Metadata-Version: 2.1
Name: dutch_text_analytics
Version: 0.1.1
Summary: Dutch Text Analytics is a versatile toolkit designed to facilitate the exploration, execution, and validation of a diverse range of Natural Language Processing (NLP) tasks specifically tailored for the Dutch language. This repository provides a comprehensive set of tools, including code examples, scripts, and resources, to enhance and streamline your Dutch NLP projects.
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Description: # Dutch Text Analytics
        Dutch Text Analytics is a versatile toolkit designed to facilitate the exploration, execution, and validation of a diverse range of Natural Language Processing (NLP) tasks specifically tailored for the Dutch language. This repository provides a comprehensive set of tools, including code examples, scripts, and resources, to enhance and streamline your Dutch NLP projects.
        
        ## Getting Started
        
        ### Prerequisites
        
        - Ensure you have Python version 3.8.10 installed on your system.
        
        ### Installation
        
        - To install the *Dutch Text Analytics* package, open a command prompt and run:
        
        ```bash
        pip install dutch_text_analytics
        ```
        ### Usage
        
        - In your Python script or Jupyter Notebook, import the library as follows:
        
        ```python
        import dutch_text_analytics.text_analytics as ta
        ```
        - To access modules and leverage the functionalities provided by the toolkit, instantiate the TextProcessing class:
        
        ```python
        text_processor = ta.TextProcessing()
        ```
        - For detailed usage examples and demonstrations, refer to the demo scripts available in the dutch_text_analytics/demos folder.
        
        ## Modules Overview
        
        ## Text Processing
        
        - The TextProcessing module provides powerful tools for working with Dutch text, including lemmatization, handling separable verbs, and displaying dependency trees.
        
        ```python
        # Example: Instantiate TextProcessing
        text_processor = ta.TextProcessing()
        
        # Example: Lemmatize a sentence
        lemmatized_sentence = text_processor.lemmatize("Your Dutch sentence here.")
        
        # Example: Handle separable verbs in a sentence
        processed_sentence = text_processor.handle_separable_verbs("Your Dutch sentence here.")
        
        # Example: Display dependency tree of a sentence
        text_processor.display_dependency("Your Dutch sentence here.")
        ```
        - Explore the module for additional functionalities to enhance your Dutch text processing workflows.
        
        - Tip: The TextProcessing takes in language argument. For english:
        
        ```python
        # Example: Instantiate TextProcessing
        text_processor = ta.TextProcessing(language='en')
        ```
        
        ## Demos
        
        - Check out the 'dutch_text_analytics/demos' folder for hands-on demonstrations and code examples showcasing the capabilities of Dutch Text Analytics across various NLP tasks.
        
        Feel free to contribute, report issues, or suggest improvements. Happy coding with Dutch Text Analytics!
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