PDF Table and Text Parsing with Python
Extract data from purchase orders with PyPDF, PdfPlumber, and RegEx.
Let’s take a look at the image above for a moment. Metaphorically, PDF files can be seen as the raw product, which in this case are mangos. If we turn them into juice, we are adding liquidity to Mangos (literally)! With juices, we can make ice creams, yoghurts, cakes, smoothies, use them for cooking, and much more. That’s exactly what happens when we parse PDF files, and turn the data into text files, CSVs, JSONs and other formats that allow for much easier integration.
In automation, PDF parsing is an increasingly demanding skill, because it allows companies to cut hours of manual and boring work. Purchase orders are a good example, they’re usually sent in PDF format, and workers need to extract the information line-by-line, before shipping the products to the client, which is a layer of complexity that can easily be removed.
Mastering PDF parsers such as PyPDF, PDFMiner, PdfPlumber, Tabula and many more, is key to seamlessly extracting data from purchase orders and incorporating it with your automation infrastructure and accounting software.
Nonetheless, when dealing with PDF data, the easiest part is to apply the parser, the real challenge relies on cleaning and extracting meaningful…
