How to Implement Delays Using Python WAIT Function

A Complete Guide to Implementing Waits in Python Using Sleep, Asyncio, Threading, and Subprocesses

Sometimes, your code should do nothing more than wait. You may need to limit API calls or synchronize background operations; in such cases, implementing a delay can be a wise decision.

In this article, I'll walk you through four different methods that Python uses to handle "waiting," ranging from simple pauses to managing threads and subprocesses.

What Does "Python Wait" Mean?

Python purposefully stops execution when it waits. However, there can be wide variations in what causes that stop and what happens during its waiting period.

A task may be delayed for several seconds, or it may need to wait for approval from another thread or process before continuing. Waiting might include more than just time; it can also involve focus, control, or coordination.

Python provides multiple ways to wait, and we’ll begin with a simple example to introduce this topic: a fixed-time delay using time.sleep().

Comparison Table: Python Wait Methods

Python Wait Method 1: Using time.sleep() for Simple Delays

The most straightforward approach to postponing execution is to use Python's time.sleep() function. It's ideal for simple waiting scenarios because it actually stops your program for a specific period of time.

As you've already seen, there are many reasons why delays may take place. time.sleep() requires no setup when you're simply spacing out operations, such as API requests, animations, or user input.

How does it work?

Let’s see an example. After moving on to the next phase, we'll write a Python script that will wait for three seconds. This is what is going to happen:

1. The active thread stops immediately.
2. During sleep, Python doesn't respond to input or run other programs.
3. Execution continues from the following line after the time limit has expired.

Let’s see the code.

import time

print("Waiting for 3 seconds...")
time.sleep(3)
print("Done waiting.")

Here is the immediate output.

Python continues exactly where it left off after the wait is over. Here is the entire output.

This is a simple, blocking delay that is ideal when your application has no other tasks to perform during the wait.

Python Wait Method 2: Using asyncio.sleep() in Asynchronous Code

Blocking your code over time when it runs asynchronously, sleep() may be less helpful than useful. Instead, Python's asyncio module offers non-blocking wait techniques, which are ideal for performing multiple tasks concurrently. When programming asynchronously, you don't want to "pause everything." Your objective is to pause one task while allowing others to continue.

How does it work?

Let's look at an actual case study. We are going to build an async function that waits to do something without stopping the event loop. What's going to happen is this:

1. An async task starts and writes a message to say so.
2. After that, it uses await asyncio to stop just that coroutine.
3. Other async jobs can still run while we wait, if they are present.
4. It writes one last message and ends execution after the wait.

Let's look at the code.

import asyncio

async def wait_and_print():
    print("Async wait started...")
    await asyncio.sleep(3)
    print("Async wait finished.")

await wait_and_print()

Here is the immediate output.

Here is the entire output.

This non-blocking delay allows other asynchronous operations to go on while the coroutine remains inactive in the background.

Python Wait Method 3: Synchronizing Threads with threading.Event().wait()

So far, you have seen how to delay tasks in simple and asynchronous scenarios. What if there is more than one thread going at the same time, and one needs to wait until another important thread is done?

Python’s threading.Event().wait() provides a way to block a thread until a signal is received. Unlike time.sleep(), it's not about time; it's about getting threads to work together.

How does it work?

Let's break it down with a real-life example.

This is what you're going to build:

• A thread is awaiting a signal
• Following a little sleep, that signal is transmitted by another thread
• Once the signal is received, the waiting thread starts working again

This lets threads communicate regarding time, which matters for many real-world tasks like processing files or task queues.

import threading
import time

# Create an event object
event = threading.Event()

def wait_for_signal():
    print("Thread 1: Waiting for event to be set...")
    event.wait()  # Wait until the event is set
    print("Thread 1: Event received, continuing execution.")

def send_signal():
    print("Thread 2: Sleeping for 3 seconds before setting event...")
    time.sleep(3)
    event.set()
    print("Thread 2: Event is set.")

# Start both threads
t1 = threading.Thread(target=wait_for_signal)
t2 = threading.Thread(target=send_signal)

t1.start()
t2.start()

t1.join()
t2.join()

Here is the immediate output..

Here is the full response.

This delay is different from others because it doesn't depend on a set timer in the waiting thread. The wait stops when the other thread does, not when it starts. Because of this, it works well when the timing is uncertain but externally controlled.

Python Wait Method 4: Waiting for External Programs with subprocess.wait()

You've seen how Python can wait inside of its own threads or coroutines so far. Sometimes, though, your code starts a whole new process, and you have to wait until that external task is done. This is where you have to use subprocess waiting.

How does it work?

Let's look at a clear picture from real life. This is what the code does:

1. Start a background process that runs a short Python script.
2. It prints a message, takes three seconds, and then prints it again.
3. At the same time, the main script stops running by using.communicate(), which internally includes wait().
4. When the subprocess is done, the main script copies its result and shows it.

You can see both the wait and what you were waiting for this way. Here is the code.

import subprocess

print("Main process: Launching a subprocess...")

# Start a subprocess and capture its output
process = subprocess.Popen(
    ["python", "-c", "import time; print('Subprocess: Starting...'); time.sleep(3); print('Subprocess: Finished.')"],
    stdout=subprocess.PIPE,
    stderr=subprocess.PIPE,
    text=True
)

# Wait for it to finish and get output
stdout, stderr = process.communicate()

print("Main process: Subprocess output:")
print(stdout.strip())
print("Main process: Subprocess is done.")

Here is the immediate output.

Here is the entire output.

Here, the extra program runs independently. Python just waits in the background and pauses until that program finishes. Use this way when you need to run other tools, compilers, or scripts.

Quick Takeaways on Python Wait Methods

• Use time.sleep() when you need some time off and take part in no other tasks.
• Use await asyncio.sleep() if your code is asynchronous and requires non-blocking waits.
• Use threading.Event().wait() when your program must pause while a task on another thread is completed.
• Use subprocess.wait() when you need to pause until another program or script finishes running.

Final Thoughts

In Python, waiting is not just wasted time. It is often where stability, coordination, and accuracy are achieved. You now know four different ways to make your program wait: using time.sleep() for simple delays, asyncio.sleep() for non-blocking pauses in asynchronous code, threading.Event().wait() for coordinating between threads, and subprocess.wait() for holding execution until an external program finishes.

By understanding these methods, you can choose the right approach for your situation, whether you are slowing down requests, managing multiple tasks at once, synchronizing threads, or waiting for external tools to complete. If you are preparing for technical interviews, reviewing common Python interview questions can also help you strengthen your knowledge of these concepts.