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Multithreading & Multiprocessing · Lesson 51 of 56

Multithreading Basics

Source: 16-Multithreading and Multiprocessing/multi_threading.py

Start here — no coding background needed

What you will learn

Concept: multiple tasks interleaved on one CPU — feels parallel.

In simple words

Like chatting while music plays — switches fast between tasks.

Do many tasks at once — advanced; understand ideas first, code locally later.

Easy example — try this first

Easy example — run this first. Change values and press Run again.

Python

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference notes (from full bootcamp)

Optional — deeper detail for when you are ready

Reference script from the bootcamp repo. Read the code below; run a simplified version in the playground when marked runnable.

Example HCL
HCL
### Multithreading
## When to use Multi Threading
###I/O-bound tasks: Tasks that spend more time waiting for I/O operations (e.g., file operations, network requests).
###  Concurrent execution: When you want to improve the throughput of your application by performing multiple operations concurrently.

import threading
import time

def print_numbers():
    for i in range(5):
        time.sleep(2)
        print(f"Number:{i}")

def print_letter():
    for letter in "abcde":
        time.sleep(2)
        print(f"Letter: {letter}")

##create 2 threads
t1=threading.Thread(target=print_numbers)
t2=threading.Thread(target=print_letter)

t=time.time()
## start the thread
t1.start()
t2.start()

### Wait for the threads to complete
t1.join()
t2.join()

finished_time=time.time()-t
print(finished_time)

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Practice test — try yourself

Write code, press Check. Wrong answer shows the correct code to copy & run.

You learned "Multithreading Basics". Use print() to show: Done: Multithreading Basics

Hint: Use one print() with the exact text.

Python