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Diffstat (limited to 'Doc/howto/sorting.rst')
| -rw-r--r-- | Doc/howto/sorting.rst | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/Doc/howto/sorting.rst b/Doc/howto/sorting.rst index f2e64ee..10cb94c 100644 --- a/Doc/howto/sorting.rst +++ b/Doc/howto/sorting.rst @@ -127,7 +127,7 @@ Sort Stability and Complex Sorts ================================ Sorts are guaranteed to be `stable -<http://en.wikipedia.org/wiki/Sorting_algorithm#Stability>`_\. That means that +<https://en.wikipedia.org/wiki/Sorting_algorithm#Stability>`_\. That means that when multiple records have the same key, their original order is preserved. >>> data = [('red', 1), ('blue', 1), ('red', 2), ('blue', 2)] @@ -145,7 +145,7 @@ ascending *age*, do the *age* sort first and then sort again using *grade*: >>> sorted(s, key=attrgetter('grade'), reverse=True) # now sort on primary key, descending [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)] -The `Timsort <http://en.wikipedia.org/wiki/Timsort>`_ algorithm used in Python +The `Timsort <https://en.wikipedia.org/wiki/Timsort>`_ algorithm used in Python does multiple sorts efficiently because it can take advantage of any ordering already present in a dataset. @@ -184,7 +184,7 @@ decorated list, but including it gives two benefits: directly. Another name for this idiom is -`Schwartzian transform <http://en.wikipedia.org/wiki/Schwartzian_transform>`_\, +`Schwartzian transform <https://en.wikipedia.org/wiki/Schwartzian_transform>`_\, after Randal L. Schwartz, who popularized it among Perl programmers. Now that Python sorting provides key-functions, this technique is not often needed. |