Module 4 · Testing behind the screen Lesson 12 of 15
A performance smoke test
A performance test answers one question: does the page still answer in a reasonable time when several people use it at once. You do not need a load-testing platform to find the obvious slow case.
The concept
Start with the endpoint that already feels slow to you, at the load you actually expect, and compare against a number you chose in advance - not against a feeling after the fact.
The bug you are hunting is the one that grows with data: a missing index, an N-plus-one query, an unbounded list. A smoke test catches those; a full load test is for later.
import statistics, time, requests
def test_search_is_fast_enough():
times = []
for _ in range(50):
t0 = time.perf_counter()
requests.get("http://localhost:3000/api/jobs?q=analyst", timeout=10)
times.append(time.perf_counter() - t0)
median = statistics.median(times)
assert median < 1.0, f"median {median:.2f}s"
print(f"median {median:.3f}s worst {max(times):.3f}s")Worked example
Time fifty requests to the search endpoint and assert the median under one second; that catches the query that was fine with ten rows and dies with ten thousand.
Your practice task
Measure the response time of one endpoint under a repeated call and write down the median and the worst case.
Do this before moving on. Reading a solution teaches the shape of it; typing it teaches you.
Key takeaway
Start with the endpoint that already feels slow to you, at the load you actually expect, and compare against a number you chose in advance - not against a feeling after the fact.
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