Is python's asynchronous faster than nodejs?

Python and Node.js are two popular programming languages, both of which support asynchronous programming. Asynchronous programming is a form of programming that allows the program to avoid waiting for an operation to complete before proceeding to the next operation, thereby improving the execution efficiency of the program. But which one is faster, Python’s asynchronous programming or Node.js?

First, let us understand how asynchronous programming is implemented in Python and Node.js. Node.js uses an event-driven single-threaded model, which uses an event loop mechanism to implement asynchronous programming. In Node.js, when an asynchronous operation completes, an event is added to the event queue, and the event loop continuously removes and executes events from the event queue.

Python’s asynchronous programming uses a coroutine-based multi-threading model, which uses a coroutine scheduler to implement asynchronous programming. Coroutines are lightweight threads that can run multiple coroutines simultaneously in one thread, thus avoiding the overhead caused by thread switching.

Theoretically, Python’s asynchronous is faster than Node.js. Because in Node.js, all events are executed serially, while in Python, multiple coroutines can be executed at the same time, thus making better use of CPU resources. In addition, Python's coroutines are more lightweight than Node.js events, and coroutine switching is less expensive, so tasks can be switched and executed faster.

However, in fact, Python’s asynchronous programming is not necessarily faster than Node.js. This is because Python's coroutine scheduler requires frequent context switching. If there are too many coroutines, the overhead of the scheduler will become very large, resulting in performance degradation. In Node.js, the event loop mechanism can better manage the number of events and avoid the occurrence of too many events.

In addition, Node.js has a more complete encapsulation of IO operations and is more suitable for IO-intensive application scenarios than Python. Python is more suitable for CPU-intensive application scenarios. If you want to develop a web application that needs to handle a lot of IO, then Node.js will be a better choice. And if you need to perform calculation-intensive operations such as data analysis and machine learning, then Python's asynchronous programming may be more suitable.

To sum up, Python’s asynchronous programming is faster in theory than Node.js. However, in specific application scenarios, which language to choose needs to be chosen based on actual needs.

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