semvec/pypi-packages huggingface dataset:
tweetprocessor 1.0.0
This is my text processor that will process text using 10 NLP processing tehcniques for the ML SPECIALIZATION
Requires Python: ==3.12

# TextPreprocessor

## Overview
The TextPreprocessor is a Python class designed for comprehensive text preprocessing. It facilitates tasks like removing links, hashtags, special characters, emojis, numbers, and stopwords. Additionally, it provides functionality for converting text to lowercase.

## Installation
Ensure you have NLTK installed. You can install NLTK via pip:

pip install nltk




## Usage
```python
### Import the TextPreprocessor class
from text_preprocessor import TextPreprocessor
# Initialize the preprocessor with default settings
preprocessor = TextPreprocessor()

# Customize the preprocessor by setting flags
preprocessor = TextPreprocessor(
    remove_links=True,
    remove_hashtags=True,
    remove_characters=True,
    convert_to_lowercase=True,
    remove_emojis=True,
    remove_numbers=True,
    remove_stopwords_flag=True
)



text = "Your text goes here..."


processed_text = preprocessor.preprocess_text(text)

```
## Available Methods
1. preprocess_text(text): Preprocesses the input text based on the initialized flags.
2. Other methods in the class can be used individually for specific preprocessing steps (e.g., remove_links, remove_stopwords, etc.).
# Examples
```python

text = "Hello! This is an example text with #hashtags and links: https://example.com"



# Initialize preprocessor
preprocessor = TextPreprocessor(remove_links=True, remove_hashtags=True)

# Preprocess text
processed_text = preprocessor.preprocess_text(text)
print(processed_text)
Output: "Hello This is an example text with and links"

```

# License

This project is licensed under the MIT License - see the LICENSE file for details.