📝 Python Text Summarizer

Extractive Text Summarization with Python & NLTK

An educational Python project that implements Extractive Text Summarization using the Natural Language Toolkit (NLTK).

The application analyzes a text, calculates word frequencies, scores every sentence, and automatically generates a concise summary by selecting the most relevant sentences.

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📚 Project Background

This project was developed as part of a Python course project.

The objective is to implement an extractive text summarization algorithm without using machine learning or AI models.

Instead, the algorithm relies on classical Natural Language Processing (NLP) techniques provided by the NLTK library.

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🚀 Features

• Read text files
• Tokenize text
• Remove punctuation
• Remove English stopwords
• Calculate word frequencies
• Normalize word frequencies
• Split text into sentences
• Calculate sentence scores
• Select the top 20% highest-ranked sentences
• Generate an extractive text summary

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🏗️ Project Structure

PythonProjekt/
│
├── data/
│   └── ClimateScienceText.txt
│
├── src/
│   ├── utils.py
│   ├── tokenizer.py
│   ├── frequency.py
│   ├── summarizer.py
│   └── main.py
│
├── requirements.txt
├── SUMMARY.md
└── README.md

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⚙️ Technologies

• Python 3
• NLTK
• Dictionaries
• Functions
• Modular Programming
• Natural Language Processing (NLP)

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📋 Workflow

Read Text
      │
      ▼
Tokenization
      │
      ▼
Remove Stopwords
      │
      ▼
Calculate Word Frequencies
      │
      ▼
Normalize Frequencies
      │
      ▼
Split into Sentences
      │
      ▼
Calculate Sentence Scores
      │
      ▼
Select Top 20%
      │
      ▼
Generate Summary

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▶️ Installation

Clone the repository

git clone https://github.com/fdeniz07/PythonProjekt.git

Open the project

cd PythonProjekt

Create a virtual environment

Windows

python -m venv .venv
.venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

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▶️ Run

python src/main.py

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📄 Example Output

================================================================================
SUMMARY
================================================================================

Climate science is a vast and multifaceted discipline...

Understanding the drivers of climate change...

Renewable energy technologies...

Climate science informs urban planning...

Climate science is a vital and indispensable field...

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🎯 Learning Objectives

This project demonstrates:

• Text preprocessing
• Tokenization
• Stopword removal
• Dictionary usage
• Frequency analysis
• Sentence scoring
• Extractive summarization
• Modular software design
• Clean code principles

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📖 Documentation

Additional documentation is available in:

• SUMMARY.md

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🔮 Possible Improvements

• Support for multiple languages
• PDF document summarization
• Graphical user interface (Tkinter or PySide)
• Adjustable summary percentage
• Command-line arguments
• Export summary to TXT or PDF
• Web API with FastAPI
• Web application with Flask

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👨‍💻 Author

Fatih Deniz

Software Developer

GitHub: https://github.com/fdeniz07

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📜 License

This project was created for educational purposes.