Repeat python function with precise time stamp

2 min read 24-09-2024

Repeat python function with precise time stamp

In many scenarios, you may need to execute a Python function at precise intervals or specific times. This is particularly useful for tasks such as scheduling automated reports, running background jobs, or performing periodic data processing. In this article, we’ll explore how to achieve that using Python's built-in libraries.

Original Problem

Here is the original code snippet that may be causing some confusion:

import time

def repeat_function():
    while True:
        print("Function executed")
        time.sleep(1)

This code executes repeat_function continuously every second. However, it's important to note that using time.sleep(1) doesn’t guarantee that the function will run at precise intervals because any delays in execution or processing may affect the timing.

Understanding the Problem

The goal is to execute a function at precise time intervals rather than merely running it continuously every second. Let’s transform this into a more precise version that can account for execution time.

Optimized Code for Precise Execution

We can optimize our initial function using the time module while ensuring that our function executes at precise timestamps. Here's an improved version:

import time

def repeat_function():
    start_time = time.time()
    interval = 1  # interval in seconds

    while True:
        current_time = time.time()
        elapsed_time = current_time - start_time

        if elapsed_time >= interval:
            print("Function executed at", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))
            start_time = current_time  # reset the start time

Analysis of the Improved Code

Precision: This version calculates the elapsed time since the last execution and only executes the function when the specified interval has passed. This minimizes the drift caused by function execution time.
Timestamping: The code uses time.strftime() to format the current local time, making it easier to understand when the function was executed.
Endless Loop: The loop continues indefinitely, executing the function every second (or whatever interval you set), which is ideal for repeated tasks that need to run in the background.

Practical Example

Suppose you want to log the system's CPU usage every 5 seconds. You can modify the function like this:

import time
import psutil  # You might need to install this package

def log_cpu_usage():
    start_time = time.time()
    interval = 5  # Log every 5 seconds

    while True:
        current_time = time.time()
        elapsed_time = current_time - start_time

        if elapsed_time >= interval:
            cpu_usage = psutil.cpu_percent()
            print(f"CPU Usage logged at {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())}: {cpu_usage}%")
            start_time = current_time

Additional Explanations

Library Usage: The psutil library is utilized here to gather system information. You can install it using pip install psutil.
Scalability: This approach is easy to adapt. You can change the interval variable to any number of seconds based on your needs.
Resource Management: Remember that while this method is efficient for a few repeated tasks, it's not ideal for a large number of functions due to Python's Global Interpreter Lock (GIL) affecting concurrent executions.

Conclusion

Using a precise timestamp to repeat a function in Python can enhance your scripts significantly, especially for tasks requiring regular execution. The enhanced approach provided above is a robust solution to keep your tasks running on schedule while reducing timing errors caused by execution delays.

Useful Resources

By following the practices laid out in this article, you can ensure that your functions run precisely when you need them to!