txt2phrases 1.0.3

A comprehensive library for text processing, keyword extraction, and classification from PDF and HTML documents

txt2phrases

txt2phrases is a Python library and CLI tool designed for processing and analyzing text data.
It provides a streamlined pipeline for converting documents (HTML, PDF) into plain text, extracting keywords using AI models, and classifying keywords into specific and general categories using TF-IDF.

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✨ Features

1. PDF to Text Conversion

• Extract plain text from PDF files for further processing.

2. HTML to Text Conversion

• Convert HTML documents into clean, plain text.

3. AI-Powered Keyword Extraction

• Use advanced NLP models (e.g., Hugging Face Transformers) to extract and rank the most important keywords from text files.

4. Automated Pipeline

• Run the entire pipeline (PDF/HTML → TXT → Keywords) with a single command.

5. Batch Processing

• Process single files or entire directories efficiently.

6. Configurable Parameters

• Customize thresholds, batch sizes, and output formats to suit your needs.

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🧩 Installation

Install txt2phrases directly from PyPI:

pip install txt2phrases

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🚀 Quick Start

# Convert PDF to text
txt2phrases pdf2txt -i document.pdf -o output_folder

# Convert HTML to text
txt2phrases html2txt -i webpage.html -o output_folder

# Extract keywords from text files
txt2phrases keyphrases -i text_files/ -o keywords/ -n 500

# Run complete pipeline
txt2phrases auto -i pygetpapers_output/ -o results/ -n 100

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🐍 Python API

from txt2phrases import (
    convert_pdf_to_text,
    convert_html_to_text, 
    KeywordExtraction,
    classify_keywords_split_files
)

# Convert PDF to text
txt_path = convert_pdf_to_text("document.pdf", "output_folder")

# Extract keywords
extractor = KeywordExtraction(
    input_path="text_files/",
    output_folder="keywords/",
    top_n=1000
)
extractor.extract()

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🧠 CLI Commands

📄 pdf2txt

Convert PDF files to text format.

txt2phrases pdf2txt -i input.pdf -o output_folder
txt2phrases pdf2txt -i pdfs_directory/ -o text_output/

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🌐 html2txt

Convert HTML files to clean text format.

txt2phrases html2txt -i webpage.html -o output_folder
txt2phrases html2txt -i html_directory/ -o text_output/

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🔑 keyphrases

Extract keyphrases from text files using advanced NLP models.

txt2phrases keyphrases -i text.txt -o keywords/ -n 500
txt2phrases keyphrases -i text_directory/ -o keywords/ -n 1000

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⚙️ auto

Complete processing pipeline for PyGetPapers output or PDF directories.

txt2phrases auto -i pygetpapers_output/ -o results/ -n 200
txt2phrases auto -i pdf_collection/ -o results/ -n 100

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🔍 Advanced Features

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2. Complete Research Pipeline

# Download papers with PyGetPapers
pygetpapers -q "machine learning" -o papers/ -k 100

# Process and analyze  
txt2phrases auto -i papers/ -o analysis/ -n 200

# Classify results
python -c "
from txt2phrases import classify_keywords_split_files
classify_keywords_split_files('analysis/', 'classified/', threshold=0.7)
"

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📦 Output Formats

• Text Conversion: .txt files with extracted text
• Keyword Extraction: .csv files containing keyword and count columns

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🧱 Requirements

To use txt2phrases, ensure you have the following installed:

• Python 3.8+
• Dependencies:
  • argparse: For CLI argument parsing
  • beautifulsoup4: For HTML parsing
  • pandas: For data manipulation and CSV export
  • tqdm: For progress bars during batch processing
  • transformers: For AI-powered keyword extraction
  • scikit-learn: For TF-IDF-based keyword classification
  • torch: For running NLP models

Install dependencies with:

pip install -r requirements.txt

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📚 Documentation

For full documentation and examples, visit the GitHub repository.

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📄 License

This project is licensed under the MIT License — see the LICENSE file for details.