





'''simple docstring'''

import requests
from bsa import BeautifulSoup

def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase      )						->					str:

   '''simple docstring'''







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


if __name__ == "__main__":
    a        =						{
        "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))












'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a        =						{"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    a        =						[
        "SEW_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SEWForCTC",
        "SEWForSequenceClassification",
        "SEWModel",
        "SEWPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_sew import (
            SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
            SEWForCTC,
            SEWForSequenceClassification,
            SEWModel,
            SEWPreTrainedModel,
        )


else:
    import sys

    a        =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





