"""simple docstring"""


import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  # 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_e_0_0 and cp <= 0x9_f_f_f)
      or (cp >= 0x3_4_0_0 and cp <= 0x4_d_b_f)  #
      or (cp >= 0x2_0_0_0_0 and cp <= 0x2_a_6_d_f)  #
      or (cp >= 0x2_a_7_0_0 and cp <= 0x2_b_7_3_f)  #
      or (cp >= 0x2_b_7_4_0 and cp <= 0x2_b_8_1_f)  #
      or (cp >= 0x2_b_8_2_0 and cp <= 0x2_c_e_a_f)  #
      or (cp >= 0xf_9_0_0 and cp <= 0xf_a_f_f)
      or (cp >= 0x2_f_8_0_0 and cp <= 0x2_f_a_1_f)  #
  ):  #
    return True

  return False






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  # word like '180' or '身高' or '神'
  for char in word:
    _UpperCAmelCase         =					ord(lowercase						)
    if not _is_chinese_char(lowercase						):
      return 0
  return 1






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					set()

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






def 			__UpperCAmelCase    (	lowercase      ,lowercase						):







  """simple docstring"""
  if not chinese_word_set:
    return bert_tokens
  _UpperCAmelCase         =					max([len(lowercase						) for w in chinese_word_set]						)

  _UpperCAmelCase         =					bert_tokens
  _UpperCAmelCase       , _UpperCAmelCase         =					0, len(lowercase						)
  while start < end:
    _UpperCAmelCase         =					True
    if is_chinese(bert_word[start]						):
      _UpperCAmelCase         =					min(end - start      ,lowercase						)
      for i in range(lowercase      ,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 			__UpperCAmelCase    (	lowercase      ,lowercase      ,lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					[]

  for i in range(0      ,len(lowercase						)      ,1_00						):
    _UpperCAmelCase         =					ltp_tokenizer.seg(lines[i : i + 1_00]						)[0]
    _UpperCAmelCase         =					[get_chinese_word(lowercase						) for r in res]
    ltp_res.extend(lowercase						)
  assert len(lowercase						) == len(lowercase						)

  _UpperCAmelCase         =					[]
  for i in range(0      ,len(lowercase						)      ,1_00						):
    _UpperCAmelCase         =					bert_tokenizer(lines[i : i + 1_00]      ,add_special_tokens=lowercase      ,truncation=lowercase      ,max_length=5_12						)
    bert_res.extend(res["""input_ids"""]						)
  assert len(lowercase						) == len(lowercase						)

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

  assert len(lowercase						) == len(lowercase						)

  return ref_ids






def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  # 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(lowercase						) > 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(lowercase      ,lowercase      ,lowercase						)

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


if __name__ == "__main__":
    UpperCAmelCase__     						=  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""")

    UpperCAmelCase__     						=  parser.parse_args()
    main(args)

"""simple docstring"""


import requests

UpperCAmelCase__     						=  """"""  # <-- Put your OpenWeatherMap appid here!
UpperCAmelCase__     						=  """https://api.openweathermap.org/data/2.5/"""






def 			__UpperCAmelCase    (	lowercase = "Chicago"      ,lowercase = APPID						):







  """simple docstring"""
  return requests.get(URL_BASE + """weather"""      ,params=locals()						).json()






def 			__UpperCAmelCase    (	lowercase = "Kolkata, India"      ,lowercase = APPID						):







  """simple docstring"""
  return requests.get(URL_BASE + """forecast"""      ,params=locals()						).json()






def 			__UpperCAmelCase    (	lowercase = 55.68      ,lowercase = 12.57      ,lowercase = APPID						):







  """simple docstring"""
  return requests.get(URL_BASE + """onecall"""      ,params=locals()						).json()


if __name__ == "__main__":
    from pprint import pprint

    while True:
        UpperCAmelCase__     						=  input("""Enter a location:""").strip()
        if location:
            pprint(current_weather(location))
        else:
            break
