






import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class 					a_(						UpperCAmelCase__	,    unittest.TestCase					):



     """simple docstring"""



     __snake_case						:							Any       			=BertweetTokenizer
     __snake_case						:							Optional[Any]       			=False





     def   __UpperCamelCase		(						self			:					Union[str, Any])    ->					Any:

      """simple docstring"""
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      SCREAMING_SNAKE_CASE							  =						["""I""", """m""", """V@@""", """R@@""", """r""", """e@@"""]
      SCREAMING_SNAKE_CASE							  =						dict(zip(lowerCAmelCase__       ,       range(len(lowerCAmelCase__))))
      SCREAMING_SNAKE_CASE							  =						["""#version: 0.2""", """a m</w>"""]
      SCREAMING_SNAKE_CASE							  =						{"""unk_token""": """<unk>"""}

      SCREAMING_SNAKE_CASE							  =						os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['vocab_file'])
      SCREAMING_SNAKE_CASE							  =						os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['merges_file'])
      with open(self.vocab_file       ,       'w'       ,       encoding='utf-8') as fp:
       for token in vocab_tokens:
        fp.write(f'''{token} {vocab_tokens[token]}\n''')
      with open(self.merges_file       ,       'w'       ,       encoding='utf-8') as fp:
       fp.write('\n'.join(lowerCAmelCase__))





     def   __UpperCamelCase		(						self			:					Dict       ,       **lowerCAmelCase__			:					List[Any])    ->					str:

      """simple docstring"""
      kwargs.update(self.special_tokens_map)
      return BertweetTokenizer.from_pretrained(self.tmpdirname       ,       **lowerCAmelCase__)





     def   __UpperCamelCase		(						self			:					str       ,       lowerCAmelCase__			:					Optional[Any])    ->					str:

      """simple docstring"""
      SCREAMING_SNAKE_CASE							  =						"""I am VinAI Research"""
      SCREAMING_SNAKE_CASE							  =						"""I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
      return input_text, output_text





     def   __UpperCamelCase		(						self			:					Optional[Any])    ->					str:

      """simple docstring"""
      SCREAMING_SNAKE_CASE							  =						BertweetTokenizer(self.vocab_file       ,       self.merges_file       ,       **self.special_tokens_map)
      SCREAMING_SNAKE_CASE							  =						"""I am VinAI Research"""
      SCREAMING_SNAKE_CASE							  =						"""I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
      SCREAMING_SNAKE_CASE							  =						tokenizer.tokenize(lowerCAmelCase__)
      self.assertListEqual(lowerCAmelCase__       ,       lowerCAmelCase__)

      SCREAMING_SNAKE_CASE							  =						tokens + [tokenizer.unk_token]

      SCREAMING_SNAKE_CASE							  =						[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__)       ,       lowerCAmelCase__)












from datetime import date

import requests

__UpperCAmelCase      				=							"https://api.carbonintensity.org.uk/intensity"





def 		A_			(		)							->str:







 """simple docstring"""

 SCREAMING_SNAKE_CASE							  =						requests.get(lowercase_	).json()['data'][0]
 return last_half_hour["intensity"]["actual"]





def 		A_			(		lowercase_					,       lowercase_	)							->list:







 """simple docstring"""

 return requests.get(f'''{BASE_URL}/{start}/{end}'''	).json()["data"]


if __name__ == "__main__":
      for entry in fetch_from_to(start=date(2_0_2_0, 1_0, 1), end=date(2_0_2_0, 1_0, 3)):
            print("from {from} to {to}: {intensity[actual]}".format(**entry))
      print(f'{fetch_last_half_hour() = }')




