txt2phrases 0.1.0

A Python library for HTML to TXT conversion, keyword extraction, and TF-IDF-based per-chapter classification.

## txt2phrases

A Python library for:

1. **HTML to TXT conversion**  
2. **Keyword extraction using Hugging Face Transformers**  
3. **Per-chapter TF-IDF-based specific keyword classification**

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## Installation

You can install `txt2phrases` directly from PyPI:

```bash
pip install txt2phrases

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CLI Usage

Convert HTML → TXT

Convert all HTML files in a folder to plain text:

html2text -i path/to/html_folder -o path/to/output_folder

• -i / --input : Path to the folder containing HTML files
• -o / --output : Path to the folder where TXT files will be saved

Extract keywords from TXT files

Extract top keywords from all TXT files in a folder:

extract_keywords -i path/to/txt_folder -o path/to/output_folder -n 3500

• -i / --input_folder : Folder containing TXT files
• -o / --output_folder : Folder to save keyword CSVs
• -n / --top_n : Number of top keywords to extract (default: 3500)

Generate per-chapter specific keywords (TF-IDF)

Create per-chapter CSVs listing keywords specific to each chapter:

specific_keywords -i path/to/csv_folder -o path/to/output_folder -t 0.6 -f 5

• -i / --input_dir : Folder with per-chapter CSV files containing keyword,count
• -o / --output_dir : Folder to save per-chapter specific keyword CSVs
• -t / --threshold : TF-IDF threshold for a keyword to be considered specific (default: 0.6)
• -f / --min_freq : Minimum frequency of a keyword to consider (default: 5)

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Python Usage

Convert HTML → TXT

from txt2phrases.html2text import html_to_txt_folder

html_to_txt_folder("path/to/html_folder", "path/to/output_folder")

Extract Keywords

from txt2phrases.keyword import KeywordExtraction

extractor = KeywordExtraction(
    textfile="path/to/file.txt",
    saving_path="path/to/output_folder",
    output_filename="keywords.csv",
    top_n=1000
)

top_keywords = extractor.extract_keywords()

Per-Chapter Specific Keywords

from txt2phrases.classify_specific import classify_keywords_split_files

classify_keywords_split_files(
    input_dir="path/to/chapter_csv_folder",
    output_dir="path/to/output_folder",
    threshold=0.6,
    min_freq=5
)

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Requirements

• Python 3.8+
• beautifulsoup4
• pandas
• tqdm
• transformers
• scikit-learn

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