10 Python Tornado Best Practices

Python Tornado is a powerful web framework that can be used to create web applications quickly and easily. It is a great choice for developing high-performance web applications, and it is becoming increasingly popular among developers.

However, it is important to use best practices when developing with Python Tornado. In this article, we will discuss 10 best practices for developing with Python Tornado. We will cover topics such as using asynchronous programming, using the right data structures, and more. By following these best practices, you can ensure that your web applications are secure, efficient, and reliable.

1. Use the correct version of Python

Python Tornado is a web framework that requires Python 3.5 or higher, and if you use an older version of Python, it won’t work properly.

Using the correct version of Python also ensures that your code will be compatible with other libraries and frameworks that are built on top of Python. This means that you can easily integrate your application with other services and tools without having to worry about compatibility issues.

Finally, using the latest version of Python helps ensure that your code is secure and up-to-date with the latest security patches. By keeping your code updated, you can avoid potential vulnerabilities and keep your application safe from malicious attacks.

2. Don’t use Tornado for CPU-bound tasks

Tornado is an asynchronous web framework, which means it’s designed to handle multiple requests at the same time. This makes it great for I/O-bound tasks like serving web pages or handling API calls.

However, when it comes to CPU-bound tasks, Tornado can be inefficient because it has to wait for each task to finish before moving on to the next one. This can lead to slow performance and poor scalability. Therefore, if you’re dealing with CPU-bound tasks, it’s best to use a different framework such as multiprocessing or threading.

3. Avoid blocking operations in your handlers

Tornado is a single-threaded web framework, meaning that it can only handle one request at a time. If you have a handler that performs a blocking operation (such as making an API call or accessing a database), then all other requests will be blocked until the first request is finished. This can lead to poor performance and slow response times for your users.

To avoid this issue, use asynchronous operations in your handlers whenever possible. Tornado provides several tools to help with this, such as its AsyncHTTPClient library and its coroutine decorator. By using these tools, you can ensure that your handlers are non-blocking and that your application remains responsive even under heavy load.

4. Use non-blocking database drivers

Tornado is an asynchronous web framework, meaning that it can handle multiple requests at the same time. However, if you use a blocking database driver, such as MySQLdb, then your Tornado application will be limited to handling one request at a time. This means that any other requests will have to wait until the first request has been completed before they can be processed.

Using non-blocking drivers, such as Motor or AsyncMySQL, allows your Tornado application to process multiple requests simultaneously and thus improve performance.

5. Use a reverse proxy like Nginx or HAProxy

A reverse proxy is a server that sits between the client and your application. It can handle requests from multiple clients, caching responses for faster performance, and also provide additional security features like rate limiting or authentication. This helps to offload some of the work from Tornado, allowing it to focus on serving dynamic content.

Using a reverse proxy also allows you to scale up easily by adding more servers behind the proxy. This makes it easier to manage traffic spikes and ensure high availability. Finally, using a reverse proxy gives you more control over how requests are routed, which can be useful when deploying applications across multiple environments.

6. Use Asynchronous Redis client

Redis is an in-memory data structure store that can be used for caching, message queues, and other types of data storage. When using Redis with Tornado, it’s important to use an asynchronous client so that the main thread isn’t blocked while waiting for a response from Redis. This ensures that your application remains responsive and can handle more requests at once.

Using an asynchronous Redis client also allows you to take advantage of Tornado’s non-blocking I/O capabilities, which makes it easier to scale your application as needed. Additionally, using an asynchronous client helps reduce latency by allowing multiple requests to be processed simultaneously.

7. Use asynchronous HTTP clients like Treq and AioHTTP

Using asynchronous HTTP clients allows you to make multiple requests at the same time, which can significantly reduce latency and improve performance. This is especially important when dealing with large amounts of data or making frequent API calls. Asynchronous HTTP clients also allow for better scalability since they don’t block other requests while waiting for a response.

Finally, using asynchronous HTTP clients makes it easier to write code that is more maintainable and readable. By taking advantage of Tornado’s async features, you can avoid writing complex callback functions and instead use simpler syntax like await/async.

8. Use async/await syntax instead of gen.coroutine

Async/await syntax is more concise and easier to read than gen.coroutine, making it simpler for developers to understand the code. It also allows for better error handling, as exceptions can be caught in a try-except block. Finally, async/await syntax is faster than gen.coroutine, which means your Tornado application will run more efficiently.

9. Use native coroutines whenever possible

Coroutines are a way of writing asynchronous code that is more efficient and easier to read than traditional callback-based approaches.

Native coroutines in Python Tornado allow you to write asynchronous code without having to worry about callbacks or other complexities. This makes your code simpler, faster, and more maintainable. Additionally, native coroutines can be used with the tornado.gen module for even greater efficiency.

Using native coroutines whenever possible will help ensure that your application runs as efficiently as possible and is easy to maintain.

10. Use a single IOLoop per process

Using a single IOLoop per process allows for better resource utilization, as the same loop can be used to handle multiple requests. This also helps reduce latency and improve performance, since there is no need to create new loops for each request. Additionally, it simplifies code by eliminating the need to manage multiple loops. Finally, using a single IOLoop makes debugging easier, since all of the events are handled in one place.