




import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case__   )
class     a__					(      snake_case__   ):
						# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
						_a							:					str      =					field(default="""text-classification"""				,       metadata={"""include_in_asdict_even_if_is_default""": True}   )
						_a							:					ClassVar[Features]      =					Features({"""text""": Value("""string"""   )}   )
						_a							:					ClassVar[Features]      =					Features({"""labels""": ClassLabel}   )
						_a							:					str      =					"text"
						_a							:					str      =					"labels"






						def        __SCREAMING_SNAKE_CASE(     self	,    _A    ):




											"""simple docstring"""



											if self.label_column not in features:
																raise ValueError(f"""Column {self.label_column} is not present in features."""    )
											if not isinstance(features[self.label_column]	,    _A    ):
																raise ValueError(f"""Column {self.label_column} is not a ClassLabel."""    )
											__lowerCAmelCase            = copy.deepcopy(self    )
											__lowerCAmelCase            = self.label_schema.copy()
											__lowerCAmelCase            = features[self.label_column]
											__lowerCAmelCase            = label_schema
											return task_template






						@property
						def        __SCREAMING_SNAKE_CASE(     self    ):




											"""simple docstring"""



											return {
											    self.text_column: "text",
											    self.label_column: "labels",
											}










import requests
from bsa import BeautifulSoup







def 			_a   (		SCREAMING_SNAKE_CASE_							:       str   ,   SCREAMING_SNAKE_CASE_							:       dict  ):
					__lowerCAmelCase            = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE_   ,   params=SCREAMING_SNAKE_CASE_  ).content   ,   "html.parser"  )
					__lowerCAmelCase            = soup.find("div"   ,   attrs={"class": "gs_ri"}  )
					__lowerCAmelCase            = div.find("div"   ,   attrs={"class": "gs_fl"}  ).find_all("a"  )
					return anchors[2].get_text()


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




