text-to-nlp 0.1.1

A simple text preprocessing package for NLP

Text to NLP

A simple and efficient Python package for text preprocessing in Natural Language Processing (NLP).

Features

• Tokenizes text into words.
• Removes stop words (e.g., "the", "is").
• Lemmatizes words to their base form (e.g., "running" → "run").
• Removes punctuation marks (e.g., "!", ".", ",").
• Converts text to TF-IDF vectors for machine learning.

Requirements

• Python 3.6+
• nltk>=3.8.1
• scikit-learn>=1.3.0

Installation

pip install text-to-nlp

## Usage
```python
from text_preprocessor import TextPreprocessor

# Initialize the preprocessor
processor = TextPreprocessor()

# Preprocess a single text
text = "I am running and jumping happily!!!"
processed_text = processor.preprocess(text)
print("Processed text:", processed_text)  # Output: running jumping happily

# Convert multiple texts to TF-IDF
texts = ["I am running happily!", "Jumping is fun?", "Sad days are bad."]
tfidf_matrix, vectorizer = processor.to_tfidf(texts)
print("TF-IDF matrix shape:", tfidf_matrix.toarray().shape)  # Output: (3, 1000)