Metadata-Version: 2.1
Name: dutch-text-analytics
Version: 0.1.2
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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# 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 [demos](https://github.com/allmin/dutch_text_analytics/tree/main/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 [demos](https://github.com/allmin/dutch_text_analytics/tree/main/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!

