Concurrency Basics

Concurrency, in the context of computer science, refers to the ability of a system to execute multiple tasks simultaneously. This is a crucial concept in modern software development, especially as applications become more complex and require handling multiple operations at once.

Key Concepts

  • Parallelism: The execution of two or more tasks at the same time.
  • Concurrency: The execution of two or more tasks by a single processor in interleaved fashion.
  • Thread: A thread of execution within a process.
  • Lock: A synchronization mechanism used to ensure that only one thread can access a resource at a time.

Types of Concurrency

  • CPU-bound: Tasks that are limited by the processing power of the CPU.
  • IO-bound: Tasks that are limited by the speed of input/output operations.

Benefits of Concurrency

  • Improved performance: By executing tasks concurrently, the system can make better use of available resources.
  • Better responsiveness: Applications can remain responsive even when performing time-consuming tasks.

Challenges

  • Complexity: Concurrency introduces complexity into the system, making it harder to design and maintain.
  • Race conditions: When two or more threads access the same resource concurrently, it can lead to race conditions, where the outcome depends on the order of execution.

Example

Here is a simple example of a concurrent program in Python:

import threading

def print_numbers():
    for i in range(1, 6):
        print(i)

thread1 = threading.Thread(target=print_numbers)
thread2 = threading.Thread(target=print_numbers)

thread1.start()
thread2.start()

thread1.join()
thread2.join()

Further Reading

For more information on concurrency, you might want to check out our Concurrency Deep Dive guide.

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