def process_twitter_data(
status: Status,
twitter_credentials: dict,
add_sentiment: bool = True,
add_bot_analysis: bool = True) -> TwitterDataOutput:
output: TwitterDataOutput = TwitterDataOutput(status={}, user={})
try:
# 1. Retrieve status document
status_doc: StatusDoc = TwitterDataProcessor.process_status(
status=status)
response_sent: SentimentAnalysisOutput = SentimentAnalysisOutput()
# 2. Add additional parameters related to sentiment analysis
if add_sentiment:
if len(status_doc.text) >= TwitterDataProcessor.min_char:
response_sent: SentimentAnalysisOutput = TwitterDataProcessor.process_sentiment_analysis(
doc=status_doc.text)
status_doc.sentiment_analysis: dict = response_sent.__dict__
# 3. Get the user
user: User = status.__getattribute__("user")
user_doc: UserAccountDoc = TwitterDataProcessor.process_user(
user=user)
# 4. Add additional params
if add_bot_analysis:
response_botometer_analysis: BotometerAnalysisOutput = TwitterDataProcessor.process_botometer_analysis(
user_id=user_doc.id,
twitter_credentials=twitter_credentials)
user_doc.botometer_analysis: dict = response_botometer_analysis.__dict__
# 5. Get the output
output: TwitterDataOutput = TwitterDataOutput(
status=status_doc.__dict__, user=user_doc.__dict__)
except Exception as e:
logger.error(e)
return output
def on_status(self, status: Status):
logger.info(f"1. Loading Status with ID {status.__getattribute__('id')}")
# 1. Check whether the status is already in the storage
non_exists: bool = self.check_data_in_storage(
entity_id=status.__getattribute__('id'),
storage=self.storage,
collection_name=self.collection_names.get("status"),
identifier_key="id")
if non_exists:
# 3. Process Tweets an Users
logger.info(f"2. Pre-processing Status with ID {status.__getattribute__('id')}")
data: TwitterDataOutput = self.process_status(
status=status, add_sentiment=self.add_sentiment,
add_bot_analysis=self.add_bot_analysis)
logger.info(f"3. Storing Status with ID {status.__getattribute__('id')} in {self.storage.title()}")
# 2. Storage data
self.storage_data(data=data, collection_names=self.collection_names,
storage=self.storage, mongodb_connector=self.mongodb_connector,
elasticsearch_connector=self.elasticsearch_connector,
identifier_key=self.identifier_key)
