Classify request latencies

Beginner~5 min

Label each latency (in milliseconds) as "ok", "warn" or "crit" using two thresholds: a value is "crit" when it is greater than or equal to crit_ms, "warn" when it is greater than or equal to warn_ms, and "ok" otherwise. Return the labels in the same order as the input.

Function

Implement classify. Input: latencies: list[float], warn_ms: float, crit_ms: float. Returns: list[str].

Constraints

0 <= len(latencies) <= 100_000
0 < warn_ms <= crit_ms

Examples

>>> classify([120, 250, 900, 499.9], 250, 500)

['ok', 'warn', 'crit', 'warn']

Details

Level: Basic syntax, loops, strings, lists and dictionaries. One idea per problem.
Roles: Site Reliability Engineer, Backend Engineer, DevOps Engineer
Topics: Loops and control flow, Lists and tuples
Tests: 2 public (run with Run), 2 hidden (graded on Submit)
Grading: Exact match of the return value

Function

Implement classify. Input: latencies: list[float], warn_ms: float, crit_ms: float. Returns: list[str].

Constraints

0 <= len(latencies) <= 100_000
0 < warn_ms <= crit_ms

Examples

>>> classify([120, 250, 900, 499.9], 250, 500)

['ok', 'warn', 'crit', 'warn']

Details

Level: Basic syntax, loops, strings, lists and dictionaries. One idea per problem.
Roles: Site Reliability Engineer, Backend Engineer, DevOps Engineer
Topics: Loops and control flow, Lists and tuples
Tests: 2 public (run with Run), 2 hidden (graded on Submit)
Grading: Exact match of the return value

Python 3.13

def classify(latencies: list[float], warn_ms: float, crit_ms: float) -> list[str]:
    labels = []
    return labels

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Classify request latencies · Python practice