PDF Key Matcher

PDF Key Matcher is an open-source, terminal-based application designed to analyze and compare text from PDF files with a description text file. This tool is especially useful for tailoring CVs to match job descriptions, helping users identify keyword matches and gaps.

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🚀 Features

• PDF Text Extraction: Extract text directly from PDF files (e.g., CVs).
• Description File Support: Load comparison descriptions from plain text files.
• Text Preprocessing: Includes case conversion, special character removal, and stop-word filtering.
• Keyword Matching: Compare PDF content with the description and calculate matching percentages.
• Unmatched Keywords: Identify keywords in the description that are missing from the PDF.
• Terminal-Friendly Output: Visualize results directly in the terminal.
• Clean and Modular Design: Easily extensible and maintainable code structure.

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🛠️ Project Structure

pdf_key_matcher/
├── main.py              # Entry point of the app
├── utils/
│   ├── file_handler.py  # Handles file upload and text extraction
│   ├── text_processor.py # Text cleaning, preprocessing, and tokenization
│   ├── matcher.py       # Performs keyword comparison
│   ├── display.py       # Display outputs in User friendly way
├── data/
│   ├── file.pdf         # Example PDF file (e.g., CV)
│   ├── description.txt  # Example description file (e.g., job description)
├── venv/                # Virtual environment directory
├── .gitignore
├── README.md
├── LICENSE
└── requirements.txt     # Required Python libraries

🧰 Requirements

• Python 3.8 or higher
• Dependencies
  • PyMuPDF (pymupdf) for PDF text extraction.
  • re for text preprocessing and pattern matching.

🖥️ How to Use

1. Clone the Repository

git clone https://github.com/your-username/pdf-key-matcher.git
cd pdf_key_matcher

2. Set Up the Virtual Environment

Activate a virtual environment to keep dependencies isolated:

• For Linux/Mac Users

python -m venv venv
source venv/bin/activate

• For Windows Users

python -m venv venv
venv\Scripts\activate

3. Install Dependencies

Install the required Python libraries:

pip install -r requirements.txt

4. Add Your Files

Place your PDF file (e.g., CV) and the description file (e.g., job description) in the data/ folder:

• Example CV file: data/file.pdf
• Example description: data/description.txt

NOTE : pdf file name should be file.pdf and text file should be description.txt. Using Other names will not work unless you change the code.

5. Run the Application

python main.py

📂 Example Usage

Input:

• PDF File Content:

Python developer with experience in Django, and SQL.

• Description File Content:

Looking for a Python developer skilled in Flask, Django and SQL.

Output:

Match Percentage:
75.00%

Unmatched Keywords:
flask

• Sample output screenshots

🌟 Contribution

Contributions are welcome! To get started:

1. Fork the repository.

2. Create a feature branch:

git checkout -b feature-name

3. Commit your changes:

git commit -m "Add a new feature"

4. Push to your branch:

git push origin feature-name

5. Open a Pull Request.

📜 License

This project is licensed under the MIT License. See the LICENSE file for more details.