gh-110067: Improve max-heap documentation across heapq module

- Add max-heap usage examples to module docstrings in both the Python
  (Lib/heapq.py) and C (Modules/_heapqmodule.c) implementations
- Add descending heapsort example using max-heap functions to
  Doc/library/heapq.rst
- Expand the What's New in 3.14 entry for heapq with descriptions of
  each new max-heap function, context about the change, and correct
  contributor attribution

Author: kunwar-vikrant

Doc/library/heapq.rst

@@ -214,6 +214,18 @@ time::
 This is similar to ``sorted(iterable)``, but unlike :func:`sorted`, this
 implementation is not stable.
 
+Using max-heap functions, a reverse (descending) heapsort is equally
+straightforward::
+
+   >>> def heapsort_desc(iterable):
+   ...     h = []
+   ...     for value in iterable:
+   ...         heappush_max(h, value)
+   ...     return [heappop_max(h) for i in range(len(h))]
+   ...
+   >>> heapsort_desc([1, 3, 5, 7, 9, 2, 4, 6, 8, 0])
+   [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
+
 Heap elements can be tuples.  This is useful for assigning comparison values
 (such as task priorities) alongside the main record being tracked::
 

Doc/whatsnew/3.14.rst

@@ -1387,14 +1387,19 @@ graphlib
 heapq
 -----
 
-* The :mod:`!heapq` module has improved support for working with max-heaps,
-  via the following new functions:
-
-  * :func:`~heapq.heapify_max`
-  * :func:`~heapq.heappush_max`
-  * :func:`~heapq.heappop_max`
-  * :func:`~heapq.heapreplace_max`
-  * :func:`~heapq.heappushpop_max`
+* The :mod:`!heapq` module now has full public support for max-heaps,
+  providing a symmetric API to the existing min-heap functions.
+  Max-heaps maintain the reverse invariant: ``heap[0]`` is always the
+  *largest* element.  The new functions are:
+
+  * :func:`~heapq.heapify_max`: Transform a list into a max-heap in-place
+  * :func:`~heapq.heappush_max`: Push an item onto a max-heap
+  * :func:`~heapq.heappop_max`: Pop the largest item from a max-heap
+  * :func:`~heapq.heapreplace_max`: Pop largest and push new item in one step
+  * :func:`~heapq.heappushpop_max`: Push new item and pop largest in one step
+
+  These were previously available only as undocumented internal helpers.
+  (Contributed by Stan Ulbrych in :gh:`110067`.)
 
 
 hmac

Lib/heapq.py

@@ -5,7 +5,7 @@
 non-existing elements are considered to be infinite.  The interesting
 property of a heap is that a[0] is always its smallest element.
 
-Usage:
+Usage (min-heap):
 
 heap = []            # creates an empty heap
 heappush(heap, item) # pushes a new item on the heap
@@ -17,6 +17,18 @@
 item = heapreplace(heap, item) # pops and returns smallest item, and adds
                                # new item; the heap size is unchanged
 
+Usage (max-heap):
+
+heap = []                # creates an empty max-heap
+heappush_max(heap, item) # pushes a new item on the max-heap
+item = heappop_max(heap) # pops the largest item from the max-heap
+item = heap[0]           # largest item on the max-heap without popping it
+heapify_max(x)           # transforms list into a max-heap, in-place, in linear time
+item = heappushpop_max(heap, item) # pushes a new item and then returns
+                                   # the largest item; the heap size is unchanged
+item = heapreplace_max(heap, item) # pops and returns largest item, and adds
+                                   # new item; the heap size is unchanged
+
 Our API differs from textbook heap algorithms as follows:
 
 - We use 0-based indexing.  This makes the relationship between the

Modules/_heapqmodule.c

@@ -658,7 +658,7 @@ all k, counting elements from 0.  For the sake of comparison,\n\
 non-existing elements are considered to be infinite.  The interesting\n\
 property of a heap is that a[0] is always its smallest element.\n\
 \n\
-Usage:\n\
+Usage (min-heap):\n\
 \n\
 heap = []            # creates an empty heap\n\
 heappush(heap, item) # pushes a new item on the heap\n\
@@ -668,6 +668,16 @@ heapify(x)           # transforms list into a heap, in-place, in linear time\n\
 item = heapreplace(heap, item) # pops and returns smallest item, and adds\n\
                                # new item; the heap size is unchanged\n\
 \n\
+Usage (max-heap):\n\
+\n\
+heap = []                # creates an empty max-heap\n\
+heappush_max(heap, item) # pushes a new item on the max-heap\n\
+item = heappop_max(heap) # pops the largest item from the max-heap\n\
+item = heap[0]           # largest item on the max-heap without popping it\n\
+heapify_max(x)           # transforms list into a max-heap, in-place, in linear time\n\
+item = heapreplace_max(heap, item) # pops and returns largest item, and adds\n\
+                                   # new item; the heap size is unchanged\n\
+\n\
 Our API differs from textbook heap algorithms as follows:\n\
 \n\
 - We use 0-based indexing.  This makes the relationship between the\n\