![]() ![]() Note: In this blog post, we only work with searchable PDF files. This is due to historical reasons – according to the author You can install it by typing in the terminal.Īnd start using the library by importing the installed module: import fitzīear in mind that the top-level Python import name of the PyMuPDF library is fitz. Let’s dive into PyMuPDF, the library needed for text extraction. It allows you to see both the code and the results at the same time. We also recommend installing the jupyter notebook ( Project Jupyter), which is great for showcasing your work. A virtual environment is preferable since we can manage our Python packages. If you are a beginner, please follow this tutorial to set up a proper programming workspace for yourself: Python – Environment Setup. We’ll assume that you already have a Python environment (with Python >=3.7). Our today’s article will guide you through every step needed to fully extract and analyze the text from a PDF document. This issue can be easily tackled by programming with the help of the PyMuPDF library. What if you want to auto-convert all these documents and store the most useful information in your database? ![]() Bankers also need to spend days inputting invoice data into a system. For example, the HR department in any company has to look through hundreds of resumes/CVs every month. Reading or scanning many documents manually involves a lot of time and effort. It’s one of the most important tasks in natural language processing. Text Extraction refers to the process of automatically scanning and converting unstructured text into a structured format. ![]()
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