This Python script extracts tables containing specific keywords, such as "Revenue" and "Income," from a collection of PDF files in the specified input directory and saves the extracted tables as Excel files in the specified output directory.
- Extract tables with specific keywords from PDF files
- Parallel processing for faster extraction
- Customizable regex pattern for keyword search
- Error handling and logging for better traceability
- Supports specifying input and output directories
- Python 3.7 or higher
- pdfgrep (system package)
- Clone the repository or download the script:
git clone financial-statement-pdf-extractor.git
Install the Python dependencies using pip:
pip install -r requirements.txt
Install the pdfgrep package using your system's package manager: For Ubuntu:
sudo apt-get install pdfgrep
For macOS:
brew install pdfgrep
Replace input_directory with the path to the directory containing the PDF files you want to process, and output_directory with the path to the directory where you want to save the extracted tables.
Optional Arguments -p, --processes: Number of parallel processes (default: number of CPU cores) -r, --regex: Custom regex pattern for searching specific keywords in PDF files (default: '^(?s:(?=.*Revenue)|(?=.*Income))') For example, to use a custom regex pattern and specify the number of parallel processes, run the script as follows:
python script.py -i input_directory -o output_directory -r 'your_custom_pattern' -p 4
This project is licensed under the MIT License. See the LICENSE file for details.
Please feel free to open an issue or submit a pull request if you would like to contribute to the project or have any suggestions for improvements.
@ArthurStarks