Extract prices from PDF invoices

Extracting prices from PDF invoices typically involves these steps:

1. Convert PDF to Text or Data
   Use libraries like PyPDF2, pdfplumber, or pdfminer.six in Python to extract raw text from PDF invoices.

2. Parse the Text for Prices
   After extraction, use regular expressions or natural language processing (NLP) to locate price patterns (e.g., numbers with currency symbols or decimal points).

3. Handle Structured PDFs
   For PDFs that are more table-like or well-structured (like invoices), libraries like pdfplumber or camelot can extract tables directly, making it easier to isolate prices.

Example using Python (pdfplumber + regex)

python
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import pdfplumber
import re

def extract_prices_from_pdf(pdf_path):
    prices = []
    price_pattern = re.compile(r'$s?d{1,3}(?:,d{3})*(?:.d{2})?')  # Matches $12.34, $1,234.56, etc.

    with pdfplumber.open(pdf_path) as pdf:
        for page in pdf.pages:
            text = page.extract_text()
            if text:
                found_prices = price_pattern.findall(text)
                prices.extend(found_prices)
    return prices

# Example usage:
pdf_file = "invoice.pdf"
print(extract_prices_from_pdf(pdf_file))

Notes:

• Adjust regex depending on currency format (€, £, ₹, etc.).

• For scanned PDFs (images), use OCR tools like Tesseract (pytesseract).

• If invoices have consistent format, you can target specific sections or table rows.

If you want, I can provide a full article or a detailed guide on this topic.