DarkmatterVale/regex4dummies

from dependency import Dependency
from tokenizer import Tokenizer
from phrase_extractor import PhraseExtractor
from string_compare import CompareStrings

"""
The toolkit class manages all NLP related functions of regex4dummies.
This allows regex4dummies to be separate from the toolkit, but in
the same library.

Class information:
- name: toolkit
- version: 1.4.4
- author: Vale Tolpegin
"""


class Toolkit:
    def __init__(self, *args, **kwargs):
        """
        Constructor method.
        """

        self.extractor = PhraseExtractor()

    def extract_noun_phrases(self, **kwargs):
        """
        Extracts the noun phrases out of a passed
        text.
        """

        # Getting noun phrases & returning them
        return self.extractor.extract_noun_phrases(text=kwargs.get("text"), parser=kwargs.get("parser"))

    def extract_verb_phrases(self, **kwargs):
        """
        Extracts the verb phrases out of a passed
        text.
        """

        # Getting verb phrases & returning them
        return self.extractor.extract_verb_phrases(text=kwargs.get("text"), parser=kwargs.get("parser"))

    def extract_prepositional_phrases(self, **kwargs):
        """
        Extracts the prepositional phrases out of a
        passed text.
        """

        # Getting the prepositional phrases & returning them
        return self.extractor.extract_prepositional_phrases(text=kwargs.get("text"), parser=kwargs.get("parser"))

    def tokenize(self, **kwargs):
        """
        Returns the tokenized string using a parser.
        """

        string_tokenizer = Tokenizer()

        return string_tokenizer.tokenize(kwargs.get("text"), kwargs.get("parser"))

    def find_dependencies(self, **kwargs):
        """
        Returns the string with dependencies identified
        using the given parser.
        """

        dependency_finder = Dependency()

        return dependency_finder.find_dependencies(text=kwargs.get("text"), parser=kwargs.get("parser"), response_type=kwargs.get("response_type"))

    def compare_strings(self, **kwargs):
        """
        Returns the numerical value of the similarity between
        two input strings.
        """

        string_comparer = CompareStrings()

        return string_comparer.process(kwargs.get("String1"), kwargs.get("String2"))