Perf_counter() measures the time in seconds from some unspecified moment in time, which means that the return value of a single call to the function isn’t useful. Again, this is a performance counter that’s well-suited for timing parts of your code. Now you’ll add a bare-bones Python timer to the example with time.perf_counter(). The code may take a little while to run depending on your network, so you might want to use a Python timer to monitor the performance of the script. In this tutorial, you'll learn how to use a Python timer to monitor how quickly your programs are running. 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. # Python Timer Functions: Three Ways to Monitor Your Code You can install realpython-reader on your system with pip: To learn more about the Real Python Reader and how it works, check out How to Publish an Open-Source Python Package to PyPI. The example that you’ll use in this tutorial is a short function that uses the realpython-reader package to download the latest tutorials available here on Real Python. If you already have code that you’d like to measure, then feel free to follow the examples with that instead. To better compare the different ways that you can add a Python timer to your code, you’ll apply different Python timer functions to the same code example throughout this tutorial. Later, you’ll compare this with other Python timer functions and learn why perf_counter() is usually the best choice. ( Source)įirst, you’ll use perf_counter() to create a Python timer. a clock with the highest available resolution to measure a short duration. Return the value (in fractional seconds) of a performance counter, i.e. For now, note what the documentation has to say about perf_counter(): You’ll learn more about these functions later. For example, perf_counter_ns() is the nanosecond version of perf_counter(). Python 3.7 introduced several new functions, like thread_time(), as well as nanosecond versions of all the functions above, named with an _ns suffix. Time to run the main Python script: 7.If you check out the built-in time module in Python, then you’ll notice several functions that can measure time: Print('Time to run the main Python script: ' + str(executionTime_2))Īnd here is the final result: Time to import modules: 0.3277866840362549 Print('Time to import modules: ' + str(executionTime_1))ĮxecutionTime_2 = (time.time() - startTime_2) For example, you may want to separately measure the time it takes to:ĮxecutionTime_1 = (time.time() - startTime_1) Optionally, you may break down the time it takes to run each portion of the code. Here you should get a slightly lower run time: Execution time in seconds: 7.2620604038238525 Run the main Python script to generate the random integers and then convert them to stringsĪlternatively, you may check how long it takes to run the main Python script, excluding the time it takes to import both the Pandas and the NumPy modules: import pandas as pd.Import both the Pandas and the NumPy modules and.You may have noticed that in the above code we measured the time it took to: Here is an example of the time it took to run the above script: Execution time in seconds: 7.513572454452515 You may now use the following approach to measure the time to run the script: import timeįor our example, you may apply the following syntax in Python (make sure that both the Pandas and NumPy modules are installed first): import time Step 2: Measure the Time to Run the Python Script The ultimate goal is to measure the time it takes to run the above script. Steps to Measure the Time it Takes to Run a Python Script Step 1: Write the Python Scriptįor illustration purposes, let’s write a Python script that: Next, you’ll see the steps to apply the above approach in practice. Print('Execution time in seconds: ' + str(executionTime)) You may use the time module in order to measure the time it takes to run a Python script: import timeĮxecutionTime = (time.time() - startTime)
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