排序与查找：从正确结果到可解释的性能

from bisect import bisect_left, bisect_right

values = [1, 3, 3, 3, 8]
print(bisect_left(values, 3), bisect_right(values, 3))

from collections.abc import Sequence


def binary_search(values: Sequence[int], target: int) -> int:
    left, right = 0, len(values) - 1
    while left <= right:
        middle = left + (right - left) // 2
        if values[middle] == target:
            return middle
        if values[middle] < target:
            left = middle + 1
        else:
            right = middle - 1
    return -1


def merge_sort(values: list[int]) -> list[int]:
    if len(values) <= 1:
        return values.copy()
    middle = len(values) // 2
    left = merge_sort(values[:middle])
    right = merge_sort(values[middle:])
    result: list[int] = []
    i = j = 0
    while i < len(left) and j < len(right):
        if left[i] <= right[j]:
            result.append(left[i])
            i += 1
        else:
            result.append(right[j])
            j += 1
    result.extend(left[i:])
    result.extend(right[j:])
    return result


raw = [8, 3, 5, 3, 9, 1]
ordered = merge_sort(raw)
print("raw:", raw)
print("sorted:", ordered)
print("index:", binary_search(ordered, 5))
print("missing:", binary_search(ordered, 7))

tasks = [{"id": 2, "priority": 1}, {"id": 1, "priority": 1}]
print(sorted(tasks, key=lambda item: (item["priority"], item["id"])))