



import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer







def snake_case__	(      __SCREAMING_SNAKE_CASE			)		->				Dict:
		# This defines a "chinese character" as anything in the CJK Unicode block:
		#   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
		#
		# Note that the CJK Unicode block is NOT all Japanese and Korean characters,
		# despite its name. The modern Korean Hangul alphabet is a different block,
		# as is Japanese Hiragana and Katakana. Those alphabets are used to write
		# space-separated words, so they are not treated specially and handled
		# like the all of the other languages.
		if (
		    (cp >= 0X4_e00 and cp <= 0X9_fff)
		    or (cp >= 0X3_400 and cp <= 0X4_dbf)  #
		    or (cp >= 0X20_000 and cp <= 0X2a_6df)  #
		    or (cp >= 0X2a_700 and cp <= 0X2b_73f)  #
		    or (cp >= 0X2b_740 and cp <= 0X2b_81f)  #
		    or (cp >= 0X2b_820 and cp <= 0X2c_eaf)  #
		    or (cp >= 0Xf_900 and cp <= 0Xf_aff)
		    or (cp >= 0X2f_800 and cp <= 0X2f_a1f)  #
		):  #
				return True

		return False







def snake_case__	(      __SCREAMING_SNAKE_CASE			)		->				List[Any]:
		# word like '180' or '身高' or '神'
		for char in word:
				UpperCAmelCase_						       =					ord(A__			)
				if not _is_chinese_char(A__			):
						return 0
		return 1







def snake_case__	(      __SCREAMING_SNAKE_CASE			)		->				int:
		UpperCAmelCase_						       =					set()

		for token in tokens:
				UpperCAmelCase_						       =					len(A__			) > 1 and is_chinese(A__			)
				if chinese_word:
						word_set.add(A__			)
		UpperCAmelCase_						       =					list(A__			)
		return word_list







def snake_case__	(      __SCREAMING_SNAKE_CASE      ,  __SCREAMING_SNAKE_CASE			)		->				Optional[Any]:
		if not chinese_word_set:
				return bert_tokens
		UpperCAmelCase_						       =					max([len(A__			) for w in chinese_word_set]			)

		UpperCAmelCase_						       =					bert_tokens
		UpperCAmelCase_       ,    UpperCAmelCase_						       =					0, len(A__			)
		while start < end:
				UpperCAmelCase_						       =					True
				if is_chinese(bert_word[start]			):
						UpperCAmelCase_						       =					min(end - start      ,  A__			)
						for i in range(A__      ,  1      ,  -1			):
								UpperCAmelCase_						       =					"".join(bert_word[start : start + i]			)
								if whole_word in chinese_word_set:
										for j in range(start + 1      ,  start + i			):
												UpperCAmelCase_						       =					"##" + bert_word[j]
										UpperCAmelCase_						       =					start + i
										UpperCAmelCase_						       =					False
										break
				if single_word:
						start += 1
		return bert_word







def snake_case__	(      __SCREAMING_SNAKE_CASE      ,  __SCREAMING_SNAKE_CASE      ,  __SCREAMING_SNAKE_CASE			)		->				List[Any]:
		UpperCAmelCase_						       =					[]

		for i in range(0      ,  len(A__			)      ,  100			):
				UpperCAmelCase_						       =					ltp_tokenizer.seg(lines[i : i + 100]			)[0]
				UpperCAmelCase_						       =					[get_chinese_word(A__			) for r in res]
				ltp_res.extend(A__			)
		assert len(A__			) == len(A__			)

		UpperCAmelCase_						       =					[]
		for i in range(0      ,  len(A__			)      ,  100			):
				UpperCAmelCase_						       =					bert_tokenizer(lines[i : i + 100]      ,  add_special_tokens=A__      ,  truncation=A__      ,  max_length=512			)
				bert_res.extend(res["input_ids"]			)
		assert len(A__			) == len(A__			)

		UpperCAmelCase_						       =					[]
		for input_ids, chinese_word in zip(A__      ,  A__			):
				UpperCAmelCase_						       =					[]
				for id in input_ids:
						UpperCAmelCase_						       =					bert_tokenizer._convert_id_to_token(A__			)
						input_tokens.append(A__			)
				UpperCAmelCase_						       =					add_sub_symbol(A__      ,  A__			)
				UpperCAmelCase_						       =					[]
				# We only save pos of chinese subwords start with ##, which mean is part of a whole word.
				for i, token in enumerate(A__			):
						if token[:2] == "##":
								UpperCAmelCase_						       =					token[2:]
								# save chinese tokens' pos
								if len(A__			) == 1 and _is_chinese_char(ord(A__			)			):
										ref_id.append(A__			)
				ref_ids.append(A__			)

		assert len(A__			) == len(A__			)

		return ref_ids







def snake_case__	(      __SCREAMING_SNAKE_CASE			)		->				Dict:
		# For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
		# If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
		with open(args.file_name      ,  "r"      ,  encoding="utf-8"			) as f:
				UpperCAmelCase_						       =					f.readlines()
		UpperCAmelCase_						       =					[line.strip() for line in data if len(A__			) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
		UpperCAmelCase_						       =					LTP(args.ltp			)  # faster in GPU device
		UpperCAmelCase_						       =					BertTokenizer.from_pretrained(args.bert			)

		UpperCAmelCase_						       =					prepare_ref(A__      ,  A__      ,  A__			)

		with open(args.save_path      ,  "w"      ,  encoding="utf-8"			) as f:
				UpperCAmelCase_						       =					[json.dumps(A__			) + "\n" for ref in ref_ids]
				f.writelines(A__			)


if __name__ == "__main__":
			SCREAMING_SNAKE_CASE  					=    argparse.ArgumentParser(description="prepare_chinese_ref")
			parser.add_argument(
			    "--file_name",
			    type=str,
			    default="./resources/chinese-demo.txt",
			    help="file need process, same as training data in lm",
			)
			parser.add_argument(
			    "--ltp", type=str, default="./resources/ltp", help="resources for LTP tokenizer, usually a path"
			)
			parser.add_argument("--bert", type=str, default="./resources/robert", help="resources for Bert tokenizer")
			parser.add_argument("--save_path", type=str, default="./resources/ref.txt", help="path to save res")

			SCREAMING_SNAKE_CASE  					=    parser.parse_args()
			main(args)




from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

__A			:					List[Any]						=			{'UserAgent': UserAgent().random}





def 	__a     (      A__			:  List[Any]       ):
    SCREAMING_SNAKE_CASE										=   script.contents[0]
    SCREAMING_SNAKE_CASE										=   json.loads(data[data.find("{\"config\""       ) : -1]       )
    return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]





class 			_SCREAMING_SNAKE_CASE :







   '''simple docstring'''




   def __init__(       self					:			List[str]     , __lowerCamelCase					:			Optional[Any]			):
       SCREAMING_SNAKE_CASE										=   f"https://www.instagram.com/{username}/"
       SCREAMING_SNAKE_CASE										=   self.get_json()





   def      _snake_case		(       self					:			Tuple			):
       SCREAMING_SNAKE_CASE										=   requests.get(self.url     , headers=__lowerCamelCase			).text
       SCREAMING_SNAKE_CASE										=   BeautifulSoup(__lowerCamelCase     , "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					:			Union[str, Any]			):
       return f"{self.__class__.__name__}('{self.username}')"





   def __str__(       self					:			str			):
       return f"{self.fullname} ({self.username}) is {self.biography}"





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





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





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





   @property
   def      _snake_case		(       self					:			Tuple			):
       return self.user_data["business_email"]





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





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





   @property
   def      _snake_case		(       self					:			List[str]			):
       return self.user_data["edge_follow"]["count"]





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





   @property
   def      _snake_case		(       self					:			Any			):
       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 	__a     (      A__			:  str = "github"       ):
    import os

    if os.environ.get("CI"       ):
        return  # test failing on GitHub Actions
    SCREAMING_SNAKE_CASE										=   InstagramUser(A__       )
    assert instagram_user.user_data
    assert isinstance(instagram_user.user_data			,  A__       )
    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 > 150
    assert instagram_user.number_of_followers > 120000
    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()
    __A			:					Dict						=			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 = }')