How to Flatten Annotations in PDF Files with Python

Why Use Flatten Annotations with Python?

The pdfRest Flatten Annotations API Tool is designed to permanently merge annotations into the PDF content layer. This is useful when you want to ensure that comments, form fields, or markup added to a PDF are preserved when the document is printed or viewed on systems where annotations may not be displayed by default. For instance, if you've collected feedback on a document and want to create a version with all comments embedded for archival purposes, flattening annotations would be the way to go.

This tutorial will show you how to send an API call to Flatten Annotations using Python.

Flatten Annotations with Python Code Example

from requests_toolbelt import MultipartEncoder
import requests
import json

flattened_annotations_pdf_endpoint_url = 'https://api.pdfrest.com/flattened-annotations-pdf'

mp_encoder_flattenedPDF = MultipartEncoder(
    fields={
        'file': ('file_name.pdf', open('/path/to/file', 'rb'), 'application/pdf'),
        'output' : 'example_out'
    }
)

headers = {
    'Accept': 'application/json',
    'Content-Type': mp_encoder_flattenedPDF.content_type,
    'Api-Key': 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx' # place your api key here
}

print("Sending POST request to flattened-annotations-pdf endpoint...")
response = requests.post(flattened_annotations_pdf_endpoint_url, data=mp_encoder_flattenedPDF, headers=headers)

print("Response status code: " + str(response.status_code))

if response.ok:
    response_json = response.json()
    print(json.dumps(response_json, indent = 2))
else:
    print(response.text)

Reference: pdf-rest-api-samples on GitHub

Breaking Down the Code

This code snippet demonstrates how to use the pdfRest Flatten Annotations API with Python:

from requests_toolbelt import MultipartEncoder
import requests
import json

These lines import the necessary libraries. MultipartEncoder from requests_toolbelt is used for encoding multipart form data. The requests library is used to send HTTP requests, and json is used for working with JSON data.

mp_encoder_flattenedPDF = MultipartEncoder(
    fields={
        'file': ('file_name.pdf', open('/path/to/file', 'rb'), 'application/pdf'),
        'output' : 'example_out'
    }
)

This section creates a MultipartEncoder object with the PDF file to flatten and the desired output name. Replace '/path/to/file' with the actual file path and 'file_name.pdf' with the actual file name.

headers = {
    'Accept': 'application/json',
    'Content-Type': mp_encoder_flattenedPDF.content_type,
    'Api-Key': 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx' # place your api key here
}

Here, the headers for the HTTP request are defined. The 'Api-Key' should be replaced with your actual API key from pdfRest.

response = requests.post(flattened_annotations_pdf_endpoint_url, data=mp_encoder_flattenedPDF, headers=headers)

This line sends the POST request to the pdfRest API endpoint with the encoded PDF data and headers.

Beyond the Tutorial

By following the steps above, you've learned how to call the pdfRest Flatten Annotations API using Python. This can be a powerful tool in your document processing workflow, ensuring annotations are preserved in the final document version. You're encouraged to demo all of the pdfRest API Tools in the API Lab at https://pdfrest.com/apilab/ and refer to the API Reference documentation at https://pdfrest.com/documentation/ for more information.

Note: This is an example of a multipart API call. Code samples using JSON payloads can be found at https://github.com/datalogics/pdf-rest-api-samples.