How to use _save_to_json method in avocado

Best Python code snippet using avocado_python

troll_api.py

Source:troll_api.py Github

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...21 self._key_api = key_api22 self._url_to_server = url_to_server23 self._treshold = treshold24 25 def _save_to_json(self, response, path_to_save):26 """Сохранение данных полученного ответа в файл27 Args:28 response (dict): сохраняемые данные29 path_to_save (str): путь до сохраняемого файла30 """31 with open(path_to_save, "w", encoding="utf-8") as write_file:32 json.dump(response, write_file, indent=2, ensure_ascii=False)33 def set_treshold(self, treshold):34 """Метод для задания порога отсечения троллинга, при автоматической модерации35 Args:36 treshold (float): порога отсечения троллинга37 """38 self._treshold = treshold39 def get_count_available_requests(self,40 save_to_json=False, 41 path_to_save="available_requests_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")),42 timeout=300):43 """Метод для определения доступного количества запросов пользователя44 Args:45 save_to_json (bool): сохранение полученной информации в файл. Defaults to False.46 path_to_save (str): путь до сохраняемого файла. Defaults to "available_requests_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")).47 timeout (int): максимальное время ожидания ответа от сервера, сек. Defaults to 300.48 Returns:49 dict: параметры доступных запросов для пользователя50 """51 answer = requests.post(52 self._url_to_server + "/get_query_left", 53 data=json.dumps({"key_api":self._key_api}), 54 headers=self._headers,55 )56 response = answer.json()57 if save_to_json: self._save_to_json(response, path_to_save)58 return response59 60 def get_available_type_parsers(self,61 save_to_json=False, 62 path_to_save="available_parsers_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")),63 timeout=300):64 """Метод для определения доступного количества запросов пользователя65 Args:66 save_to_json (bool): сохранение полученной информации в файл. Defaults to False.67 path_to_save (str): путь до сохраняемого файла. Defaults to "available_parsers_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")).68 timeout (int): максимальное время ожидания ответа от сервера, сек. Defaults to 300.69 Returns:70 dict: параметры доступных типов парсеров для порталов71 """72 answer = requests.post(73 self._url_to_server + "/get_available_parsers", 74 data=json.dumps({"key_api":self._key_api}),75 headers=self._headers,76 )77 response = answer.json()78 if save_to_json: self._save_to_json(response, path_to_save)79 return response80 def get_proba(self, 81 question,82 answer, 83 save_to_json=False, 84 path_to_save="request_proba_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")),85 timeout=300):86 """Формирование запроса на сервер и получение данных о вероятности троллинга при ответе на вопрос87 Args:88 question (str, list): [description]89 answer (str, list): [description]90 save_to_json (bool): сохранение полученной информации в файл. Defaults to False.91 path_to_save (str): путь до сохраняемого файла. Defaults to "request_proba_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")).92 timeout (int): максимальное время ожидания ответа от сервера, сек. Defaults to 300.93 Returns:94 dict: данные о вероятности троллинга при ответе на вопрос95 """96 answer = requests.post(97 self._url_to_server + "/get_proba", 98 data=json.dumps({99 "question":question,100 "answer":answer,101 "treshold":self._treshold,102 "key_api":self._key_api103 }), 104 headers=self._headers,105 timeout=timeout106 )107 response = answer.json()108 if save_to_json: self._save_to_json(response, path_to_save)109 return response110 def get_proba_from_link(self, 111 link,112 type_parser="answers_mail.ru", 113 save_to_json=False, 114 path_to_save="request_proba_from_link_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")),115 timeout=300):116 """Формирование запроса на сервер и получение данных о вероятности троллинга при ответе на вопрос по сслыке на пост портала117 Args:118 link ([type]): ссылка на пост портала119 type_parser (str): выбор типа парсера для извлечения данных с поста портала. Defaults to "answers_mail.ru".120 save_to_json (bool): сохранение полученной информации в файл. Defaults to False.121 path_to_save (str): путь до сохраняемого файла. Defaults to "request_proba_from_link_{}.json".format(datetime.today().strftime("%Y-%m-%d_%H.%M.%S")).122 timeout (int): максимальное время ожидания ответа от сервера, сек. Defaults to 300.123 Returns:124 dict: данные о вероятности троллинга при ответе на вопрос125 """126 answer = requests.post(127 self._url_to_server + "/get_link", 128 data=json.dumps({129 "link":link,130 "parser":type_parser,131 "treshold":self._treshold,132 "key_api":self._key_api133 }), 134 headers=self._headers,135 timeout=timeout136 )137 response = answer.json()138 if save_to_json: self._save_to_json(response, path_to_save)139 return response140if __name__ == "__main__":141 api = FindTrollApi(key_api="qwerty")142 N = 7143 question = ["questionquestion"] * N144 answer = "answer"145 link = "1234567"146 t1 = time()147 data_ = api.get_proba(question, answer, save_to_json=True)148 print(time()-t1)149 """150 data1 = {151 "question":["questionquestion"]*N,152 "answer":"answer",...

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test_main.py

Source:test_main.py Github

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...128 with open(filename, "r") as json_data:129 data = json.load(json_data)130 return data131 @staticmethod132 def _save_to_json(filename, data) -> bool:133 with open(filename, "w") as json_file:134 json.dump(data, json_file, indent=2)135 return True136 def _return_accuracy_from_test(self) -> float:137 vocab_filename = "vocabulary.json"138 vocab = VocabularyCreator(self.train, vocab_filename)139 vocab.create_vocab()140 renege = RENEGE(self.train)141 if not renege.classify_emails():142 raise RuntimeError("Error classify emails")143 evaluation = evaluate(self.test)144 return evaluation["accuracy"]145 def get_accuracy_delta(self):146 return abs(self.initial_acc - self.new_acc)147 @staticmethod148 def _shuffle_email_words(email):149 for mail in email:150 split_table = mail["mail"]["Body"].split()151 random.shuffle(split_table)152 mail["mail"]["Body"] = ' '.join(split_table)153 return email154 @staticmethod155 def _add_noise(email):156 #TODO157 pass158 def test1(self):159 trainset = self._load_json("train_set.json")["dataset"]160 random.shuffle(trainset)161 self.train = "train700_mails.json"162 self._save_to_json(filename=self.train, data={"dataset": trainset})163 self.new_acc = self._return_accuracy_from_test()164 self.assertLessEqual(165 self.get_accuracy_delta(),166 self.THRESHOLD,167 "Le changement d'ordre des emails modifie l'accuracy de beaucoup.",168 )169 def test2(self):170 test_set = self._load_json("test_set.json")["dataset"]171 random.shuffle(test_set)172 self.test = "test300_mails.json"173 self._save_to_json(self.test, {"dataset": test_set})174 self.new_acc = self._return_accuracy_from_test()175 self.assertLessEqual(176 self.get_accuracy_delta(),177 self.THRESHOLD,178 "Le changement d'ordre des emails dans le testset modifie modifie l'accuracy de beaucoup.",179 )180 def test3(self):181 #Changement d'orde des mots dans train dataset182 test_set = self._load_json("train_set.json")["dataset"]183 shuffled_emails_words = self._shuffle_email_words(test_set)184 self.train = "train700_words.json"185 self._save_to_json(self.train, {"dataset": shuffled_emails_words})186 self.new_acc = self._return_accuracy_from_test()187 self.assertLessEqual(188 self.get_accuracy_delta(),189 self.THRESHOLD,190 )191 def test4(self):192 test_set = self._load_json("test_set.json")["dataset"]193 shuffled_emails_words = self._shuffle_email_words(test_set)194 self.test = "test300_words.json"195 self._save_to_json(self.test, {"dataset": shuffled_emails_words})196 self.new_acc = self._return_accuracy_from_test()197 self.assertLessEqual(198 self.get_accuracy_delta(),199 self.THRESHOLD,200 "Le changement d'ordre des mots dans le 'test dataset' modifie l'accuracy de beaucoup.",201 )202 def test5(self):203 #Ajout des memes email dans train dataset204 self.train = "train700x2.json"205 self.new_acc = self._return_accuracy_from_test()206 self.assertLessEqual(207 self.get_accuracy_delta(),208 self.THRESHOLD,209 )210 def test6(self):211 #Ajout des memes email dans test dataset212 self.test = "test300x2.json"213 self.new_acc = self._return_accuracy_from_test()214 self.assertLessEqual(215 self.get_accuracy_delta(),216 self.THRESHOLD,217 )218 def test7(self):219 #Bruit dans train dataset220 test_set = self._load_json("train_set.json")["dataset"]221 noised_emails_words = self._add_noise(test_set)222 self.train = "train700_noise.json"223 self._save_to_json(self.train, {"dataset": noised_emails_words})224 self.new_acc = self._return_accuracy_from_test()225 self.assertLessEqual(226 self.get_accuracy_delta(),227 self.THRESHOLD,228 )229 def test8(self):230 #Bruit dans test dataset231 test_set = self._load_json("test_set.json")["dataset"]232 noised_emails_words = self._add_noise(test_set)233 self.test = "test300_noise.json"234 self._save_to_json(self.test, {"dataset": noised_emails_words})235 self.new_acc = self._return_accuracy_from_test()236 self.assertLessEqual(237 self.get_accuracy_delta(),238 self.THRESHOLD,...

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main.py

Source:main.py Github

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...54 logger.info("get all public channels.")55 channels = get_all_public_channels()56 channel_path = base_path / "channel_master.json"57 logger.info(f"save all public channels. path: {channel_path}")58 _save_to_json(channels, channel_path)59 return channels60def _get_users(base_path: Path) -> List[Dict[str, Any]]:61 """62 全てのユーザ情報を取得63 Parameters64 ----------65 base_path : Path66 出力先のBaseとなるPath67 Returns68 -------69 List[Dict[str, Any]]70 全てのユーザ情報71 """72 logger.info("get all users.")73 users = get_all_users()74 users_path = base_path / "user_master.json"75 logger.info(f"save all users. path: {users_path}")76 _save_to_json(users, users_path)77 return users78def _get_channel_message(base_path: Path, channel_id: str, channel_name: str) -> None:79 """80 チャンネル情報を取得81 NOTE: 全てメモリに乗せるためメモリ不足に注意82 Parameters83 ----------84 base_path : Path85 出力先のBaseとなるPath86 channel_id : str87 チャンネルID88 channel_name : str89 チャンネル名90 """91 channel_info = f"id:{channel_id}, name: {channel_name}"92 logger.info(f"get channel_message. {channel_info}")93 messages = get_channel_message(channel_id)94 messages_path = base_path / channel_id95 messages_path.mkdir()96 channel_message_path = messages_path / "nomal_messages.json"97 logger.info(f"save channel message. {channel_info}, path: {channel_message_path}")98 _save_to_json(messages, channel_message_path) # type: ignore99 logger.info(f"get replies_message. {channel_info}")100 for message in messages:101 _get_replies(messages_path, message, channel_id, channel_info)102def _get_replies(103 base_path: Path, message: Dict[str, Any], channel_id: str, channel_info: str104) -> None:105 """106 リプライメッセージを取得107 Parameters108 ----------109 base_path : Path110 出力先のBaseとなるPath111 message : Dict[str, Any]112 メッセージ情報113 channel_id : str114 チャンネルID115 channel_info : str116 チャンネル情報117 """118 replies = get_replies(channel_id, message)119 if replies:120 # NOTE: '1638883139.000600' のように「.」が入るとファイル名として不適格なので「_」に置換121 thread_ts = message["thread_ts"].replace(".", "_")122 replies_path = base_path / f"{thread_ts}.json"123 logger.info(f"save replies message. {channel_info}, path: {replies_path}")124 _save_to_json(replies, replies_path) # type: ignore125def _save_to_json(data: Any, path: Path) -> Path:126 """127 json形式で保存する128 Parameters129 ----------130 data : Any131 保存対象のデータ132 path : Path133 保存先134 Returns135 -------136 Path137 保存されたPath138 """139 with open(path, "w") as f:...

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