Today we will be learning how we can extract the text from PDF files in Python 3.10, so that we can later process that text in any way we please. ▶ Become job-ready with Python: www.indently.io ▶ Follow me on Instagram: / indentlyreels
Awesome, so helpful! That's much simpler and ready-to-use compared to all others approaches found online. Is there a way to export the extracted text to a csv or xlsx file?
The code did not work for me on a Windows 11 PC. I kept having ChatGPT analyze the code and error messages and after many tires it fixed it: import os import PyPDF2 import re import math def extract_text_from_pdf(pdf_file: str) -> [str]: # Open the PDF file of your choice with open(pdf_file, 'rb') as pdf: reader = PyPDF2.PdfReader(pdf) pdf_text = [] for page in reader.pages: content = page.extract_text() pdf_text.append(content) return pdf_text def main(): extracted_text = extract_text_from_pdf('sample.pdf') for text in extracted_text: print(text) if __name__ == '__main__': main()
I found that by opening a pdf file with Mozilla Firefox and inspecting it with the developer tools you can collect its text (with the help of JavaScript) after the web browser has converted it to HTML and maybe save it for further processing with someone programming language.
Thank you for the awesome tutorial. I have a some question about extracting articles. I hope you can help me. While extracting articles and reports there are many references and table legends, titles which is not required. Would it be possible to remove all those references and table contents including legends and titles when extracting the pdf file?
Hey , I have some 600 files which have large volume of data, text extraction using pypdf2 is taking a lot of time , is there any other way to do this ?
I am pretty sure there are over a thousand isntances of the word "coffee" in the pdf. However, this seems to have only counted the number of pages that the word appeared.
I wrote the code line per line, word for word but it continue to give me File not found, how it's possible? p.s. I managed to extrat text, the only problem is the layout of the answer, i have a string long miles
def convert_pdf_to_text(pdf_path): with pdfplumber.open(pdf_path) as pdf: for page in pdf.pages: text = page.extract_text(layout=True) print(text) return text