"""simple docstring"""






import json
import os
from typing import Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_A   					=    logging.get_logger(__name__)

_A   					=    {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

_A   					=    {
    'vocab_file': {'ctrl': 'https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json'},
    'merges_file': {'ctrl': 'https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt'},
}

_A   					=    {
    'ctrl': 2_5_6,
}

_A   					=    {
    'Pregnancy': 1_6_8_6_2_9,
    'Christianity': 7_6_7_5,
    'Explain': 1_0_6_4_2_3,
    'Fitness': 6_3_4_4_0,
    'Saving': 6_3_1_6_3,
    'Ask': 2_7_1_7_1,
    'Ass': 9_5_9_8_5,
    'Joke': 1_6_3_5_0_9,
    'Questions': 4_5_6_2_2,
    'Thoughts': 4_9_6_0_5,
    'Retail': 5_2_3_4_2,
    'Feminism': 1_6_4_3_3_8,
    'Writing': 1_1_9_9_2,
    'Atheism': 1_9_2_2_6_3,
    'Netflix': 4_8_6_1_6,
    'Computing': 3_9_6_3_9,
    'Opinion': 4_3_2_1_3,
    'Alone': 4_4_9_6_7,
    'Funny': 5_8_9_1_7,
    'Gaming': 4_0_3_5_8,
    'Human': 4_0_8_8,
    'India': 1_3_3_1,
    'Joker': 7_7_1_3_8,
    'Diet': 3_6_2_0_6,
    'Legal': 1_1_8_5_9,
    'Norman': 4_9_3_9,
    'Tip': 7_2_6_8_9,
    'Weight': 5_2_3_4_3,
    'Movies': 4_6_2_7_3,
    'Running': 2_3_4_2_5,
    'Science': 2_0_9_0,
    'Horror': 3_7_7_9_3,
    'Confession': 6_0_5_7_2,
    'Finance': 1_2_2_5_0,
    'Politics': 1_6_3_6_0,
    'Scary': 1_9_1_9_8_5,
    'Support': 1_2_6_5_4,
    'Technologies': 3_2_5_1_6,
    'Teenage': 6_6_1_6_0,
    'Event': 3_2_7_6_9,
    'Learned': 6_7_4_6_0,
    'Notion': 1_8_2_7_7_0,
    'Wikipedia': 3_7_5_8_3,
    'Books': 6_6_6_5,
    'Extract': 7_6_0_5_0,
    'Confessions': 1_0_2_7_0_1,
    'Conspiracy': 7_5_9_3_2,
    'Links': 6_3_6_7_4,
    'Narcissus': 1_5_0_4_2_5,
    'Relationship': 5_4_7_6_6,
    'Relationships': 1_3_4_7_9_6,
    'Reviews': 4_1_6_7_1,
    'News': 4_2_5_6,
    'Translation': 2_6_8_2_0,
    'multilingual': 1_2_8_4_0_6,
}




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase       )							->   Optional[Any]:
				SCREAMING_SNAKE_CASE__		  =				set()
				SCREAMING_SNAKE_CASE__		  =				word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)       )
								SCREAMING_SNAKE_CASE__		  =				char

				SCREAMING_SNAKE_CASE__		  =				set(__UpperCAmelCase       )
				return pairs

class lowerCamelCase		(_SCREAMING_SNAKE_CASE      ):






					'''simple docstring'''


					a   	=		VOCAB_FILES_NAMES
					a   	=		PRETRAINED_VOCAB_FILES_MAP
					a   	=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					a   	=		CONTROL_CODES



					def __init__(						self			:				str   , _snake_case			:				Union[str, Any]   , _snake_case			:				Tuple   , _snake_case			:				Dict="<unk>"   , **_snake_case			:				List[str]		)							->       Tuple:
									super().__init__(unk_token=_snake_case   , **_snake_case		)

									with open(_snake_case   , encoding="utf-8"		) as vocab_handle:
													SCREAMING_SNAKE_CASE__		  =				json.load(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				{v: k for k, v in self.encoder.items()}
									with open(_snake_case   , encoding="utf-8"		) as merges_handle:
													SCREAMING_SNAKE_CASE__		  =				merges_handle.read().split("\n"		)[1:-1]
									SCREAMING_SNAKE_CASE__		  =				[tuple(merge.split()		) for merge in merges]
									SCREAMING_SNAKE_CASE__		  =				dict(zip(_snake_case   , range(len(_snake_case		)		)		)		)
									SCREAMING_SNAKE_CASE__		  =				{}



					@property
					def 			lowerCAmelCase_					(						self			:				List[str]		)							->       Dict:
									return len(self.encoder		)



					def 			lowerCAmelCase_					(						self			:				str		)							->       int:
									return dict(self.encoder   , **self.added_tokens_encoder		)



					def 			lowerCAmelCase_					(						self			:				Any   , _snake_case			:				int		)							->       Optional[Any]:
									if token in self.cache:
													return self.cache[token]
									SCREAMING_SNAKE_CASE__		  =				tuple(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tuple(list(word[:-1]		) + [word[-1] + "</w>"]		)
									SCREAMING_SNAKE_CASE__		  =				get_pairs(_snake_case		)

									if not pairs:
													return token

									while True:
													SCREAMING_SNAKE_CASE__		  =				min(_snake_case   , key=lambda _snake_case		: self.bpe_ranks.get(_snake_case   , float("inf"		)		)		)
													if bigram not in self.bpe_ranks:
																	break
													SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				bigram
													SCREAMING_SNAKE_CASE__		  =				[]
													SCREAMING_SNAKE_CASE__		  =				0
													while i < len(_snake_case		):
																	try:
																					SCREAMING_SNAKE_CASE__		  =				word.index(_snake_case   , _snake_case		)
																	except ValueError:
																					new_word.extend(word[i:]		)
																					break
																	else:
																					new_word.extend(word[i:j]		)
																					SCREAMING_SNAKE_CASE__		  =				j

																	if word[i] == first and i < len(_snake_case		) - 1 and word[i + 1] == second:
																					new_word.append(first + second		)
																					i += 2
																	else:
																					new_word.append(word[i]		)
																					i += 1
													SCREAMING_SNAKE_CASE__		  =				tuple(_snake_case		)
													SCREAMING_SNAKE_CASE__		  =				new_word
													if len(_snake_case		) == 1:
																	break
													else:
																	SCREAMING_SNAKE_CASE__		  =				get_pairs(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				"@@ ".join(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				word[:-4]
									SCREAMING_SNAKE_CASE__		  =				word
									return word



					def 			lowerCAmelCase_					(						self			:				Optional[Any]   , _snake_case			:				Tuple		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				[]

									SCREAMING_SNAKE_CASE__		  =				re.findall(r"\S+\n?"   , _snake_case		)

									for token in words:
													split_tokens.extend(list(self.bpe(_snake_case		).split(" "		)		)		)
									return split_tokens



					def 			lowerCAmelCase_					(						self			:				Optional[Any]   , _snake_case			:				Union[str, Any]		)							->       List[Any]:
									return self.encoder.get(_snake_case   , self.encoder.get(self.unk_token		)		)



					def 			lowerCAmelCase_					(						self			:				Optional[int]   , _snake_case			:				Dict		)							->       Optional[Any]:
									return self.decoder.get(_snake_case   , self.unk_token		)



					def 			lowerCAmelCase_					(						self			:				Tuple   , _snake_case			:				Union[str, Any]		)							->       Any:
									SCREAMING_SNAKE_CASE__		  =				" ".join(_snake_case		).replace("@@ "   , ""		).strip()
									return out_string



					def 			lowerCAmelCase_					(						self			:				List[str]   , _snake_case			:				str   , _snake_case			:				Optional[str] = None		)							->       Tuple[str]:
									if not os.path.isdir(_snake_case		):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""		)
													return
									SCREAMING_SNAKE_CASE__		  =				os.path.join(
									    _snake_case   , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
									SCREAMING_SNAKE_CASE__		  =				os.path.join(
									    _snake_case   , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]		)

									with open(_snake_case   , "w"   , encoding="utf-8"		) as f:
													f.write(json.dumps(self.encoder   , indent=2   , sort_keys=_snake_case   , ensure_ascii=_snake_case		) + "\n"		)

									SCREAMING_SNAKE_CASE__		  =				0
									with open(_snake_case   , "w"   , encoding="utf-8"		) as writer:
													writer.write("#version: 0.2\n"		)
													for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   , key=lambda _snake_case		: kv[1]		):
																	if index != token_index:
																					logger.warning(
																					    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																					    " Please check that the tokenizer is not corrupted!"		)
																					SCREAMING_SNAKE_CASE__		  =				token_index
																	writer.write(" ".join(_snake_case		) + "\n"		)
																	index += 1

									return vocab_file, merge_file

					# def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
					#     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
					#     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
					#     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
					#     return ''.join(tokens_generated_so_far)





"""simple docstring"""






from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

_A   					=    'https://www.indeed.co.in/jobs?q=mobile+app+development&l='




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase = "mumbai"       )							->   Generator[tuple[str, str], None, None]:
				SCREAMING_SNAKE_CASE__		  =				BeautifulSoup(requests.get(url + location       ).content  ,					"html.parser"       )
				# This attribute finds out all the specifics listed in a job
				for job in soup.find_all("div"  ,					attrs={"data-tn-component": "organicJob"}       ):
								SCREAMING_SNAKE_CASE__		  =				job.find("a"  ,					attrs={"data-tn-element": "jobTitle"}       ).text.strip()
								SCREAMING_SNAKE_CASE__		  =				job.find("span"  ,					{"class": "company"}       ).text.strip()
								yield job_title, company_name


if __name__ == "__main__":
						for i, job in enumerate(fetch_jobs('Bangalore'), 1):
												print(F'Job {i:>2} is {job[0]} at {job[1]}')




