A PDF Parser is a software which can be used to extract data from PDF documents. PDF Parsers can come in form of libraries for developers or as standalone software products for end-users.
PDF Parsers are used mainly to extract data from a batch of PDF files. Manual data entry (copy & paste) is a common alternative when data needs to be extracted from only a handful of documents.
What kind of data can be extracted with a PDF Parser?
PDF files are the go-to option for many different document types, ranging from books, presentations, reports, brochures to invoice and purchase orders. While PDF offers the capability to embed rich media types and attachments, PDF parsing solutions are typically used to extract:
- Text paragraphs
- Single data fields (dates, tracking numbers, …)
- Tabular data (tables and lists)
What are typical use-cases for PDF Parsers
PDF parsers are applied in various fields, ranging from document management, document indexing to business process automation with the goal of automatically extracting data from PDF files. Use-cases we see quite often at Docparser, are Automated Invoice & Accounts Payable Processing, Purchase Order Parsing, PDF Form Processing, Converting PDF bank statements, etc.
Is PDF parsing comparable to web scraping?
PDF parsing is indeed very similar to scraping data from websites. Some people actually use the word “PDF Scraper” instead of PDF Parser. Scraping data from websites comes however with the advantage that websites typically come as hierarchically structured HTML documents. Being able to access HTML tags (e.g. <h1>, <h2>, <table>, …) makes it much easier for a software to “understand” the structure of a document. Unfortunately, the PDF specification does not contain any structuring tags. For example, a table inside a PDF file is basically just text which is arranged in a certain way. This makes extracting data from PDF files quite challenging.