How to Compress PDFs Programmatically in Python (5 Lines of Code)

The 5-Line Implementation

You'll need the requests library. If you don't have it, run pip install requests.

import requests

# 1. Your API Key (Get yours at pdfsqueezer.io)
headers = {'Authorization': 'Bearer YOUR_API_KEY'}
url = 'https://api.pdfsqueezer.io/v1/compress'

# 2. Open the file and send the request
with open('large_document.pdf', 'rb') as f:
    response = requests.post(url, files={'file': f}, headers=headers)

# 3. Save the "squeezed" version
if response.status_code == 200:
    with open('optimized_document.pdf', 'wb') as f:
        f.write(response.content)
    print("Compression Successful!")

Why use an API instead of a local library?

• Sub-Second Latency: Our globally distributed endpoints handle the heavy lifting so your server CPU stays cool.
• Object-Level Optimization: We don't just "zip" the file; we intelligently downsample images and scrub hidden metadata.
• No Dependencies: Avoid the headache of installing complex C-libraries (like Ghostscript) on your production server.

Advanced Configuration

Want more control? You can pass parameters to fine-tune the balance between quality and size:

params = {
    'quality': 75,              # 1-100 scale
    'stripMetadata': True,      # Removes EXIF and private data
    'maxDimension': 1600        # Resizes oversized images
}
response = requests.post(url, files={'file': f}, headers=headers, params=params)

Integrating with AWS S3 or Google Cloud

For most production apps, you'll want to compress the file before it hits your long-term storage. By inserting PDF Squeezer into your upload pipeline, you can save thousands of dollars in egress and storage fees as your app scales.

Frequently asked questions