The way we do this is by converting each individual page into an image file. Now, once our setup is complete, we can convert a PDF into a collection of image files. tesseract is an underlying utility that performs OCR ( Optical Character Recognition) on images to extract text. Pytesseract depends upon tesseract being installed ( see here for instructions). This package can also be installed using pip: pip install pytesseract For example, pdf2image is another choice, but we’ll use Wand in this tutorial.Īdditionally, let’s go ahead and install pytesseract. There are other options for packages that convert PDFs into images files. This package also requires a tool called ImageMagick to be installed ( see here for more details). Wand can be installed using pip: pip install Wand Let’s get started by setting up the Wand package. Since pytesseract doesn’t work directly on PDFs, we have to first convert our sample PDF into an image (or collection of image files). The second of these is used to convert PDFs into image files, while pytesseract is used to extract text from images. In this case, we’re going to be using two other Python packages – pytesseract and Wand. If a PDF contains scanned-in images of text, then it’s still possible to be scrapped, but requires a few additional steps. Text = extract_text("apple_10k.pdf", password = "top secret password") If the PDF we want to scrape is password-protected, we just need to pass the password as a parameter to the same method as above. Text_pages = extract_text("apple_10k.pdf", page_numbers = ) Text10 = extract_text("apple_10k.pdf", page_numbers = range(10)) If we want to limit our extraction to specific pages, we just need to pass that specification to extract_text using the page_numbers parameter. The code above will extract the text from each page in the PDF. The extract_text function, as can be seen below, shows that we can extract text from a PDF with one line code (minus the package import)! This is an advantage of pdfminer versus some other packages like PyPDF2.įrom pdfminer.high_level import extract_text This module within pdfminer provides higher-level functions for scraping text from PDF files. Next, let’s import the extract_text method from pdfminer.high_level. To download the version of the package we need, you can use pip (note we’re downloading pdfminer.six): pip install pdfminer.six The first package we’ll be using to extract text is pdfminer. First, we’ll just download this file to a local directory and save it as “apple_10k.pdf”. Scraping hightlightable textįor the first example, let’s scrape a 10-k form from Apple ( see here). On the other hand, to read scanned-in PDF files with Python, the pytesseract package comes in handy, which we’ll see later in the post. Pdfminer (specifically pdfminer.six, which is a more up-to-date fork of pdfminer) is an effective package to use if you’re handling PDFs that are typed and you’re able to highlight the text. To read PDF files with Python, we can focus most of our attention on two packages – pdfminer and pytesseract. In this post, we’ll cover how to extract text from several types of PDFs. In a previous article, we talked about how to scrape tables from PDF files with Python.
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