messageanalyzer.detect_language_patterns
========================================

.. py:module:: messageanalyzer.detect_language_patterns


Functions
---------

.. autoapisummary::

   messageanalyzer.detect_language_patterns.detect_language_patterns


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

.. py:function:: detect_language_patterns(messages: List[str], method: str = 'language', n: int = 2, top_n: int = 5) -> Union[List[str], List[Tuple[str, int]]]

   Detects language patterns in a list of messages.

   :param messages: A list of text messages to analyze.
   :type messages: List[str]
   :param method: The method to use for pattern detection. Supported methods are:
                  - "language": Detects the language of each message.
                  - "ngrams": Extracts common n-grams.
                  - "char_patterns": Analyzes common character patterns.
   :type method: str, default = "language"
   :param n: The 'n' in n-grams, used when method="ngrams".
   :type n: int, default = 2
   :param top_n: The number of top patterns to return.
   :type top_n: int, default = 5

   :returns: A list of detected patterns based on the chosen method:
             - For "language", a list of detected languages (e.g., ['en', 'fr']).
             - For "ngrams", a list of tuples (ngram, frequency).
             - For "char_patterns", a list of tuples (character, frequency).
   :rtype: Union[List[str], List[Tuple[str, int]]]

   :raises TypeError: If messages is not a list of strings.
   :raises ValueError: If method is unsupported.

   .. rubric:: Examples

   >>> messages = ["Hello, how are you?", "Bonjour, comment ça va?", "Hola, ¿cómo estás?"]

   Example 1: Detecting languages
   >>> detect_language_patterns(messages, method="language")
   ['en', 'fr', 'es']  # English, French, Spanish

   Example 2: Extracting common 2-grams
   >>> detect_language_patterns(messages, method="ngrams", n=2, top_n=5)
   [('how are', 1), ('are you', 1), ('comment ça', 1), ('ça va', 1), ('cómo estás', 1)]

   Example 3: Analyzing common character patterns
   >>> detect_language_patterns(messages, method="char_patterns", top_n=5)
   [(' ', 8), ('o', 7), ('e', 6), ('a', 5), ('m', 3)]