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Add doctests (GH-25474)
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@ -18,7 +18,9 @@ Sorting Basics
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==============
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A simple ascending sort is very easy: just call the :func:`sorted` function. It
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returns a new sorted list::
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returns a new sorted list:
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.. doctest::
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>>> sorted([5, 2, 3, 1, 4])
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[1, 2, 3, 4, 5]
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@ -28,6 +30,8 @@ in-place (and returns ``None`` to avoid confusion). Usually it's less convenient
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than :func:`sorted` - but if you don't need the original list, it's slightly
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more efficient.
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.. doctest::
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>>> a = [5, 2, 3, 1, 4]
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>>> a.sort()
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>>> a
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@ -36,6 +40,8 @@ more efficient.
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Another difference is that the :meth:`list.sort` method is only defined for
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lists. In contrast, the :func:`sorted` function accepts any iterable.
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.. doctest::
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>>> sorted({1: 'D', 2: 'B', 3: 'B', 4: 'E', 5: 'A'})
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[1, 2, 3, 4, 5]
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@ -48,6 +54,8 @@ comparisons.
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For example, here's a case-insensitive string comparison:
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.. doctest::
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>>> sorted("This is a test string from Andrew".split(), key=str.lower)
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['a', 'Andrew', 'from', 'is', 'string', 'test', 'This']
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@ -59,6 +67,8 @@ input record.
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A common pattern is to sort complex objects using some of the object's indices
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as keys. For example:
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.. doctest::
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>>> student_tuples = [
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... ('john', 'A', 15),
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... ('jane', 'B', 12),
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@ -69,6 +79,8 @@ as keys. For example:
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The same technique works for objects with named attributes. For example:
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.. doctest::
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>>> class Student:
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... def __init__(self, name, grade, age):
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... self.name = name
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@ -95,6 +107,8 @@ convenience functions to make accessor functions easier and faster. The
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Using those functions, the above examples become simpler and faster:
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.. doctest::
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>>> from operator import itemgetter, attrgetter
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>>> sorted(student_tuples, key=itemgetter(2))
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@ -106,6 +120,8 @@ Using those functions, the above examples become simpler and faster:
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The operator module functions allow multiple levels of sorting. For example, to
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sort by *grade* then by *age*:
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.. doctest::
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>>> sorted(student_tuples, key=itemgetter(1,2))
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[('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]
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@ -119,6 +135,8 @@ Both :meth:`list.sort` and :func:`sorted` accept a *reverse* parameter with a
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boolean value. This is used to flag descending sorts. For example, to get the
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student data in reverse *age* order:
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.. doctest::
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>>> sorted(student_tuples, key=itemgetter(2), reverse=True)
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[('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]
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@ -132,6 +150,8 @@ Sorts are guaranteed to be `stable
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<https://en.wikipedia.org/wiki/Sorting_algorithm#Stability>`_\. That means that
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when multiple records have the same key, their original order is preserved.
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.. doctest::
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>>> data = [('red', 1), ('blue', 1), ('red', 2), ('blue', 2)]
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>>> sorted(data, key=itemgetter(0))
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[('blue', 1), ('blue', 2), ('red', 1), ('red', 2)]
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@ -143,6 +163,8 @@ This wonderful property lets you build complex sorts in a series of sorting
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steps. For example, to sort the student data by descending *grade* and then
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ascending *age*, do the *age* sort first and then sort again using *grade*:
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.. doctest::
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>>> s = sorted(student_objects, key=attrgetter('age')) # sort on secondary key
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>>> sorted(s, key=attrgetter('grade'), reverse=True) # now sort on primary key, descending
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[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
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@ -150,6 +172,8 @@ ascending *age*, do the *age* sort first and then sort again using *grade*:
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This can be abstracted out into a wrapper function that can take a list and
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tuples of field and order to sort them on multiple passes.
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.. doctest::
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>>> def multisort(xs, specs):
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... for key, reverse in reversed(specs):
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... xs.sort(key=attrgetter(key), reverse=reverse)
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@ -220,6 +244,8 @@ comparisons. That function should take two arguments to be compared and then
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return a negative value for less-than, return zero if they are equal, or return
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a positive value for greater-than. For example, we can do:
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.. doctest::
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>>> def numeric_compare(x, y):
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... return x - y
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>>> sorted([5, 2, 4, 1, 3], cmp=numeric_compare) # doctest: +SKIP
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@ -227,6 +253,8 @@ a positive value for greater-than. For example, we can do:
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Or you can reverse the order of comparison with:
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.. doctest::
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>>> def reverse_numeric(x, y):
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... return y - x
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>>> sorted([5, 2, 4, 1, 3], cmp=reverse_numeric) # doctest: +SKIP
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@ -234,7 +262,9 @@ Or you can reverse the order of comparison with:
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When porting code from Python 2.x to 3.x, the situation can arise when you have
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the user supplying a comparison function and you need to convert that to a key
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function. The following wrapper makes that easy to do::
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function. The following wrapper makes that easy to do:
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.. testcode::
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def cmp_to_key(mycmp):
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'Convert a cmp= function into a key= function'
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@ -255,6 +285,12 @@ function. The following wrapper makes that easy to do::
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return mycmp(self.obj, other.obj) != 0
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return K
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.. doctest::
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:hide:
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>>> sorted([5, 2, 4, 1, 3], key=cmp_to_key(reverse_numeric))
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[5, 4, 3, 2, 1]
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To convert to a key function, just wrap the old comparison function:
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.. testsetup::
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@ -280,6 +316,8 @@ Odd and Ends
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simulated without the parameter by using the builtin :func:`reversed` function
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twice:
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.. doctest::
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>>> data = [('red', 1), ('blue', 1), ('red', 2), ('blue', 2)]
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>>> standard_way = sorted(data, key=itemgetter(0), reverse=True)
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>>> double_reversed = list(reversed(sorted(reversed(data), key=itemgetter(0))))
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@ -289,7 +327,9 @@ Odd and Ends
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* The sort routines are guaranteed to use :meth:`__lt__` when making comparisons
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between two objects. So, it is easy to add a standard sort order to a class by
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defining an :meth:`__lt__` method::
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defining an :meth:`__lt__` method:
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.. doctest::
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>>> Student.__lt__ = lambda self, other: self.age < other.age
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>>> sorted(student_objects)
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@ -300,6 +340,8 @@ Odd and Ends
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are stored in a dictionary, they can be used to sort a separate list of student
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names:
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.. doctest::
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>>> students = ['dave', 'john', 'jane']
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>>> newgrades = {'john': 'F', 'jane':'A', 'dave': 'C'}
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>>> sorted(students, key=newgrades.__getitem__)
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