Convert PDF to Text File Using Python

Converting scanned documents or PDF files to text can be a tedious and time-consuming task. Thankfully, Python offers a powerful and efficient solution with the pdftotext library.

What is pdftotext?

pdftotext is a Python module that allows you to extract text from PDF files. It uses a technique called Optical Character Recognition (OCR) to convert scanned text into machine-readable text.

Installing pdftotext:

If you are using a MAC make sure you run this command before doing the pip install


brew install pkg-config poppler
pip install pdftotext

Code Example:

from pdftotext import PDF

# Open the PDF file
with open('example.pdf', 'rb') as f:
    # Load the PDF document
    pdf_document = PDF(f)

# Extract the text content
text = ""
for page in pdf_document:
    text += page.strip()

# Write the text content to a text file
with open('output.txt', 'w') as f:
    f.write(text)

Explanation:

  • The code first imports the pdftotext library.
  • It then opens the PDF file in binary read mode (rb).
  • The PDF object is created by passing the file object to the PDF class.
  • The text content is extracted by iterating over each page in the PDF document.
  • Finally, the text is written to a new text file named output.txt.

Additional Features:

  • pdftotext supports various options, such as specifying the language, page range, and layout mode.
  • You can also use the get_layout() method to obtain information about the page layout, including tables, figures, and headers.

Benefits of Using pdftotext:

  • Easy to use: Requires minimal setup and coding knowledge.
  • Fast: Converts PDF files into text quickly.
  • Flexible: Offers various options for customization and data extraction.

Conclusion:

Converting PDF files to text using Python with the pdftotext library is a powerful tool for extracting information from scanned documents or PDF files. Its ease of use, speed, and flexibility make it a valuable asset for various tasks, such as research, document analysis, and accessibility.

Next we will look at getting text from a Word document. Stay Tuned.

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