messageanalyzer.sentiment_analysis
==================================

.. py:module:: messageanalyzer.sentiment_analysis


Functions
---------

.. autoapisummary::

   messageanalyzer.sentiment_analysis.analyze_sentiment


Module Contents
---------------

.. py:function:: analyze_sentiment(messages: List[str], model: str = 'Default') -> List[Dict[str, Union[str, float, bool]]]

   This function analyzes the sentiment of a list of given messages
   and returns the sentiment scores and labels for each messange and prints alert message if it's highly negative.

   :param messages: The messages to analyze.
   :type messages: List[str]
   :param model: The model to use for sentiment analysis. The "Default" model is TextBlob.
   :type model: str, optional

   :returns: A list of dictionaries, where each dictionary contains:
             - "messages": The original message.
             - "score": The sentiment polarity score.
             - "label": The sentiment category ("positive", "negative", "neutral").
             - "alert" (optional): True if the message is highly negative.
             Alert will be printed if some messages are highly negative, and these messages will be displayed.
   :rtype: List[Dict[str, Union[str, float, bool]]]

   :raises TypeError: If `messages` is not a list of strings.
   :raises ValueError: If an unrecognized sentiment analysis model is provided.

   .. rubric:: Example

   >>> messages = ["I love this!", "This is terrible."]
   >>> analyze_sentiment(messages, "Default")
   [{'message': 'I love this!', 'score': 0.5, 'label': 'positive'},
    {'message': 'This is terrible.', 'score': -1.0, 'label': 'negative', 'alert': True}]