"""simple docstring"""




from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
     _a				:		List[Any]	   =       input('Enter image url: ').strip()
     print(F"""Downloading image from {url} ...""")
     _a				:		str	   =       BeautifulSoup(requests.get(url).content, 'html.parser')
     # The image URL is in the content field of the first meta tag with property og:image
     _a				:		List[str]	   =       soup.find('meta', {'property': 'og:image'})['content']
     _a				:		Union[str, Any]	   =       requests.get(image_url).content
     _a				:		str	   =       F"""{datetime.now():%Y-%m-%d_%H:%M:%S}.jpg"""
     with open(file_name, 'wb') as fp:
          fp.write(image_data)
     print(F"""Done. Image saved to disk as {file_name}.""")





"""simple docstring"""




from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def __init__(		self    ,					a__    ,					a__ = None    ,					a__ = None    ,					a__ = True    ,					a__ = None    ,					a__ = False    ,					a__ = None    ,					a__ = True    ,					a__ = "arrow"    ,					**a__    ,					):
       super().__init__(
           split=a__    ,					features=a__    ,					cache_dir=a__    ,					keep_in_memory=a__    ,					streaming=a__    ,					**a__    ,					)
       _lowerCAmelCase						:	List[Any]        =					load_from_cache_file
       _lowerCAmelCase						:	str        =					file_format
       _lowerCAmelCase						:	Dict        =					Spark(
           df=a__    ,					features=a__    ,					cache_dir=a__    ,					working_dir=a__    ,					**a__    ,					)






     def    __A  (		self  ):
       if self.streaming:
         return self.builder.as_streaming_dataset(split=self.split  )
       _lowerCAmelCase						:	Dict        =					None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
       self.builder.download_and_prepare(
           download_mode=a__    ,					file_format=self._file_format    ,					)
       return self.builder.as_dataset(split=self.split  )




