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Diffstat (limited to 'Doc/howto/sorting.rst')
| -rw-r--r-- | Doc/howto/sorting.rst | 79 |
1 files changed, 39 insertions, 40 deletions
diff --git a/Doc/howto/sorting.rst b/Doc/howto/sorting.rst index 134c9ce..af1149d 100644 --- a/Doc/howto/sorting.rst +++ b/Doc/howto/sorting.rst @@ -4,7 +4,6 @@ Sorting HOW TO ************** :Author: Andrew Dalke and Raymond Hettinger -:Release: 0.1 Python lists have a built-in :meth:`list.sort` method that modifies the list @@ -18,7 +17,7 @@ Sorting Basics ============== A simple ascending sort is very easy: just call the :func:`sorted` function. It -returns a new sorted list:: +returns a new sorted list: >>> sorted([5, 2, 3, 1, 4]) [1, 2, 3, 4, 5] @@ -58,28 +57,28 @@ 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), - ] + ... ('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)] The same technique works for objects with named attributes. For example: >>> class Student: - def __init__(self, name, grade, age): - self.name = name - self.grade = grade - self.age = age - def __repr__(self): - return repr((self.name, self.grade, self.age)) + ... def __init__(self, name, grade, age): + ... self.name = name + ... self.grade = grade + ... self.age = age + ... def __repr__(self): + ... return repr((self.name, self.grade, self.age)) >>> student_objects = [ - Student('john', 'A', 15), - Student('jane', 'B', 12), - Student('dave', 'B', 10), - ] + ... Student('john', 'A', 15), + ... Student('jane', 'B', 12), + ... Student('dave', 'B', 10), + ... ] >>> sorted(student_objects, key=lambda student: student.age) # sort by age [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)] @@ -208,39 +207,39 @@ return a negative value for less-than, return zero if they are equal, or return a positive value for greater-than. For example, we can do: >>> def numeric_compare(x, y): - return x - y - >>> sorted([5, 2, 4, 1, 3], cmp=numeric_compare) + ... return x - y + >>> sorted([5, 2, 4, 1, 3], cmp=numeric_compare) # doctest: +SKIP [1, 2, 3, 4, 5] Or you can reverse the order of comparison with: >>> def reverse_numeric(x, y): - return y - x - >>> sorted([5, 2, 4, 1, 3], cmp=reverse_numeric) + ... return y - x + >>> sorted([5, 2, 4, 1, 3], cmp=reverse_numeric) # doctest: +SKIP [5, 4, 3, 2, 1] When porting code from Python 2.x to 3.x, the situation can arise when you have the user supplying a comparison function and you need to convert that to a key -function. The following wrapper makes that easy to do:: - - def cmp_to_key(mycmp): - 'Convert a cmp= function into a key= function' - class K(object): - def __init__(self, obj, *args): - self.obj = obj - def __lt__(self, other): - return mycmp(self.obj, other.obj) < 0 - def __gt__(self, other): - return mycmp(self.obj, other.obj) > 0 - def __eq__(self, other): - return mycmp(self.obj, other.obj) == 0 - def __le__(self, other): - return mycmp(self.obj, other.obj) <= 0 - def __ge__(self, other): - return mycmp(self.obj, other.obj) >= 0 - def __ne__(self, other): - return mycmp(self.obj, other.obj) != 0 - return K +function. The following wrapper makes that easy to do: + + >>> def cmp_to_key(mycmp): + ... 'Convert a cmp= function into a key= function' + ... class K(object): + ... def __init__(self, obj, *args): + ... self.obj = obj + ... def __lt__(self, other): + ... return mycmp(self.obj, other.obj) < 0 + ... def __gt__(self, other): + ... return mycmp(self.obj, other.obj) > 0 + ... def __eq__(self, other): + ... return mycmp(self.obj, other.obj) == 0 + ... def __le__(self, other): + ... return mycmp(self.obj, other.obj) <= 0 + ... def __ge__(self, other): + ... return mycmp(self.obj, other.obj) >= 0 + ... def __ne__(self, other): + ... return mycmp(self.obj, other.obj) != 0 + ... return K To convert to a key function, just wrap the old comparison function: |