Python Tornado Interview & Exam Practice Questions

Master asynchronous Python with 150+ detailed Tornado practice questions and real-world explanations.

Python Tornado is the premier choice for developers who need to build high-performance, long-poll, and WebSocket-based applications, and this comprehensive practice test suite is designed to bridge the gap between basic coding and enterprise-grade mastery. Whether you are preparing for a senior backend interview or aiming to solidify your understanding of non-blocking I/O, these questions dive deep into the IOLoop architecture, asynchronous request handling, and the nuances of the tornado.gen module. You will explore everything from standard RESTful routing and template engines to advanced concepts like managing backpressure in persistent connections, securing applications with XSRF protection, and scaling across multiple cores using tornado.process. By working through these scenarios, you’ll gain the confidence to troubleshoot blocked event loops and optimize production environments behind Nginx, ensuring you are ready for any technical challenge.

Exam Domains & Sample Topics

Asynchronous Engine: IOLoop, await/yield patterns, and the mechanics of Future objects.
Request Lifecycle: RequestHandler logic, asynchronous decorators, and UI Modules.
Scalability: Multi-processing, concurrent.futures, and non-blocking caching strategies.
Real-time Protocols: WebSockets, Long Polling, and TCPServer implementation.
Production & Security: Secure cookies, JWT, AsyncHTTPTestCase, and monitoring.

Sample Practice Questions

Q1: Which of the following is the most efficient way to execute a CPU-bound task in a Tornado application without blocking the main IOLoop?

A. Run the task using a standard time.sleep() within the handler. B. Use yield with a standard synchronous function call. C. Offload the task to a ThreadPoolExecutor and await the result. D. Wrap the CPU-intensive code in a tornado.gen.coroutine. E. Call the function directly inside the get() method of a RequestHandler. F. Increase the number of IOLoop instances in a single thread.

Correct Answer: C

Overall Explanation: Tornado is single-threaded; any operation that occupies the CPU for a significant amount of time will "block" the event loop, preventing it from handling other incoming requests. Offloading these tasks to a separate thread or process is the standard way to maintain responsiveness.

Option A Incorrect: time.sleep() is synchronous and will stop the entire event loop for all users.
Option B Incorrect: yield or await only works for non-blocking objects (like Futures); calling a sync function with them doesn't make it asynchronous.
Option C Correct: This allows the CPU work to happen on a different thread, returning a Future that Tornado can monitor without stopping the loop.
Option D Incorrect: Coroutines simplify syntax but they don't magically make blocking CPU-bound code non-blocking.
Option E Incorrect: Calling it directly is the definition of "blocking the loop."
Option F Incorrect: A single thread can only have one active IOLoop; you cannot run multiple effectively to solve CPU blocking within that same thread.

Q2: When implementing a WebSocketHandler in Tornado, which method is specifically used to handle the initial handshake before the connection is upgraded?

A. on_message B. open C. check_origin D. on_close E. prepare F. data_received

Correct Answer: C

Overall Explanation: Security is paramount in WebSockets. Tornado provides a specific hook to validate the Origin header of the request to prevent Cross-Site WebSocket Hijacking (CSWH).

Option A Incorrect: This is triggered when a message is received after the connection is established.
Option B Incorrect: This is called once the WebSocket connection has been successfully opened.
Option C Correct: check_origin is executed during the handshake; returning False here will reject the connection.
Option D Incorrect: This is called after the connection has been terminated.
Option E Incorrect: While prepare is called before the handler runs, check_origin is the domain-specific method for WebSocket handshake security.
Option F Incorrect: This is a low-level method for streaming data, not specifically for the handshake logic.

Q3: What is the primary purpose of the @tornado.web.asynchronous decorator in older Tornado versions (pre-4.0/Python 3.5)?

A. It automatically converts a function into a Python thread. B. It prevents the RequestHandler from automatically finishing the request when the method returns. C. It enables automatic XSRF token generation for the decorated method. D. It speeds up database queries by 20%. E. It forces the IOLoop to prioritize that specific request. F. It is required to use the self.render() method.

Correct Answer: B

Overall Explanation: In older versions of Tornado, the framework assumed the request was finished as soon as the get() or post() method returned. If you were performing an async task, you needed this decorator to keep the connection open until self.finish() was called manually.

Option A Incorrect: Tornado does not use decorators to turn functions into threads.
Option B Correct: It tells Tornado "don't close the connection yet, I'm still doing work asynchronously."
Option C Incorrect: XSRF is handled via application settings, not this decorator.
Option D Incorrect: Decorators do not have a direct numerical impact on database speed.
Option E Incorrect: It does not affect IOLoop prioritization or scheduling.
Option F Incorrect: self.render() can be used in both synchronous and asynchronous handlers.

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