Concurrency Tutorial

Concurrency is a crucial concept in programming that allows multiple tasks to be executed simultaneously. It can greatly enhance the performance and responsiveness of applications. In this tutorial, we will explore the basics of concurrency and some common techniques used in modern programming languages.

Understanding Concurrency

Concurrency refers to the ability of a computer system to execute multiple tasks at the same time. This is different from parallelism, which involves executing multiple tasks on multiple processors or cores.

Types of Concurrency

• Thread-based: Using threads to execute multiple tasks concurrently.
• Process-based: Creating multiple processes to achieve concurrency.
• Event-driven: Using events and callbacks to handle asynchronous operations.

Common Techniques

• Mutexes: Synchronize access to shared resources.
• Semaphores: Allow a certain number of threads to access a resource simultaneously.
• Condition Variables: Coordinate the execution of threads based on certain conditions.

Example

To illustrate concurrency, let's look at a simple example using threads in Python:

import threading

def print_numbers():
    for i in range(5):
        print(f"Number {i} is printed by Thread {threading.current_thread().name}")

# Create and start threads
thread1 = threading.Thread(target=print_numbers, name="Thread-1")
thread2 = threading.Thread(target=print_numbers, name="Thread-2")

thread1.start()
thread2.start()

# Wait for threads to complete
thread1.join()
thread2.join()

For more detailed examples and further reading, check out our Concurrency Examples.

Concurrency