Python search downloadable pdf

We are now going to search inside pdf files instead. According to my pdf reader, the word "ship" is written 83 times. Let's see if we can come to the same number with pypdf2. The code works as follows: first, we open the pdf and read the pdf with the PdfFileReader method. We loop through the pages and get each page with the getPage method. Improve Article. Save Article. Like Article. Last Updated : 13 Apr, Import libraries.

URL from which pdfs to be downloaded. Requests URL and get response object. Find all hyperlinks present on webpage. From all links check for pdf link and. Get response object for link. Once you have a list of all the pdf links, you can download them using. Sample script to find links ending with. Stack Overflow for Teams — Collaborate and share knowledge with a private group.

Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. Asked 7 years, 9 months ago. Active 1 year, 5 months ago. Viewed 41k times. Improve this question. That's definitely possible. Add a comment. Active Oldest Votes. What I learned is:. Computer vision is at reach of mere mortals in If you have a good sample of already classified documents you can use OpenCV or SciKit-Image in order to extract features and train a machine learning classifier to determine what type a document is.

If the PDF you are analyzing is "searchable", you can get very far extracting all the text using a software like pdftotext and a Bayesian filter same kind of algorithm used to classify SPAM.

So there is no reliable and effective method for extracting text from PDF files but you may not need one in order to solve the problem at hand document type classification. I've written extensive systems for the company I work for to convert PDF's into data for processing invoices, settlements, scanned tickets, etc. That said, the fastest, most reliable, and least-intensive way is to use pdftotext , part of the xpdf set of tools. This tool will quickly convert searchable PDF's to a text file, which you can read and parse with Python.

Hint: Use the -layout argument. And by the way, not all PDF's are searchable, only those that contain text. Some PDF's contain only images with no text at all. It's messy, and painful, but this will work for searchable PDF docs. So far I've found this to be accurate, but painful. Here is the solution that I found it comfortable for this issue. In the text variable you get the text from PDF in order to search in it.

I agree with Paulo PDF data-mining is a huge pain. But you might have success with pdftotext which is part of the Xpdf suite freely available here:. It will give you text files, which you may find easier to work with. If you are on bash, There is a nice tool called pdfgrep , Since, This is in apt repository, You can install this with:. Trying to pick through PDFs for keywords is not an easy thing to do.

I tried to use the pdfminer library with very limited success. Everything in a PDF can stand on its own or be a part of a horizontal or vertical section, backwards or forwards. Pdfminer was having issues translating one page, not recognizing the font, so I tried another direction — optical character recognition of the document. That worked out almost perfectly. BytesIO is a streaming object that simulates a file load as if the object was coming off of disk, which wand requires as the file parameter.

This allows you to just take the data in memory instead of having to save the file to disk first and then load it. If you want to print out all the matches of a string pattern on every page.