What is threading

Threading refers to the process of executing multiple threads (also known as lightweight processes) concurrently within a single program. A thread is a sequential flow of control within a program, and each thread can run independently of other threads, allowing for the simultaneous execution of multiple tasks.

In Python, to run specific code in a thread, that code has to be in a function.

For example,

import time

def run():
    time.sleep(1) # Heavy computation
    print("Heavy computation completed")

Generally, this code may be some heavy task that we will want to complete so for this case, I will simulate that by waiting for 1 second.

Python comes with a built-in module that allows you to use threading without any installation.

import threading

To create a thread, we use the threading.Thread function and it takes some arguments which I will be covering just three.

1. target: The function to be run in the thread

2. args: A tuple of arguments to be passed in that function

3. daemon: If is set to True, the thread stops when the code exits (Whether the thread has finished or not)

import threading
import time

def run():
    time.sleep(1) # Heavy computation
    print("Heavy computation completed")

t = threading.Thread(target=run)
t.start()
print("Ended")

Output:

Ended
Heavy computation completed

If other variables like args and daemon are passed in, the code will look like this

def run(n):
    import time
    time.sleep(n) # Heavy computation
    print("Heavy computation completed")

threading.Thread(target=run, args=(1,), daemon=True)
print("Ended")

Note: Make sure the args variable is a tuple.

Output:

Ended

The "Heavy computation completed" was not printed because it didn't run before the code ended.

Conclusion

Python threading is a powerful tool for achieving concurrency and parallelism in our programs. By using the built-in threading module, we can create and manage multiple threads that can execute simultaneously, improving program performance. With threading, we can create faster, more efficient programs that take full advantage of modern hardware.