:      List[Any]  			=						_Aggregation.NONE

      snake_case__					:      Dict  			=						sql_query['sel']
      snake_case__					:      Any  			=						[
          _Condition(__SCREAMING_SNAKE_CASE							,			_Operator(__SCREAMING_SNAKE_CASE		)							,			__SCREAMING_SNAKE_CASE		)
          for column, operator, cmp_value in zip(
              sql_query['conds']['column_index']							,			sql_query['conds']['operator_index']							,			sql_query['conds']['condition']		)
      ]

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

      if not indices:
            return [], aggregation_op

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

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

            snake_case__					:      Tuple  			=						[indices[reduced[1]]]
            return ret, _Aggregation.NONE

      return indices, aggregation_op






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






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)						->      List:
      snake_case__			,       snake_case__					:      Dict  			=						_get_answer_coordinates(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)
      snake_case__					:      Optional[int]  			=						_get_float_answer(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)
      snake_case__					:      Tuple  			=						_get_answer_text(__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE							,			__SCREAMING_SNAKE_CASE		)
      # keep the original data the same with TaPas
      if len(__SCREAMING_SNAKE_CASE		) == 0:
            snake_case__					:      List[str]  			=						[EMPTY_ANSWER]
      return answer_text






'''simple docstring'''






import bsa
import requests






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      dict[str, str]:
      return {
          "name": soup.ha.a.text,
          "genre": soup.find('span'							,			class_='genre'		).text.strip(),
          "rating": soup.strong.text,
          "page_link": f"https://www.imdb.com{soup.a.get('href'		)}",
      }






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE = 5		)						->      tuple:
      snake_case__					:      Tuple  			=						int(float(__SCREAMING_SNAKE_CASE		)		)
      if num_movies < 1:
            return ()
      snake_case__					:      Any  			=						(
          'https://www.imdb.com/search/title?title_type='
          f"feature&sort=num_votes,desc&count={num_movies}"
      )
      snake_case__					:      Union[str, Any]  			=						bsa.BeautifulSoup(requests.get(__SCREAMING_SNAKE_CASE		).content							,			'html.parser'		)
      return tuple(
          get_movie_data_from_soup(__SCREAMING_SNAKE_CASE		)
          for movie in source.find_all('div'							,			class_='lister-item mode-advanced'		)		)


if __name__ == "__main__":
      import json

      A_ 			=		int(input("How many movies would you like to see? "))
      print(
          ", ".join(
              json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
          )
      )
