We can also use it as a PDF transformer and a PDF parser. It provides information such as fonts and lines. PDFMiner allows the user to analyze text data and obtain the definite location of a text. It is a tool used to extract information from PDF documents. Let us look into some of the libraries Python offers to handle PDFs: PdfMiner
Pdfrw was created by Patrick Maupin and allows you to perform all functions which PyPDF2 is capable of except a few such as encryption, decryption, and types of decompression. You can also use a substitute package - pdfrw. But since PyPDF4 is not fully backward compatible with the PyPDf2, it is suggested to use PyPDF2.
The biggest difference between PyPDF and the other versions was that the later versions supported Python3. After a year or so, a company named Phasit sponsored a branch of the PyPDF called PyPDF2 which was consistent with the original package and worked pretty well for several years.Ī series of packages were released later on with the name of PyPDF3 and later renamed as PyPDF4. The first PyPDF package was released in 2005 and the last official release in 2010. Get certified and learn more about Python Programming and apply those skills and knowledge in the real world. You can also extract information from PDF and use into Natural Language Processing or any other Machine Learning models. An overview of advanced python programming makes it easier to play with a PDF in Python. There are several libraries and frameworks available which are designed in Python exclusively for text analytics. Now an important question arises, why do we need Python to process PDFs? Well, processing a PDF falls under the category of text analytics.
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