


'''simple docstring'''







from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
   _lowercase       						=			input('Enter image url: ').strip()
   print(f'Downloading image from {url} ...')
   _lowercase       						=			BeautifulSoup(requests.get(url).content, 'html.parser')
   # The image URL is in the content field of the first meta tag with property og:image
   _lowercase       						=			soup.find('meta', {'property': 'og:image'})['content']
   _lowercase       						=			requests.get(image_url).content
   _lowercase       						=			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'''







import inspect
import re
from hashlib import shaaaa
from typing import Dict, List

from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql  # noqa F401
from .text import text

def    __UpperCamelCase	(	a    : List[str]     ) ->str:
 snake_case				=			[]
 for line in lines:
  snake_case				=			re.sub(R'''#.*'''					,   ''''''					,   a     )  # remove comments
  if line:
   filtered_lines.append(a     )
 snake_case				=			'''\n'''.join(a     )

 # Make a hash from all this code
 snake_case				=			full_str.encode('''utf-8'''     )
 return shaaaa(a     ).hexdigest()


# get importable module names and hash for caching
_lowercase       						=			{
    'csv': (csv.__name__, _hash_python_lines(inspect.getsource(csv).splitlines())),
    'json': (json.__name__, _hash_python_lines(inspect.getsource(json).splitlines())),
    'pandas': (pandas.__name__, _hash_python_lines(inspect.getsource(pandas).splitlines())),
    'parquet': (parquet.__name__, _hash_python_lines(inspect.getsource(parquet).splitlines())),
    'arrow': (arrow.__name__, _hash_python_lines(inspect.getsource(arrow).splitlines())),
    'text': (text.__name__, _hash_python_lines(inspect.getsource(text).splitlines())),
    'imagefolder': (imagefolder.__name__, _hash_python_lines(inspect.getsource(imagefolder).splitlines())),
    'audiofolder': (audiofolder.__name__, _hash_python_lines(inspect.getsource(audiofolder).splitlines())),
}

# Used to infer the module to use based on the data files extensions
_lowercase       						=			{
    '.csv': ('csv', {}),
    '.tsv': ('csv', {'sep': '\t'}),
    '.json': ('json', {}),
    '.jsonl': ('json', {}),
    '.parquet': ('parquet', {}),
    '.arrow': ('arrow', {}),
    '.txt': ('text', {}),
}
_EXTENSION_TO_MODULE.update({ext: ('imagefolder', {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ('imagefolder', {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext: ('audiofolder', {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
_EXTENSION_TO_MODULE.update({ext.upper(): ('audiofolder', {}) for ext in audiofolder.AudioFolder.EXTENSIONS})
_lowercase       						=			{'imagefolder', 'audiofolder'}

# Used to filter data files based on extensions given a module name
_lowercase       						=			{}
for _ext, (_module, _) in _EXTENSION_TO_MODULE.items():
   _MODULE_TO_EXTENSIONS.setdefault(_module, []).append(_ext)

_MODULE_TO_EXTENSIONS["imagefolder"].append('.zip')






_MODULE_TO_EXTENSIONS["audiofolder"].append('.zip')

