Gutenberg Scribe is a project designed to work with Project Gutenberg public-domain texts for analysis, processing, and digital humanities research.
The project demonstrates how to download, process, and analyze literary texts from the Gutenberg corpus using Python-based tools.
This repository can be used for experimenting with natural language processing (NLP), text mining, and book data analysis.
- Download and process public-domain books
- Text preprocessing and cleaning
- Extract metadata such as author, title, and language
- Perform text analysis on classic literature
- Generate datasets for NLP experiments
Programming Language
- Python
Libraries
- Pandas
- NumPy
- NLTK / spaCy (for text processing)
- Requests
Tools
- Jupyter Notebook
- Python scripts
Gutenberg-scribe-main
│
├── data/
│ └── Gutenberg text files
│
├── notebooks/
│ └── analysis notebooks
│
├── scripts/
│ └── text processing scripts
│
├── requirements.txt
└── README.md
(Structure may vary depending on implementation.)
git clone https://github.com/N-y-c-t-o/Gutenberg-scribe-main.git
cd Gutenberg-scribe-main
python3 -m venv venv
Linux / macOS
source venv/bin/activate
Windows
venv\Scripts\activate
pip install -r requirements.txt
Run the main analysis script:
run the frontend with:
-
npm i -
npm run dev
run the backend with:
uvicorn app:app --reload
or open the Jupyter notebook for interactive analysis.
This project can be used for:
- Literary text analysis
- Word frequency analysis
- Sentiment analysis on novels
- NLP training datasets
- Digital humanities research
This project demonstrates:
- Text data preprocessing
- Natural language processing techniques
- Working with large text datasets
- Python-based data analysis workflows
Possible improvements include:
- Interactive text visualization dashboard
- Machine learning models for genre classification
- Named entity recognition for book characters
- Web interface for searching books
Developed by N-y-c-t-o
This project is open-source and intended for educational and research purposes.