초보자도 쉽게 따라 하는 느린 Python 코드 가속화 방법 5가지

import time

def load_records():
    return list(range(100_000))

def filter_records(records):
    return [r for r in records if r % 2 == 0]

start = time.perf_counter()
records = load_records()
print(f"Load : {time.perf_counter() - start:.4f}s")

start = time.perf_counter()
filtered = filter_records(records)
print(f"Filter : {time.perf_counter() - start:.4f}s")

import time
numbers = list(range(1_000_000))

# Manual loop
start = time.perf_counter()
total = 0
for n in numbers:
    total += n
print(f"Manual loop : {time.perf_counter() - start:.4f}s")

# Built-in sum()
start = time.perf_counter()
total = sum(numbers)
print(f"Built-in : {time.perf_counter() - start:.4f}s")

# Slow: list membership check inside loop
for code in incoming:
    if code in approved: # O(n) slow
        valid.append(code)

# Fast: convert to set outside loop
approved_set = set(approved)
for code in incoming:
    if code in approved_set: # O(1) fast
        valid.append(code)

import numpy as np
prices_array = np.array(prices)

# NumPy vectorization
start = time.perf_counter()
discounted = np.round(prices_array * (1 - discount_rate), 2)
print(f"NumPy : {time.perf_counter() - start:.4f}s")