How to convert DOCX to PDF using Python

In this post, you’ll learn how to convert DOCX files to PDFs in your Python application using Nutrient’s DOCX-to-PDF Python API. With our API, you receive 100 credits with the free plan. Different operations on a document consume different amounts of credits, so the number of PDF documents you can generate may vary. All you need to do is create a free account(opens in a new tab) to get access to your API key.

Nutrient API

Document conversion is just one of our 30+ PDF API tools. You can combine our conversion tool with other tools to create complex document processing workflows. You’ll be able to convert various file formats into PDFs and then:

• Merge several resulting PDFs into one
• OCR, watermark, or flatten PDFs
• Remove or duplicate specific PDF pages

Once you create your account, you’ll be able to access all our PDF API tools.

Step 1 — Creating a free account on Nutrient

Go to our website(opens in a new tab), where you’ll see the page below, prompting you to create your free account.

Once you’ve created your account, you’ll be welcomed by the page below, which shows an overview of your plan details.

As you can see in the bottom-left corner, you’ll start with 100 credits to process, and you’ll be able to access all our PDF API tools.

Step 2 — Obtaining the API key

After you’ve verified your email, you can get your API key from the dashboard. In the menu on the left, click API Keys. You’ll see the following page, which is an overview of your keys:

Copy the Live API Key, because you’ll need this for the DOCX-to-PDF API.

Step 3 — Setting up folders and files

Now, create a folder called docx_to_pdf and open it in a code editor. For this tutorial, you’ll use VS Code as your primary code editor. Next, create two folders inside docx_to_pdf and name them input_documents and processed_documents.

Next, copy your DOCX file to the input_documents folder. You can use our demo document as an example.

Then, in the root folder, docx_to_pdf, create a file called processor.py. This is the file where you’ll keep your code.

Your folder structure will look like this:

docx_to_pdf
├── input_documents
|    └── document.docx
├── processed_documents
└── processor.py

Step 4 — Writing the code

Open the processor.py file and paste the code below into it:

import requests
import json

instructions = {
  'parts': [
    {
      'file': 'document'
    }
  ]
}

response = requests.request(
  'POST',
  'https://api.nutrient.io/build',
  headers = {
    'Authorization': 'Bearer YOUR API KEY HERE'
  },
  files = {
    'document': open('input_documents/document.docx', 'rb')
  },
  data = {
    'instructions': json.dumps(instructions)
  },
  stream = True
)

if response.ok:
  with open('processed_documents/result.pdf', 'wb') as fd:
    for chunk in response.iter_content(chunk_size=8096):
      fd.write(chunk)
else:
  print(response.text)
  exit()

Code explanation

In the code above, you first import the requests and json dependencies. After that, you create the instructions for the API call.

You then use the requests module to make the API call, and once it succeeds, you store the result in the processed_documents folder.

Output

To execute the code, use the command below:

python3 processor.py

Once the code has been executed, you’ll see a new processed file under the processed_documents folder called result.pdf.

The folder structure will look like this:

docx_to_pdf
├── input_documents
|    └── document.docx
├── processed_documents
|    └── result.pdf
└── processor.py

Final words

In this post, you learned how to easily and seamlessly convert DOCX files to PDF documents for your Python application using our DOCX-to-PDF Python API.

You can integrate these functions into your existing applications. With the same API token, you can also perform other operations, such as merging several documents into a single PDF, adding watermarks, and more. To get started with a free trial, sign up(opens in a new tab) here.