Welcome to the Python Tutorials section on parallel programming. In this article, we will delve into the basics of parallel programming and how it can be effectively implemented in Python.

Parallel programming is a key concept in modern computing, allowing for the execution of multiple tasks simultaneously. This can lead to significant performance improvements in applications that are computationally intensive.

What is Parallel Programming?

Parallel programming involves breaking down a large task into smaller subtasks that can be executed concurrently. This can be achieved using various techniques such as multi-threading, multi-processing, and distributed computing.

Multi-threading

Multi-threading is a technique that allows multiple threads of execution to run concurrently within the same process. In Python, the threading module provides a simple way to create and manage threads.

Multi-processing

Multi-processing is another technique that allows multiple processes to run concurrently. This can be more effective than multi-threading in Python due to the Global Interpreter Lock (GIL), which prevents multiple native threads from executing Python bytecodes at once.

The multiprocessing module in Python provides tools for creating and managing processes.

Distributed Computing

Distributed computing involves executing tasks across multiple machines. This can be achieved using frameworks such as Apache Hadoop and Spark.

Parallel Programming in Python

Python has several libraries that can be used for parallel programming:

  • concurrent.futures: This module provides a high-level interface for asynchronously executing callables.
  • multiprocessing: As mentioned earlier, this module provides tools for creating and managing processes.
  • threading: This module provides a simple way to create and manage threads.

Example: Multi-threading in Python

Here's a simple example of multi-threading in Python:

import threading

def print_numbers():
    for i in range(1, 11):
        print(i)

# Create two threads
thread1 = threading.Thread(target=print_numbers)
thread2 = threading.Thread(target=print_numbers)

# Start the threads
thread1.start()
thread2.start()

# Wait for the threads to finish
thread1.join()
thread2.join()

This example creates two threads that print numbers from 1 to 10.

Learn More

If you're interested in learning more about parallel programming in Python, we recommend checking out the following resources:

Concurrency