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

Introduction

Hey there, fellow developer! Ready to dive into the world of ServiceTitan API integration? You're in for a treat. ServiceTitan's API is a powerful tool that can supercharge your field service management workflows. In this guide, we'll walk through building a robust integration that'll have you managing customers, scheduling jobs, and crunching numbers like a pro.

Prerequisites

Before we jump in, let's make sure you've got your ducks in a row:

• A Python environment (3.7+ recommended)
• Essential libraries: requests, json
• Your ServiceTitan API credentials (keep these safe!)

Got all that? Great! Let's roll up our sleeves and get coding.

Authentication

First things first: we need to get that golden ticket – the access token. Here's how:

import requests

def get_access_token(client_id, client_secret):
    url = "https://auth.servicetitan.io/connect/token"
    payload = {
        "grant_type": "client_credentials",
        "client_id": client_id,
        "client_secret": client_secret,
        "scope": "all"
    }
    response = requests.post(url, data=payload)
    return response.json()["access_token"]

Pro tip: These tokens expire, so implement a refresh mechanism to keep your integration humming along smoothly.

Making API Requests

Now that we're authenticated, let's start making some requests:

def make_api_request(endpoint, method="GET", data=None):
    headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "application/json"
    }
    url = f"https://api.servicetitan.io/v2/{endpoint}"
    response = requests.request(method, url, headers=headers, json=data)
    response.raise_for_status()
    return response.json()

This function is your Swiss Army knife for API requests. Use it wisely!

Error Handling

The API might throw you a curveball now and then. Be ready:

from requests.exceptions import RequestException

try:
    response = make_api_request("customers")
except RequestException as e:
    print(f"Oops! Something went wrong: {e}")

Data Processing

Once you've got your data, it's time to make it sing:

def process_customers(customer_data):
    return [
        {
            "id": customer["id"],
            "name": customer["name"],
            "phone": customer["phoneNumber"]
        }
        for customer in customer_data["data"]
    ]

Implementing Key Functionalities

Let's put it all together with some real-world examples:

Customer Management

def create_customer(name, phone):
    data = {"name": name, "phoneNumber": phone}
    return make_api_request("customers", method="POST", data=data)

Job Scheduling

def schedule_job(customer_id, service_type, start_time):
    data = {
        "customerId": customer_id,
        "serviceType": service_type,
        "startDateTime": start_time
    }
    return make_api_request("jobs", method="POST", data=data)

Optimizing Performance

Remember, the API has rate limits. Be a good citizen:

import time

def rate_limited_request(endpoint):
    response = make_api_request(endpoint)
    time.sleep(1)  # Be nice to the API
    return response

Testing and Debugging

Always test your code. Your future self will thank you:

import unittest

class TestServiceTitanIntegration(unittest.TestCase):
    def test_customer_creation(self):
        customer = create_customer("John Doe", "1234567890")
        self.assertIsNotNone(customer["id"])

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

Deployment and Maintenance

Consider containerizing your integration with Docker for easy deployment and scaling. And don't forget to keep an eye on those API changes!

Conclusion

And there you have it! You've just built a solid foundation for your ServiceTitan API integration. Remember, this is just the beginning. The API has tons more to offer, so keep exploring and building awesome things!

Happy coding, and may your services always be titan-ic! 🚀