Multiprocessing vs Multithreading di Python: Panduan Lengkap

Concurrency dan parallelism adalah konsep penting dalam programming modern untuk meningkatkan performa aplikasi. Python menyediakan dua pendekatan utama: multithreading dan multiprocessing. Dalam tutorial ini, kita akan mempelajari perbedaan keduanya, kapan menggunakan masing-masing, dan bagaimana mengimplementasikannya dengan efektif.

Konsep Dasar

Threading

• Lightweight (ringan)
• Berbagi memory space
• Context switching lebih cepat
• Cocok untuk I/O-bound tasks

Multiprocessing

• Heavyweight (lebih berat)
• Memory space terpisah
• True parallelism
• Cocok untuk CPU-bound tasks

Global Interpreter Lock (GIL)

Apa itu GIL?

GIL adalah mutex (mutual exclusion lock) yang melindungi akses ke Python objects, mencegah multiple threads mengeksekusi Python bytecode secara bersamaan.

import threading
import time

CPU-bound task
def cpuintensive():

    count = 0
    for i in range(50000000):

        count += 1
    return count

Single thread
start = time.time()
cpuintensive()
cpuintensive()

end = time.time()
print(f"Single thread: {end - start:.2f}s")

Multi-threading (TIDAK lebih cepat karena GIL!)
start = time.time()
t1 = threading.Thread(target=cpuintensive)
t2 = threading.Thread(target=cpuintensive)

t1.start()
t2.start()
t1.join()
t2.join()
end = time.time()
print(f"Multi-threading: {end - start:.2f}s")

Single thread: 3.45s
Multi-threading: 3.52s  # Tidak ada speedup!

import threading
import requests
import time

urls = [
    'https://jsonplaceholder.typicode.com/posts/1',
    'https://jsonplaceholder.typicode.com/posts/2',
    'https://jsonplaceholder.typicode.com/posts/3',
    'https://jsonplaceholder.typicode.com/posts/4',
    'https://jsonplaceholder.typicode.com/posts/5',
]

def download(url):
    """Download content dari URL"""
    response = requests.get(url)
    print(f"Downloaded {url}: {len(response.content)} bytes")

Sequential (tanpa threading)
start = time.time()
for url in urls:
    download(url)
sequentialtime = time.time() - start
print(f"\nSequential: {sequentialtime:.2f}s")


Multi-threading
start = time.time()
threads = []
for url in urls:
    thread = threading.Thread(target=download, args=(url,))
    threads.append(thread)
    thread.start()

for thread in threads:
    thread.join()

threadedtime = time.time() - start
print(f"Multi-threading: {threadedtime:.2f}s")

print(f"Speedup: {sequentialtime/threadedtime:.2f}x")

Downloaded https://jsonplaceholder.typicode.com/posts/1: 292 bytes
Downloaded https://jsonplaceholder.typicode.com/posts/2: 293 bytes
...

Sequential: 2.45s
Multi-threading: 0.62s
Speedup: 3.95x  # Significant speedup!

import threading
import sqlite3
import time

def querydatabase(query, resultlist, index):

    """Execute database query"""
    conn = sqlite3.connect('example.db')
    cursor = conn.cursor()

    cursor.execute(query)
    result = cursor.fetchall()
    resultlist[index] = result

    conn.close()
    print(f"Query {index+1} completed: {len(result)} rows")

Multiple queries
queries = [
    "SELECT  FROM users WHERE age > 25",