Data Automation & Cleaning Intermediate

Extract Line Items, GSTIN & Invoice Totals from PDF Invoices using Regex in Python

Parse unstructured vendor PDF invoices into structured Pandas DataFrames using pdfplumber and regular expressions in Python.

#pdfplumber#pandas

Problem Statement

Accounts payable teams process thousands of unstructured PDF vendor invoices manually. This script extracts invoice numbers, dates, GSTINs, and totals automatically.

Formula / Core Logic

Extracts text via pdfplumber and applies compiled regex patterns for Invoice Number, Grand Total, and Tax amounts.

Installation

pip install pdfplumber pandas

pdf-invoice-data-extraction-regex-python.py

import pdfplumber
import re
import pandas as pd

.def parse_pdf_invoice(pdf_path):
    text = ''
    with pdfplumber.open(pdf_path) as pdf:
        for page in pdf.pages:
            text += page.extract_text() or ''
            
    inv_match = re.search(r'Invoice\s*No[:\s]*([A-Za-z0-9/-]+)', text, re.IGNORECASE)
    tot_match = re.search(r'Total[:\s]*([0-9,.]+)', text, re.IGNORECASE)
    return {
        'Invoice_No': inv_match.group(1) if inv_match else 'UNKNOWN',
        'Total_Amount': tot_match.group(1) if tot_match else '0.00'
    }

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Frequently Asked Questions

Q: Does this work on scanned image PDFs?

Scanned PDFs require OCR (pytesseract); pdfplumber works best on digital native PDF invoices.