Python Timer Functions: Three Ways to Monitor Your Code

While many developers recognize Python as an effective programming language, pure Python programs may run more slowly than their counterparts in compiled languages like C, Rust, and Java. In this tutorial, you’ll learn how to use a Python timer to monitor how quickly your programs are running.

In this tutorial, you’ll learn how to use:

• time.perf_counter() to measure time in Python
• Classes to keep state
• Context managers to work with a block of code
• Decorators to customize a function

You’ll also gain background knowledge into how classes, context managers, and decorators work. As you explore examples of each concept, you’ll be inspired to use one or several of them in your code, for timing code execution, as well as in other applications. Each method has its advantages, and you’ll learn which to use depending on the situation. Plus, you’ll have a working Python timer that you can use to monitor your programs!

Python Timers

First, you’ll take a look at some example code that you’ll use throughout the tutorial. Later, you’ll add a Python timer to this code to monitor its performance. You’ll also learn some of the simplest ways to measure the running time of this example.

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Python Timer Functions

If you check out the built-in time module in Python, then you’ll notice several functions that can measure time:

• monotonic()
• perf_counter()
• process_time()
• time()

Python 3.7 introduced several new functions, like