Concurrency vs Parallelism

Learn the fundamental distinction between concurrency and parallelism - two related but different concepts that are often confused.

Key Differences

🔄 Concurrency

Dealing with multiple things at once. Tasks may appear to run simultaneously but actually alternate execution.

Example: Single-core CPU handling multiple tasks through time-slicing

⚡ Parallelism

Actually doing multiple things simultaneously. Tasks execute at the same time on different processing units.

Example: Multi-core CPU executing different tasks on different cores

💡 Key Insight

Concurrency is about dealing with lots of things at once. Parallelism is about doing lots of things at once. You can have concurrency without parallelism, but parallelism always involves concurrency.

Practical Examples

🔄 Concurrency Example: Web Server

# Single-threaded but concurrent handling
import asyncio
import aiohttp

async def handle_request(request):
    # While waiting for database, other requests can be processed
    data = await database.fetch(request.user_id)
    return response(data)

# Handles 1000s of concurrent connections on single thread

⚡ Parallelism Example: Image Processing

# Truly parallel execution
from multiprocessing import Pool

def process_pixel(pixel_data):
    return apply_filter(pixel_data)

# Each core processes different pixels simultaneously
with Pool() as pool:
    results = pool.map(process_pixel, image_pixels)