Sorting Basics¶
A simple ascending sort is very easy: just call the sorted()
function. It returns a new sorted list:
>>> sorted([5, 2, 3, 1, 4]) [1, 2, 3, 4, 5]
You can also use the list.sort()
method. It modifies the list in-place (and returns None
to avoid confusion). Usually it’s less convenient than sorted()
- but if you don’t need the original list, it’s slightly more efficient.
>>> a = [5, 2, 3, 1, 4] >>> a.sort() >>> a [1, 2, 3, 4, 5]
Another difference is that the list.sort()
method is only defined for lists. In contrast, the sorted()
function accepts any iterable.
>>> sorted({1: 'D', 2: 'B', 3: 'B', 4: 'E', 5: 'A'}) [1, 2, 3, 4, 5]
Key Functions
Both list.sort()
and sorted()
have a key parameter to specify a function (or other callable) to be called on each list element prior to making comparisons.
For example, here’s a case-insensitive string comparison:
>>>>>> sorted("This is a test string from Andrew".split(), key=str.lower) ['a', 'Andrew', 'from', 'is', 'string', 'test', 'This']
The value of the key parameter should be a function (or other callable) that takes a single argument and returns a key to use for sorting purposes. This technique is fast because the key function is called exactly once for each input record.
A common pattern is to sort complex objects using some of the object’s indices as keys. For example:
>>>>>> student_tuples = [ ... ('john', 'A', 15), ... ('jane', 'B', 12), ... ('dave', 'B', 10), ... ] >>> sorted(student_tuples, key=lambda student: student[2]) # sort by age [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
Ascending and Descending¶ #升序和降序
Both list.sort()
and sorted()
accept a reverse parameter with a boolean value. This is used to flag descending sorts. For example, to get the student data in reverse age order:
>>> sorted(student_tuples, key=itemgetter(2), reverse=True) [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]>>>
>>> sorted(student_objects, key=attrgetter('age'), reverse=True) [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]