This class has no parameters, you can just create it like so: writer = PyPDF2.PdfFileWriter() Next thing we need is a PdfFileWriter object. This is the main reason why I also used the other library, PDFMiner, in the project.
#PDF EXTRACT TEXT TO WORD PDF#
However, even the official documentation says this on the method: “This works well for some PDF files, but poorly for others, depending on the generator used.” Which is not exactly reassuring, and in my experience, extractText did not work properly, it left out first and last lines of pages. For example, to get the text on the 7th page (remember, zero-index) of a pdf, you would first create a PageObject from the PdfFileReader, and call this method: reader.getPage(7-1).extractText() We are not going to heavily utilise the PageObject class, one extra thing you could consider doing is the extractText method, which converts the contents of a page to a string variable. Be careful, PageObjects are in a list, so the method uses a zero-based index. Perhaps the most important method is getPage(page_num) which returns one page of the file as a separate PageObject. You can also get the total number of pages with reader.numPages. For example, reader.documentInfo is an attribute that contains the document information dictionary in this format: You can get a number of general information about your document with this reader object. The parameter is the path to a pdf document we want to work with.
The first object we need is a PdfFileReader: reader = PyPDF2.PdfFileReader('Complete_Works_Lovecraft.pdf')
#PDF EXTRACT TEXT TO WORD INSTALL#
PyPDF2Īs a first step, install the package: pip install PyPDF2
For more information on this project, please refer to my GitHub repo. Then, in the second part, we are going to work on one project, which is about splitting a 708-page long pdf file into separate smaller files, extracting the text information, cleaning it, and then exporting to easily readable text files. We will discuss the different classes and methods we need. As their name suggests, they are libraries written specifically to work with pdf files. In the first part, we are going to have a look at two Python libraries, PyPDF2 and PDFMiner.
#PDF EXTRACT TEXT TO WORD HOW TO#
There is a pdf, there is text in it, we want the text out, and I am going to show you how to do that using Python. Some systems are capable of reproducing formatted output that closely approximates the original page including images, columns, and other non-textual components.I don’t think there is much room for creativity when it comes to writing the intro paragraph for a post about extracting text from a pdf file.
Advanced systems capable of producing a high degree of recognition accuracy for most fonts are now common, and with support for a variety of digital image file format inputs. OCR is a field of research in pattern recognition, artificial intelligence and computer vision.Early versions needed to be trained with images of each character, and worked on one font at a time. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example from a television broadcast).Widely used as a form of data entry from printed paper data records – whether passport documents, invoices, bank statements, computerized receipts, business cards, mail, printouts of static-data, or any suitable documentation – it is a common method of digitizing printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining.
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