Table of Contents
Introduction to Python PDF Scraping
There is a great amount of information on the web provided in PDF format which is used as an alternative for paper-based documents. Thanks to its great compatibility across different operating systems and devices, it’s one of the most commonly used data formats today.
However, the content in PDF format is often unstructured, and downloading
and scraping hundreds of PDF files manually is time-consuming and rather
exhausting. In this article, we’ll explore the process of downloading data
from PDF files with the help of Python and its packages. So, let’s move on
and discover this PDF scraper for free!
How to Scrape Data from PDF Documents
Before getting deeper into coding with Python, let’s have a look at the other methods that can be used for extracting PDF data:How to Scrape all PDF Files from a Website
In this part, we’ll learn how to download files from a web directory. We’re going to use BeautifulSoup – the best scraping module of Python, as well as the requests module. As usually, we start with installing all the necessary packages and modules.
The next step is to copy the website URL and build an HTML parser using
BeautifulSoup, then use the requests module to get request.
After that, we need to look through the PDFs from the target website and
finally we need to create an info function using the pypdf2 module to
extract all the information from the PDF. The complete code looks like
this:
How to Get URLs from PDF Files
In this section, we are going to learn how to extract URLs from PDF files with Python. For this purpose, we’ll use PyMuPDF and pikepdf libraries by applying two methods:- To extract annotations like markups, and notes, and comments that redirect to the browser when you click on them.
- To extract the whole raw text and parse URLs by using regular expressions.
Getting URLs from annotations
For this method, we’ll use the pikepdf library. We need to open a PDF file and go through all annotations to identify if there is an URL:
You can use any PDF file, just be sure that it has clickable links.
After running the code, you will get the output with links:
Getting URLs through regular expressions
In this method, we will get all the raw text from a PDF file and parse URLsafter that using regular expressions. First, we need to get the text version of our PDF file:
The next step is to parse the URLs from the text by running the
following module.
The output will be the following:
Common Python Libraries for PDF Scraping
Here is the list of Python libraries that are widely used for the PDF scraping process:- PDFMiner is a very popular tool for extracting content from PDF documents, it focuses mainly on downloading and analyzing text items.
- PyPDF2 is a pure-python library used for PDF files handling. It enables the content extraction, PDF documents splitting into pages, document merging, cropping, and page transforming. It supports both encrypted and unencrypted documents.
- Tabula-py is used to read the table of PDF documents and convert into pandas’ DataFrame and also it enables to convert PDF files into CSV/JSON file.
- PDFQuery is used to extract data from PDF documents using the shortest possible code.
