请参阅 Python 文档中的示例bisect
:
与 sorted() 函数不同,bisect() 函数具有键或反转参数是没有意义的,因为这会导致设计效率低下(对 bisect 函数的连续调用不会“记住”所有先前的键查找) .
相反,最好搜索预先计算的键列表以找到相关记录的索引:
>>> data = [('red', 5), ('blue', 1), ('yellow', 8), ('black', 0)]
>>> data.sort(key=lambda r: r[1])
>>> keys = [r[1] for r in data] # precomputed list of keys
>>> data[bisect_left(keys, 0)]
('black', 0)
>>> data[bisect_left(keys, 1)]
('blue', 1)
>>> data[bisect_left(keys, 5)]
('red', 5)
>>> data[bisect_left(keys, 8)]
('yellow', 8)
所以在你的情况下:
nested_list = [[123,'Aaron','CA'],[124,'Bob','WY'],[125,'John','TX']]
insert_me = [122,'George','AL']
keys = [r[1] for r in nested_list]
nested_list.insert(bisect.bisect_left(keys,insert_me[1]),insert_me)
[[123, 'Aaron', 'CA'],
[124, 'Bob', 'WY'],
[122, 'George', 'AL'],
[125, 'John', 'TX']]
为避免keys
每次都重新构建,请在其中插入新值keys
:
keys.insert(bisect_left(keys,insert_me[1]),insert_me[1])
更新:
在 insert/bisect、append/sorted 和 heapq 解决方案之间进行了一些性能比较:
# elements heapq insert/bisect append/sorted
10,000 0.01s 0.08s 2.43s
20,000 0.03s 0.28s 10.06s
30,000 0.04s 0.60s 22.81s