InvoiceFlow: PDF Invoices to Excel

Invoice information needs to move from PDF documents into structured data before it is useful for spreadsheet analysis. InvoiceFlow processes batches of digital PDF invoices and exports invoice-level fields and line items into separate Excel sheets.

The project turns a repeated document-handling task into a command-line pipeline with explicit responsibilities.

Invoice layouts can differ, and a batch needs to be processed without mixing extraction rules with orchestration or spreadsheet formatting. The tool supports sequential execution for debugging and multiprocessing for batch processing.

Version 0.1.0 extracts text from digital PDFs. OCR for scans, AI extraction, additional export formats, a REST API and a GUI are documented roadmap items. They are not implemented features claimed by this case study.

• Batch processing and exportDiscover PDF inputs, extract structured invoice data and write formatted multi-sheet Excel workbooks.
• Extension pointsAn isolated parser layer and pluggable extractor strategies for different invoice layouts or future extraction methods.
• Development and operationDemo invoice generation, a benchmark command, environment-based configuration and rotating file logs.

The CLI routes the generate, process and benchmark commands. The pipeline discovers PDFs and coordinates execution. A parser reads text, an extractor maps that text into an InvoiceData model, and an exporter writes the workbook.

A BaseExtractor subclass can add a layout-specific mapping without changing the orchestration. ProcessPoolExecutor distributes extraction across processes. Keeping parsing separate provides a place for a future OCR backend without presenting OCR as a current capability.

Technologies: Python, pdfplumber, pandas, openpyxl, ReportLab, Faker, ProcessPoolExecutor and pytest.

The design addresses two practical difficulties: varying document layouts and coordinating batch work while keeping debugging possible. The strategy interface isolates extraction changes; sequential mode makes the same processing path easier to investigate.

The benchmark reports throughput on the machine running it. No fixed performance number or client time saving is claimed here.

The result is a public toolkit that converts batches of digital PDF invoices into structured Excel workbooks. The repository and product documentation let visitors inspect the project and try the commands.

This is an example of the Python and automation work I can bring to a custom workflow, while the exact extraction rules and integrations depend on the documents and systems involved.