Integration • Developer SDK pattern

Python PDF API

Add PDF generation and structured document extraction to FastAPI, Django, Flask, scripts, workers, and data pipelines.

Extract JSON from PDF · PDF Form Field Extraction · Documentation

Python applications can call PrefillPDF using standard HTTP libraries. Send structured data into a template or submit an existing PDF for extraction.

This works well for backend APIs, scheduled jobs, ETL pipelines, financial systems, internal tools, and AI-assisted document workflows.

Common Python workflows

FastAPI document endpoint

Receive application data, call PrefillPDF, and return or store the generated PDF.

PDF extraction worker

Process uploaded PDFs asynchronously, extract JSON, validate fields, and write results to a database.

Batch processing script

Read records from CSV or a database and generate or analyze documents in controlled batches.

How the integration works

Create an API client

Use requests, httpx, or your preferred HTTP client and load the API key from environment variables.

Prepare the request

Send JSON for PDF generation or multipart/file data for document extraction.

Validate the response

Check status codes, content type, returned JSON, and error fields.

Store or return the result

Save extracted data, stream the PDF, upload it to storage, or continue your business workflow.

Python request example

import os
import requests

response = requests.post(
    "https://api.prefillpdf.com/fill-pdf",
    headers={
        "Authorization": f"Bearer {os.environ['PREFILLPDF_API_KEY']}",
        "Accept": "application/json",
    },
    json={
        "template_id": "your-template-id",
        "data": {
            "customer_name": "Jane Smith",
            "amount": 25000,
        },
    },
    timeout=60,
)

response.raise_for_status()
result = response.json()