![]() Reactive Programming is a subset of Asynchronous Programming, which triggers code execution reactively, when data is presented, regardless of whether the function supposed to process it is already busy. In Asynchronous Programming - if a Function A calls Function B, regardless of its dependence of the result from Function B, both can execute at the same time, and if need be, wait for the other one to finish to utilize each other's results. In Synchronous Programming - if a Function A calls Function B, it stops execution until Function B finishes execution, after which Function A can resume. ![]() Asynchronous and Reactive ProgrammingĪsynchronous Programming revolves around parallel execution - where a task can be executed and finished independent of the main flow. Once it starts, you can't externally cancel it without terminating the entire program or if you cause the sleep() method itself to throw an exception, which would halt it. Additionally, this make it unfit for Asynchronous and Reactive Applications, which oftentimes require real-time data and feedback.Īnother thing to note about time.sleep() is the fact that you can't stop it. This makes it unfit for longer waiting times, as it clogs up the thread of the processor during that time period. It seizes up the thread it's on and blocks it for the duration of the sleep. However, there's one major downside to the time.sleep() function, very noticeable in multi-threaded environments. Though, keep in mind that with 2 decimal places, the sleep duration might not be exactly on spot, especially since it's hard to test, given the fact that the print() statements take some (variable) time to execute as well. If you'd like to sleep for less than 1 second, you can easily pass non-whole numbers as well: print(().time()) Quite clearly, we can see a 5s delay between the two print() statements, with a fairly high precision - down to the second decimal place. It accepts the number of seconds you'd like the process to sleep for - unlike many other languages that are based in milliseconds: import datetime One of the most common solutions to the problem is the sleep() function of the built-in time module. In this article, we'll take a look at how to delay code execution in Python - also known as sleeping. In a sense, code delay can technically become code scheduling with a valid loop and termination condition - assuming that the delay mechanism in place isn't blocking. Alternatively, they might write a script that checks if the website has anything new on it. To allow for breathing space, as well as to make sure we don't negatively impact either the users of the website or the website itself - we'd limit the number of requests sent by delaying each one.Ī student, waiting for exam results might furiously refresh their school's website, waiting for news. Many requests, fired in rapid succession can, depending on the server in question, quickly take up all of the free connections and effectively become a DoS Attack. For example, while web scraping (ethically), and following the ToS of the website in question, abiding by the robots.txt file - you might very well want to delay the execution of each request so as to not overwhelm the resources of the server. In multi-threaded systems, a thread might want to wait for another thread to finish an operation, to continue working with that result.Īnother example could be lessening the strain on a server we're working with. ![]() ![]() The most common need for code delaying is when we're waiting for some other process to finish, so that we can work with the result of that process. Code Delaying (also known as sleeping) is exactly what the name implies, the delaying of code execution for some amount of time. ![]()
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