Step by Step Guide to Building a PandaDoc API Integration in Python

Introduction

Hey there, fellow developer! Ready to supercharge your document workflows? Let's dive into building a PandaDoc API integration in Python. PandaDoc's API is a powerhouse for automating document creation, sending, and tracking. By the end of this guide, you'll be wielding this tool like a pro.

Prerequisites

Before we jump in, make sure you've got:

• A Python environment (3.6+ recommended)
• A PandaDoc account with API access
• Your favorite code editor

Got all that? Great! Let's roll.

Setting up the project

First things first, let's get our project structure in order:

mkdir pandadoc_integration
cd pandadoc_integration
python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
pip install requests

Authentication

Alright, time to get that API key. Head over to your PandaDoc account, navigate to the API section, and grab your key. We'll use it to authenticate our requests:

import requests

API_KEY = 'your_api_key_here'
BASE_URL = 'https://api.pandadoc.com/public/v1'

headers = {
    'Authorization': f'API-Key {API_KEY}',
    'Content-Type': 'application/json'
}

Basic API Operations

Let's start with the bread and butter of document operations:

Creating a document

def create_document(name, content):
    url = f'{BASE_URL}/documents'
    payload = {
        'name': name,
        'document_template_uuid': 'your_template_id',
        'recipients': [{'email': '[email protected]', 'first_name': 'John', 'last_name': 'Doe'}],
        'fields': content
    }
    response = requests.post(url, headers=headers, json=payload)
    return response.json()

# Usage
doc = create_document('My Awesome Document', {'field1': 'value1', 'field2': 'value2'})
print(f"Document created with ID: {doc['id']}")

Retrieving document details

def get_document(doc_id):
    url = f'{BASE_URL}/documents/{doc_id}'
    response = requests.get(url, headers=headers)
    return response.json()

# Usage
doc_details = get_document('abc123')
print(f"Document status: {doc_details['status']}")

Sending a document for signature

def send_document(doc_id):
    url = f'{BASE_URL}/documents/{doc_id}/send'
    payload = {'message': 'Please sign this document'}
    response = requests.post(url, headers=headers, json=payload)
    return response.json()

# Usage
send_result = send_document('abc123')
print(f"Document sent: {send_result['id']}")

Advanced Features

Now that we've got the basics down, let's spice things up:

Using templates

def create_from_template(template_id, data):
    url = f'{BASE_URL}/documents'
    payload = {
        'template_uuid': template_id,
        'recipients': [{'email': '[email protected]', 'first_name': 'John', 'last_name': 'Doe'}],
        'tokens': data
    }
    response = requests.post(url, headers=headers, json=payload)
    return response.json()

# Usage
doc = create_from_template('template123', {'customer_name': 'Acme Inc', 'order_number': '12345'})

Handling webhooks

from flask import Flask, request

app = Flask(__name__)

@app.route('/webhook', methods=['POST'])
def handle_webhook():
    data = request.json
    if data['event'] == 'document_state_changed':
        print(f"Document {data['document']['id']} changed to status: {data['document']['status']}")
    return '', 200

if __name__ == '__main__':
    app.run(port=5000)

Error Handling and Best Practices

Always expect the unexpected:

import time

def api_call_with_retry(func, *args, max_retries=3, **kwargs):
    for attempt in range(max_retries):
        try:
            return func(*args, **kwargs)
        except requests.exceptions.RequestException as e:
            if attempt == max_retries - 1:
                raise
            time.sleep(2 ** attempt)  # Exponential backoff

# Usage
try:
    doc = api_call_with_retry(create_document, 'Retry Test', {'field': 'value'})
except requests.exceptions.RequestException as e:
    print(f"Failed to create document after multiple attempts: {e}")

Testing the Integration

Don't forget to test! Here's a quick unit test example:

import unittest
from unittest.mock import patch
from your_module import create_document

class TestPandaDocIntegration(unittest.TestCase):
    @patch('requests.post')
    def test_create_document(self, mock_post):
        mock_post.return_value.json.return_value = {'id': 'test123'}
        result = create_document('Test Doc', {'field': 'value'})
        self.assertEqual(result['id'], 'test123')

if __name__ == '__main__':
    unittest.main()

Deployment Considerations

As you scale up, keep these in mind:

• Use environment variables for API keys
• Implement proper logging
• Consider using a task queue for background processing

Conclusion

And there you have it! You're now equipped to build a robust PandaDoc integration in Python. Remember, the API has a ton more features to explore, so don't be afraid to dive deeper into the official documentation.

Happy coding, and may your documents always be perfectly formatted and promptly signed!