Python Sleep Milliseconds(ms) with examples

💡 Outline
You can use time.sleep() method to sleep for milliseconds in Python.
If you want to delay python program by 500 ms, then you need to pass 0.5 as parameter to sleep method.

Using time's sleep method

import time time.sleep(0.5)

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import time time.sleep(0.5)

1. Introduction

Sometimes, the execution of a program needs to be suspended or paused for a given time. This is done so that the user can understand the whole program and plan the future steps of the program accordingly. In python, there is a provision by which execution of the current thread can be stopped for some time.

This tutorial will demonstrate some methods by which a program can sleep or stop its execution for some milliseconds in Python.

2. Using time.sleep() Method

To sleep for milliseconds in Python:

• Import time module.
• Convert milliseconds to seconds by multiplying with 0.001.
• Pass converted seconds to time.sleep() method to sleep for milliconds in Python.

Example:

Output:

In this method, we used Python’s time() module which helps in dealing with time in python and represents in the form of an object, a number, or even a string. This module also helps in measuring the execution speed and efficiency of the code.

time module provides a function called time.sleep() that takes a number of seconds as an input and pauses the program for that duration.

Now, as we know that there are 1000 milliseconds in one second, so we need to convert if the input time is in milliseconds. For converting milliseconds to seconds, we multiply the given number of milliseconds by 0.001.

Note that we have converted the input time and we have stored the converted time in the variable called time_sec variable. After that, we have used only the time_sec variable for suspending the execution of the current code using the sleep() function.

Please note that sleep time may be slightly longer than the specified time, depending on operating system and load. This is because the function relies on the underlying system clock, which may not have a high enough resolution or accuracy to measure milliseconds precisely.

Therefore, sleeping for milliseconds in Python using time.sleep() may not be suitable for all situations, especially if the program requires high precision, reliability, or concurrency. In such cases, alternative methods may be preferable, such as using time.perf_counter() to measure elapsed time, using asyncio or threading modules to create non-blocking tasks, or using multiprocessing or concurrent.futures modules to run parallel processes.

These methods can provide more control and flexibility over the timing and execution of the program, but they may also introduce more complexity and overhead. Therefore, the choice of the best method depends on the specific needs and goals of the program.

3. Using threading.Timer() Method to Make the Program Sleep for Milliseconds

The threading module helps in creating, managing, and controlling threads in Python. There are different objects and functions in this module to perform these tasks.

threading.timer() module provides a class called Timer that can execute a function after a given number of seconds.The constructor of timer takes two arguments: the delay in seconds and function to call

We can create a timer object that will run function after elapsed time. We need to start timer thread by calling start() method on timer object.

For example, the following code creates a timer that prints “Hello World” after 0.5 seconds:

Output:

Explanation

• Defined a function in which we have printed message.
• We created timer object by passing time for sleep in milliseconds(ms) and function name somefunction as argument.
• Called start() on timer object to start the thread.

Note: We can also deal with multiple threads in the same code and set the execution time of each thread individually using the threading module. This process is called multithreading.

4. Conclusion

In this article, we have explored two ways to sleep for milliseconds in Python. time.sleep() works great in case we don’t need exact precision.