whoiskatrin/financial-statement-pdf-extractor

Python script to extract as much structured information as possible from annual/quarterly reports.

PDF Financial Statement Extractor 📚🔍

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.

Features ✨

• 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

Installation 🛠️

Dependencies

• Python 3.7 or higher
• pdfgrep (system package)

Steps

1. 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

Usage

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

License 📄

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

Contributing 🤝

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.

financial-statement-pdf-extractor's Issues

pages not getting

        cmd = "pdfgrep -Pn '^(?s:(?=.*Revenue)|(?=.*Income))' " + pdf + " | awk -F\":\" '$0~\":\"{print $1}' | tr '\n' ','"
        pages = subprocess.check_output(cmd, shell=True).decode("utf-8")