bisect of Python

bisect

在有序列表中执行二分查找和插入。

https://docs.python.org/3.5/library/bisect.html

This module provides support for maintaining a list in sorted order without having to sort the list after each insertion. For long lists of items with expensive comparison operations, this can be an improvement over the more common approach. The module is called bisect because it uses a basic bisection algorithm to do its work. The source code may be most useful as a working example of the algorithm (the boundary conditions are already right!).

The following functions are provided:

bisect.bisect_left(a, x, lo=0, hi=len(a))

Locate the insertion point for x in a to maintain sorted order. The parameters lo and hi may be used to specify a subset of the list which should be considered; by default the entire list is used. If x is already present in a, the insertion point will be before (to the left of) any existing entries. The return value is suitable for use as the first parameter to list.insert() assuming that a is already sorted.

The returned insertion point i partitions the array a into two halves so that all(val < x for val in a[lo:i]) for the left side and all(val >= x for val in a[i:hi]) for the right side.

bisect.bisect_right(a, x, lo=0, hi=len(a))

bisect.bisect(a, x, lo=0, hi=len(a))

Similar to bisect_left(), but returns an insertion point which comes after (to the right of) any existing entries of x in a.

The returned insertion point i partitions the array a into two halves so that all(val <= x for val in a[lo:i]) for the left side and all(val > x for val in a[i:hi]) for the right side.

bisect.insort_left(a, x, lo=0, hi=len(a))

Insert x in a in sorted order. This is equivalent to a.insert(bisect.bisect_left(a, x, lo, hi), x) assuming that a is already sorted. Keep in mind that the O(log n) search is dominated by the slow O(n) insertion step.

bisect.insort_right(a, x, lo=0, hi=len(a))

bisect.insort(a, x, lo=0, hi=len(a))

Similar to insort_left(), but inserting x in a after any existing entries of x.

Demo

>>> def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'):
...     i = bisect(breakpoints, score)
...     return grades[i]
...
>>> [grade(score) for score in [33, 99, 77, 70, 89, 90, 100]]
['F', 'A', 'C', 'C', 'B', 'A', 'A']

>>> 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)

https://pymotw.com/3/bisect/index.html

#bisect_example.py

import bisect

# A series of random numbers
values = [14, 85, 77, 26, 50, 45, 66, 79, 10, 3, 84, 77, 1]

print('New  Pos  Contents')
print('---  ---  --------')

l = []
for i in values:
    position = bisect.bisect(l, i)
    bisect.insort(l, i)
    print('{:3}  {:3}'.format(i, position), l)

The first column of the output shows the new random number. The second column shows the position where the number will be inserted into the list. The remainder of each line is the current sorted list.

$ python3 bisect_example.py

New  Pos  Contents
---  ---  --------
 14    0 [14]
 85    1 [14, 85]
 77    1 [14, 77, 85]
 26    1 [14, 26, 77, 85]
 50    2 [14, 26, 50, 77, 85]
 45    2 [14, 26, 45, 50, 77, 85]
 66    4 [14, 26, 45, 50, 66, 77, 85]
 79    6 [14, 26, 45, 50, 66, 77, 79, 85]
 10    0 [10, 14, 26, 45, 50, 66, 77, 79, 85]
  3    0 [3, 10, 14, 26, 45, 50, 66, 77, 79, 85]
 84    9 [3, 10, 14, 26, 45, 50, 66, 77, 79, 84, 85]
 77    8 [3, 10, 14, 26, 45, 50, 66, 77, 77, 79, 84, 85]
  1    0 [1, 3, 10, 14, 26, 45, 50, 66, 77, 77, 79, 84, 85]