





"""simple docstring"""





from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

SCREAMING_SNAKE_CASE__   =  {'UserAgent': UserAgent().random}


def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		Optional[Any]     ):







      '''simple docstring'''




      lowerCAmelCase    		=			script.contents[0]
      lowerCAmelCase    		=			json.loads(data[data.find("""{\"config\""""     ) : -1]     )
      return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]

class 						lowercase   :





      def __init__(			self ,		lowercase					)						->	List[Any]:
            lowerCAmelCase    		=			f'https://www.instagram.com/{username}/'
            lowerCAmelCase    		=			self.get_json()





      def        _snake_case     (			self					)						->	int:
            lowerCAmelCase    		=			requests.get(self.url ,		headers=A__					).text
            lowerCAmelCase    		=			BeautifulSoup(A__ ,		"""html.parser"""					).find_all("""script"""					)
            try:
                  return extract_user_profile(scripts[4]					)
            except (json.decoder.JSONDecodeError, KeyError):
                  return extract_user_profile(scripts[3]					)





      def __repr__(			self					)						->	Optional[int]:
            return f'{self.__class__.__name__}(\'{self.username}\')'





      def __str__(			self					)						->	List[str]:
            return f'{self.fullname} ({self.username}) is {self.biography}'





      @property
      def        _snake_case     (			self					)						->	Union[str, Any]:
            return self.user_data["username"]





      @property
      def        _snake_case     (			self					)						->	Union[str, Any]:
            return self.user_data["full_name"]





      @property
      def        _snake_case     (			self					)						->	List[Any]:
            return self.user_data["biography"]





      @property
      def        _snake_case     (			self					)						->	str:
            return self.user_data["business_email"]





      @property
      def        _snake_case     (			self					)						->	Optional[Any]:
            return self.user_data["external_url"]





      @property
      def        _snake_case     (			self					)						->	List[Any]:
            return self.user_data["edge_followed_by"]["count"]





      @property
      def        _snake_case     (			self					)						->	int:
            return self.user_data["edge_follow"]["count"]





      @property
      def        _snake_case     (			self					)						->	Union[str, Any]:
            return self.user_data["edge_owner_to_timeline_media"]["count"]





      @property
      def        _snake_case     (			self					)						->	str:
            return self.user_data["profile_pic_url_hd"]





      @property
      def        _snake_case     (			self					)						->	Optional[int]:
            return self.user_data["is_verified"]





      @property
      def        _snake_case     (			self					)						->	Dict:
            return self.user_data["is_private"]







def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		str = "github"     ):







      '''simple docstring'''




      import os

      if os.environ.get("""CI"""     ):
            return  # test failing on GitHub Actions
      lowerCAmelCase    		=			InstagramUser(__lowercase     )
      assert instagram_user.user_data
      assert isinstance(instagram_user.user_data				,		__lowercase     )
      assert instagram_user.username == username
      if username != "github":
            return
      assert instagram_user.fullname == "GitHub"
      assert instagram_user.biography == "Built for developers."
      assert instagram_user.number_of_posts > 1_50
      assert instagram_user.number_of_followers > 12_00_00
      assert instagram_user.number_of_followings > 15
      assert instagram_user.email == "support@github.com"
      assert instagram_user.website == "https://github.com/readme"
      assert instagram_user.profile_picture_url.startswith("""https://instagram."""     )
      assert instagram_user.is_verified is True
      assert instagram_user.is_private is False


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       SCREAMING_SNAKE_CASE__   =  InstagramUser("github")
       print(instagram_user)
       print(f'{instagram_user.number_of_posts = }')
       print(f'{instagram_user.number_of_followers = }')
       print(f'{instagram_user.number_of_followings = }')
       print(f'{instagram_user.email = }')
       print(f'{instagram_user.website = }')
       print(f'{instagram_user.profile_picture_url = }')
       print(f'{instagram_user.is_verified = }')
       print(f'{instagram_user.is_private = }')














from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCamelCase			:	Any								={
    'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCamelCase			:	Optional[Any]								=[
	    'MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'MegatronBertForCausalLM',
	    'MegatronBertForMaskedLM',
	    'MegatronBertForMultipleChoice',
	    'MegatronBertForNextSentencePrediction',
	    'MegatronBertForPreTraining',
	    'MegatronBertForQuestionAnswering',
	    'MegatronBertForSequenceClassification',
	    'MegatronBertForTokenClassification',
	    'MegatronBertModel',
	    'MegatronBertPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_megatron_bert import (
		    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MegatronBertForCausalLM,
		    MegatronBertForMaskedLM,
		    MegatronBertForMultipleChoice,
		    MegatronBertForNextSentencePrediction,
		    MegatronBertForPreTraining,
		    MegatronBertForQuestionAnswering,
		    MegatronBertForSequenceClassification,
		    MegatronBertForTokenClassification,
		    MegatronBertModel,
		    MegatronBertPreTrainedModel,
		)

else:
	import sys

	_UpperCamelCase			:	Optional[int]								=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



