Precision@K

Task

Implement precision_at_k(labels: list[int], scores: list[float], k: int) -> float. Labels are binary, where 1 means relevant. Sort examples by descending score and return the fraction of relevant labels among the selected examples.

Requirements

• Return 0.0 when k <= 0.
• When k exceeds the dataset size, use every example.
• Preserve original input order when scores tie.
• Inputs have equal length and labels are binary.

Example

labels = [0, 1, 1, 0]
scores = [0.2, 0.9, 0.4, 0.7]

precision_at_k(labels, scores, 2)
# 0.5