When working with embedded devices, it is often necessary to measure the execution time of a program. This can be useful for optimizing code, identifying bottlenecks, or simply understanding the performance of the device. In this article, we will explore three different ways to calculate the program execution time in Python for an embedded device.

Option 1: Using the time module

The simplest way to measure program execution time is by using the time module in Python. This module provides a function called time() that returns the current time in seconds since the epoch. By calling this function before and after the code we want to measure, we can calculate the difference to get the execution time.

import time

start_time = time.time()

# Code to measure execution time

end_time = time.time()
execution_time = end_time - start_time

print("Execution time:", execution_time)

This method is simple and straightforward, but it may not be very accurate for measuring short execution times. The time() function has a resolution of about 1 microsecond, which means that it may not be able to accurately measure very short execution times.

Option 2: Using the timeit module

If we need more accurate measurements, we can use the timeit module in Python. This module provides a Timer class that allows us to time the execution of a specific piece of code. The Timer class automatically repeats the code multiple times to get a more accurate measurement.

import timeit

code_to_measure = '''
# Code to measure execution time
'''

execution_time = timeit.timeit(code_to_measure, number=1)

print("Execution time:", execution_time)

This method is more accurate than using the time module, as it repeats the code multiple times and calculates the average execution time. However, it may not be suitable for measuring very long execution times, as it can take a significant amount of time to repeat the code multiple times.

Option 3: Using the perf_counter function

If we need the highest level of accuracy, we can use the perf_counter function from the time module. This function returns a floating-point value representing a clock with the highest available resolution on the system.

import time

start_time = time.perf_counter()

# Code to measure execution time

end_time = time.perf_counter()
execution_time = end_time - start_time

print("Execution time:", execution_time)

This method provides the highest level of accuracy for measuring execution time. However, it may not be available on all systems, as it relies on the system’s clock with the highest available resolution.

After exploring these three options, it is clear that the best option depends on the specific requirements of the embedded device and the desired level of accuracy. If accuracy is not critical and short execution times need to be measured, option 1 using the time module is a simple and effective choice. If more accurate measurements are required, option 2 using the timeit module is a good choice. Finally, if the highest level of accuracy is needed and the system supports it, option 3 using the perf_counter function is the best choice.