Partitioning Large PDF Files with Python and Unstructured.io

When dealing with large PDF files, it can often be beneficial to break them down into smaller, more manageable chunks. This process, known as partitioning, can improve processing efficiency and make it easier to analyze or manipulate the document. In this article, we will discuss how to use Python and a powerful library called Unstructured.io to partition PDF files into smaller sections.

Libraries Used

We will be using two Python libraries for this task:

1. PyPDF2: A library that can read, write, merge, and split PDF files.
2. Unstructured.io: A library that can segment PDF documents using document image analysis models.

Code Walkthrough

Here is the Python code that accomplishes this task:

from PyPDF2 import PdfReader, PdfWriter

# Read the original PDF
input_pdf = PdfReader(f'./exam-prep/{filename}')

batch_size = 100
num_batches = len(input_pdf.pages) // batch_size + 1

# Extract batches of 100 pages from the PDF
for b in range(num_batches):
    writer = PdfWriter()

    # Get the start and end page numbers for this batch
    start_page = b * batch_size
    end_page = min((b+1) * batch_size, len(input_pdf.pages))

    # Add pages in this batch to the writer
    for i in range(start_page, end_page):
        writer.add_page(input_pdf.pages[i])

    # Save the batch to a separate PDF file
    batch_filename = f'./exam-prep/output/{filename}-batch{b+1}.pdf'
    with open(batch_filename, 'wb') as output_file:
        writer.write(output_file)

    # Now you can use the `partition_pdf` function from Unstructured.io to analyze the batch
    elements = partition_pdf(filename=batch_filename)
    # Do something with `elements`...

Step 1: Reading the PDF

First, we import the necessary classes from the PyPDF2 library: PdfReader and PdfWriter. The PdfReader class is used to read the original PDF file, which is stored in a subdirectory called 'exam-prep'.

Step 2: Partitioning the PDF

We decide on a batch size, which is the number of pages each chunk of the PDF will contain. In this example, we chose a batch size of 100 pages, but this can be adjusted according to your needs.

The number of batches is then calculated by dividing the total number of pages in the PDF by the batch size. We add 1 to ensure that we capture any leftover pages if the total number of pages is not a multiple of the batch size.

Step 3: Writing the PDF Chunks

Next, we loop over each batch, creating a new PdfWriter object for each one. For each batch, we calculate the start and end page numbers and add each page in that range to the PdfWriter using the add_page method.

Once all the pages for a batch have been added, we write them to a new PDF file in the 'output' subdirectory. The filename of each chunk includes the original filename and the batch number.

Step 4: Analyzing the PDF Chunks

With the PDF divided into smaller chunks, you can now use the partition_pdf function from the Unstructured.io library to analyze each batch. This function segments a PDF document using a document image analysis model and returns a list of elements present in the pages of the parsed PDF document.

Conclusion

Partitioning large PDF files into smaller chunks can make them easier, fault tolerant and consume less memory.