




import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD




def 					lowerCamelCase__       (						A__       :					Optional[int]	):





       '''simple docstring'''



       def wrapper(*A__       :					Dict  ,			**A__       :					Dict	):
              __lowerCamelCase   =						timeit.default_timer()
              __lowerCamelCase   =						func(*A__  ,			**A__	)
              __lowerCamelCase   =						timeit.default_timer() - starttime
              return delta

       __lowerCamelCase   =						func.__name__

       return wrapper




def 					lowerCamelCase__       (						A__       :					dict  ,			A__       :					Tuple=100  ,			A__       :					Optional[Any]=None	):





       '''simple docstring'''



       __lowerCamelCase   =						[]
       __lowerCamelCase   =						seq_shapes or {}
       for i in range(A__	):
              __lowerCamelCase   =						{}
              for col_id, (k, v) in enumerate(features.items()	):
                     if isinstance(A__  ,			_ArrayXD	):
                            __lowerCamelCase   =						np.random.rand(*v.shape	).astype(v.dtype	)
                     elif isinstance(A__  ,			datasets.Value	):
                            if v.dtype == "string":
                                   __lowerCamelCase   =						"""The small grey turtle was surprisingly fast when challenged."""
                            else:
                                   __lowerCamelCase   =						np.random.randint(10  ,			size=1	).astype(v.dtype	).item()
                     elif isinstance(A__  ,			datasets.Sequence	):
                            while isinstance(A__  ,			datasets.Sequence	):
                                   __lowerCamelCase   =						v.feature
                            __lowerCamelCase   =						seq_shapes[k]
                            __lowerCamelCase   =						np.random.rand(*A__	).astype(v.dtype	)
                     __lowerCamelCase   =						data

              dummy_data.append((i, example)	)

       return dummy_data




def 					lowerCamelCase__       (						A__       :					Tuple  ,			A__       :					Union[str, Any]  ,			A__       :					Optional[int]=100  ,			A__       :					int=None	):





       '''simple docstring'''



       __lowerCamelCase   =						generate_examples(A__  ,			num_examples=A__  ,			seq_shapes=A__	)

       with ArrowWriter(features=A__  ,			path=A__	) as writer:
              for key, record in dummy_data:
                     __lowerCamelCase   =						features.encode_example(A__	)
                     writer.write(A__	)

              __lowerCamelCase,   __lowerCamelCase   =						writer.finalize()

       if not num_final_examples == num_examples:
              raise ValueError(
                  f'Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}.'	)

       __lowerCamelCase   =						datasets.Dataset.from_file(filename=A__  ,			info=datasets.DatasetInfo(features=A__	)	)

       return dataset







import requests
from bsa import BeautifulSoup







def SCREAMING_SNAKE_CASE				(       lowercase_ ,				lowercase_						)   ->       str:



       """simple docstring"""

       A__       =    BeautifulSoup(requests.get(lowercase_ ,				params=lowercase_						).content ,				'''html.parser'''						)
       A__       =    soup.find('''div''' ,				attrs={'''class''': '''gs_ri'''}						)
       A__       =    div.find('''div''' ,				attrs={'''class''': '''gs_fl'''}						).find_all('''a'''						)
       return anchors[2].get_text()


if __name__ == "__main__":
  _lowerCamelCase	:		Optional[Any]							       =   {
      """title""": (
          """Precisely geometry controlled microsupercapacitors for ultrahigh areal """
          """capacitance, volumetric capacitance, and energy density"""
      ),
      """journal""": """Chem. Mater.""",
      """volume""": 30,
      """pages""": """3979-3990""",
      """year""": 2018,
      """hl""": """en""",
  }
  print(get_citation("""https://scholar.google.com/scholar_lookup""", params=params))


