LCOV - code coverage report
Current view: top level - Modules - _heapqmodule.c (source / functions) Hit Total Coverage
Test: CPython 3.12 LCOV report [commit 5e6661bce9] Lines: 6 227 2.6 %
Date: 2023-03-20 08:15:36 Functions: 2 19 10.5 %
Branches: 1 88 1.1 %

           Branch data     Line data    Source code
       1                 :            : /* Drop in replacement for heapq.py
       2                 :            : 
       3                 :            : C implementation derived directly from heapq.py in Py2.3
       4                 :            : which was written by Kevin O'Connor, augmented by Tim Peters,
       5                 :            : annotated by François Pinard, and converted to C by Raymond Hettinger.
       6                 :            : 
       7                 :            : */
       8                 :            : 
       9                 :            : #ifndef Py_BUILD_CORE_BUILTIN
      10                 :            : #  define Py_BUILD_CORE_MODULE 1
      11                 :            : #endif
      12                 :            : 
      13                 :            : #include "Python.h"
      14                 :            : #include "pycore_list.h"          // _PyList_ITEMS()
      15                 :            : 
      16                 :            : #include "clinic/_heapqmodule.c.h"
      17                 :            : 
      18                 :            : 
      19                 :            : /*[clinic input]
      20                 :            : module _heapq
      21                 :            : [clinic start generated code]*/
      22                 :            : /*[clinic end generated code: output=da39a3ee5e6b4b0d input=d7cca0a2e4c0ceb3]*/
      23                 :            : 
      24                 :            : static int
      25                 :          0 : siftdown(PyListObject *heap, Py_ssize_t startpos, Py_ssize_t pos)
      26                 :            : {
      27                 :            :     PyObject *newitem, *parent, **arr;
      28                 :            :     Py_ssize_t parentpos, size;
      29                 :            :     int cmp;
      30                 :            : 
      31                 :            :     assert(PyList_Check(heap));
      32                 :          0 :     size = PyList_GET_SIZE(heap);
      33         [ #  # ]:          0 :     if (pos >= size) {
      34                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
      35                 :          0 :         return -1;
      36                 :            :     }
      37                 :            : 
      38                 :            :     /* Follow the path to the root, moving parents down until finding
      39                 :            :        a place newitem fits. */
      40                 :          0 :     arr = _PyList_ITEMS(heap);
      41                 :          0 :     newitem = arr[pos];
      42         [ #  # ]:          0 :     while (pos > startpos) {
      43                 :          0 :         parentpos = (pos - 1) >> 1;
      44                 :          0 :         parent = arr[parentpos];
      45                 :          0 :         Py_INCREF(newitem);
      46                 :          0 :         Py_INCREF(parent);
      47                 :          0 :         cmp = PyObject_RichCompareBool(newitem, parent, Py_LT);
      48                 :          0 :         Py_DECREF(parent);
      49                 :          0 :         Py_DECREF(newitem);
      50         [ #  # ]:          0 :         if (cmp < 0)
      51                 :          0 :             return -1;
      52         [ #  # ]:          0 :         if (size != PyList_GET_SIZE(heap)) {
      53                 :          0 :             PyErr_SetString(PyExc_RuntimeError,
      54                 :            :                             "list changed size during iteration");
      55                 :          0 :             return -1;
      56                 :            :         }
      57         [ #  # ]:          0 :         if (cmp == 0)
      58                 :          0 :             break;
      59                 :          0 :         arr = _PyList_ITEMS(heap);
      60                 :          0 :         parent = arr[parentpos];
      61                 :          0 :         newitem = arr[pos];
      62                 :          0 :         arr[parentpos] = newitem;
      63                 :          0 :         arr[pos] = parent;
      64                 :          0 :         pos = parentpos;
      65                 :            :     }
      66                 :          0 :     return 0;
      67                 :            : }
      68                 :            : 
      69                 :            : static int
      70                 :          0 : siftup(PyListObject *heap, Py_ssize_t pos)
      71                 :            : {
      72                 :            :     Py_ssize_t startpos, endpos, childpos, limit;
      73                 :            :     PyObject *tmp1, *tmp2, **arr;
      74                 :            :     int cmp;
      75                 :            : 
      76                 :            :     assert(PyList_Check(heap));
      77                 :          0 :     endpos = PyList_GET_SIZE(heap);
      78                 :          0 :     startpos = pos;
      79         [ #  # ]:          0 :     if (pos >= endpos) {
      80                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
      81                 :          0 :         return -1;
      82                 :            :     }
      83                 :            : 
      84                 :            :     /* Bubble up the smaller child until hitting a leaf. */
      85                 :          0 :     arr = _PyList_ITEMS(heap);
      86                 :          0 :     limit = endpos >> 1;         /* smallest pos that has no child */
      87         [ #  # ]:          0 :     while (pos < limit) {
      88                 :            :         /* Set childpos to index of smaller child.   */
      89                 :          0 :         childpos = 2*pos + 1;    /* leftmost child position  */
      90         [ #  # ]:          0 :         if (childpos + 1 < endpos) {
      91                 :          0 :             PyObject* a = arr[childpos];
      92                 :          0 :             PyObject* b = arr[childpos + 1];
      93                 :          0 :             Py_INCREF(a);
      94                 :          0 :             Py_INCREF(b);
      95                 :          0 :             cmp = PyObject_RichCompareBool(a, b, Py_LT);
      96                 :          0 :             Py_DECREF(a);
      97                 :          0 :             Py_DECREF(b);
      98         [ #  # ]:          0 :             if (cmp < 0)
      99                 :          0 :                 return -1;
     100                 :          0 :             childpos += ((unsigned)cmp ^ 1);   /* increment when cmp==0 */
     101                 :          0 :             arr = _PyList_ITEMS(heap);         /* arr may have changed */
     102         [ #  # ]:          0 :             if (endpos != PyList_GET_SIZE(heap)) {
     103                 :          0 :                 PyErr_SetString(PyExc_RuntimeError,
     104                 :            :                                 "list changed size during iteration");
     105                 :          0 :                 return -1;
     106                 :            :             }
     107                 :            :         }
     108                 :            :         /* Move the smaller child up. */
     109                 :          0 :         tmp1 = arr[childpos];
     110                 :          0 :         tmp2 = arr[pos];
     111                 :          0 :         arr[childpos] = tmp2;
     112                 :          0 :         arr[pos] = tmp1;
     113                 :          0 :         pos = childpos;
     114                 :            :     }
     115                 :            :     /* Bubble it up to its final resting place (by sifting its parents down). */
     116                 :          0 :     return siftdown(heap, startpos, pos);
     117                 :            : }
     118                 :            : 
     119                 :            : /*[clinic input]
     120                 :            : _heapq.heappush
     121                 :            : 
     122                 :            :     heap: object(subclass_of='&PyList_Type')
     123                 :            :     item: object
     124                 :            :     /
     125                 :            : 
     126                 :            : Push item onto heap, maintaining the heap invariant.
     127                 :            : [clinic start generated code]*/
     128                 :            : 
     129                 :            : static PyObject *
     130                 :          0 : _heapq_heappush_impl(PyObject *module, PyObject *heap, PyObject *item)
     131                 :            : /*[clinic end generated code: output=912c094f47663935 input=7c69611f3698aceb]*/
     132                 :            : {
     133         [ #  # ]:          0 :     if (PyList_Append(heap, item))
     134                 :          0 :         return NULL;
     135                 :            : 
     136         [ #  # ]:          0 :     if (siftdown((PyListObject *)heap, 0, PyList_GET_SIZE(heap)-1))
     137                 :          0 :         return NULL;
     138                 :          0 :     Py_RETURN_NONE;
     139                 :            : }
     140                 :            : 
     141                 :            : static PyObject *
     142                 :          0 : heappop_internal(PyObject *heap, int siftup_func(PyListObject *, Py_ssize_t))
     143                 :            : {
     144                 :            :     PyObject *lastelt, *returnitem;
     145                 :            :     Py_ssize_t n;
     146                 :            : 
     147                 :            :     /* raises IndexError if the heap is empty */
     148                 :          0 :     n = PyList_GET_SIZE(heap);
     149         [ #  # ]:          0 :     if (n == 0) {
     150                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
     151                 :          0 :         return NULL;
     152                 :            :     }
     153                 :            : 
     154                 :          0 :     lastelt = PyList_GET_ITEM(heap, n-1) ;
     155                 :          0 :     Py_INCREF(lastelt);
     156         [ #  # ]:          0 :     if (PyList_SetSlice(heap, n-1, n, NULL)) {
     157                 :          0 :         Py_DECREF(lastelt);
     158                 :          0 :         return NULL;
     159                 :            :     }
     160                 :          0 :     n--;
     161                 :            : 
     162         [ #  # ]:          0 :     if (!n)
     163                 :          0 :         return lastelt;
     164                 :          0 :     returnitem = PyList_GET_ITEM(heap, 0);
     165                 :          0 :     PyList_SET_ITEM(heap, 0, lastelt);
     166         [ #  # ]:          0 :     if (siftup_func((PyListObject *)heap, 0)) {
     167                 :          0 :         Py_DECREF(returnitem);
     168                 :          0 :         return NULL;
     169                 :            :     }
     170                 :          0 :     return returnitem;
     171                 :            : }
     172                 :            : 
     173                 :            : /*[clinic input]
     174                 :            : _heapq.heappop
     175                 :            : 
     176                 :            :     heap: object(subclass_of='&PyList_Type')
     177                 :            :     /
     178                 :            : 
     179                 :            : Pop the smallest item off the heap, maintaining the heap invariant.
     180                 :            : [clinic start generated code]*/
     181                 :            : 
     182                 :            : static PyObject *
     183                 :          0 : _heapq_heappop_impl(PyObject *module, PyObject *heap)
     184                 :            : /*[clinic end generated code: output=96dfe82d37d9af76 input=91487987a583c856]*/
     185                 :            : {
     186                 :          0 :     return heappop_internal(heap, siftup);
     187                 :            : }
     188                 :            : 
     189                 :            : static PyObject *
     190                 :          0 : heapreplace_internal(PyObject *heap, PyObject *item, int siftup_func(PyListObject *, Py_ssize_t))
     191                 :            : {
     192                 :            :     PyObject *returnitem;
     193                 :            : 
     194         [ #  # ]:          0 :     if (PyList_GET_SIZE(heap) == 0) {
     195                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
     196                 :          0 :         return NULL;
     197                 :            :     }
     198                 :            : 
     199                 :          0 :     returnitem = PyList_GET_ITEM(heap, 0);
     200                 :          0 :     PyList_SET_ITEM(heap, 0, Py_NewRef(item));
     201         [ #  # ]:          0 :     if (siftup_func((PyListObject *)heap, 0)) {
     202                 :          0 :         Py_DECREF(returnitem);
     203                 :          0 :         return NULL;
     204                 :            :     }
     205                 :          0 :     return returnitem;
     206                 :            : }
     207                 :            : 
     208                 :            : 
     209                 :            : /*[clinic input]
     210                 :            : _heapq.heapreplace
     211                 :            : 
     212                 :            :     heap: object(subclass_of='&PyList_Type')
     213                 :            :     item: object
     214                 :            :     /
     215                 :            : 
     216                 :            : Pop and return the current smallest value, and add the new item.
     217                 :            : 
     218                 :            : This is more efficient than heappop() followed by heappush(), and can be
     219                 :            : more appropriate when using a fixed-size heap.  Note that the value
     220                 :            : returned may be larger than item!  That constrains reasonable uses of
     221                 :            : this routine unless written as part of a conditional replacement:
     222                 :            : 
     223                 :            :     if item > heap[0]:
     224                 :            :         item = heapreplace(heap, item)
     225                 :            : [clinic start generated code]*/
     226                 :            : 
     227                 :            : static PyObject *
     228                 :          0 : _heapq_heapreplace_impl(PyObject *module, PyObject *heap, PyObject *item)
     229                 :            : /*[clinic end generated code: output=82ea55be8fbe24b4 input=719202ac02ba10c8]*/
     230                 :            : {
     231                 :          0 :     return heapreplace_internal(heap, item, siftup);
     232                 :            : }
     233                 :            : 
     234                 :            : /*[clinic input]
     235                 :            : _heapq.heappushpop
     236                 :            : 
     237                 :            :     heap: object(subclass_of='&PyList_Type')
     238                 :            :     item: object
     239                 :            :     /
     240                 :            : 
     241                 :            : Push item on the heap, then pop and return the smallest item from the heap.
     242                 :            : 
     243                 :            : The combined action runs more efficiently than heappush() followed by
     244                 :            : a separate call to heappop().
     245                 :            : [clinic start generated code]*/
     246                 :            : 
     247                 :            : static PyObject *
     248                 :          0 : _heapq_heappushpop_impl(PyObject *module, PyObject *heap, PyObject *item)
     249                 :            : /*[clinic end generated code: output=67231dc98ed5774f input=5dc701f1eb4a4aa7]*/
     250                 :            : {
     251                 :            :     PyObject *returnitem;
     252                 :            :     int cmp;
     253                 :            : 
     254         [ #  # ]:          0 :     if (PyList_GET_SIZE(heap) == 0) {
     255                 :          0 :         return Py_NewRef(item);
     256                 :            :     }
     257                 :            : 
     258                 :          0 :     PyObject* top = PyList_GET_ITEM(heap, 0);
     259                 :          0 :     Py_INCREF(top);
     260                 :          0 :     cmp = PyObject_RichCompareBool(top, item, Py_LT);
     261                 :          0 :     Py_DECREF(top);
     262         [ #  # ]:          0 :     if (cmp < 0)
     263                 :          0 :         return NULL;
     264         [ #  # ]:          0 :     if (cmp == 0) {
     265                 :          0 :         return Py_NewRef(item);
     266                 :            :     }
     267                 :            : 
     268         [ #  # ]:          0 :     if (PyList_GET_SIZE(heap) == 0) {
     269                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
     270                 :          0 :         return NULL;
     271                 :            :     }
     272                 :            : 
     273                 :          0 :     returnitem = PyList_GET_ITEM(heap, 0);
     274                 :          0 :     PyList_SET_ITEM(heap, 0, Py_NewRef(item));
     275         [ #  # ]:          0 :     if (siftup((PyListObject *)heap, 0)) {
     276                 :          0 :         Py_DECREF(returnitem);
     277                 :          0 :         return NULL;
     278                 :            :     }
     279                 :          0 :     return returnitem;
     280                 :            : }
     281                 :            : 
     282                 :            : static Py_ssize_t
     283                 :          0 : keep_top_bit(Py_ssize_t n)
     284                 :            : {
     285                 :          0 :     int i = 0;
     286                 :            : 
     287         [ #  # ]:          0 :     while (n > 1) {
     288                 :          0 :         n >>= 1;
     289                 :          0 :         i++;
     290                 :            :     }
     291                 :          0 :     return n << i;
     292                 :            : }
     293                 :            : 
     294                 :            : /* Cache friendly version of heapify()
     295                 :            :    -----------------------------------
     296                 :            : 
     297                 :            :    Build-up a heap in O(n) time by performing siftup() operations
     298                 :            :    on nodes whose children are already heaps.
     299                 :            : 
     300                 :            :    The simplest way is to sift the nodes in reverse order from
     301                 :            :    n//2-1 to 0 inclusive.  The downside is that children may be
     302                 :            :    out of cache by the time their parent is reached.
     303                 :            : 
     304                 :            :    A better way is to not wait for the children to go out of cache.
     305                 :            :    Once a sibling pair of child nodes have been sifted, immediately
     306                 :            :    sift their parent node (while the children are still in cache).
     307                 :            : 
     308                 :            :    Both ways build child heaps before their parents, so both ways
     309                 :            :    do the exact same number of comparisons and produce exactly
     310                 :            :    the same heap.  The only difference is that the traversal
     311                 :            :    order is optimized for cache efficiency.
     312                 :            : */
     313                 :            : 
     314                 :            : static PyObject *
     315                 :          0 : cache_friendly_heapify(PyObject *heap, int siftup_func(PyListObject *, Py_ssize_t))
     316                 :            : {
     317                 :            :     Py_ssize_t i, j, m, mhalf, leftmost;
     318                 :            : 
     319                 :          0 :     m = PyList_GET_SIZE(heap) >> 1;         /* index of first childless node */
     320                 :          0 :     leftmost = keep_top_bit(m + 1) - 1;     /* leftmost node in row of m */
     321                 :          0 :     mhalf = m >> 1;                         /* parent of first childless node */
     322                 :            : 
     323         [ #  # ]:          0 :     for (i = leftmost - 1 ; i >= mhalf ; i--) {
     324                 :          0 :         j = i;
     325                 :            :         while (1) {
     326         [ #  # ]:          0 :             if (siftup_func((PyListObject *)heap, j))
     327                 :          0 :                 return NULL;
     328         [ #  # ]:          0 :             if (!(j & 1))
     329                 :          0 :                 break;
     330                 :          0 :             j >>= 1;
     331                 :            :         }
     332                 :            :     }
     333                 :            : 
     334         [ #  # ]:          0 :     for (i = m - 1 ; i >= leftmost ; i--) {
     335                 :          0 :         j = i;
     336                 :            :         while (1) {
     337         [ #  # ]:          0 :             if (siftup_func((PyListObject *)heap, j))
     338                 :          0 :                 return NULL;
     339         [ #  # ]:          0 :             if (!(j & 1))
     340                 :          0 :                 break;
     341                 :          0 :             j >>= 1;
     342                 :            :         }
     343                 :            :     }
     344                 :          0 :     Py_RETURN_NONE;
     345                 :            : }
     346                 :            : 
     347                 :            : static PyObject *
     348                 :          0 : heapify_internal(PyObject *heap, int siftup_func(PyListObject *, Py_ssize_t))
     349                 :            : {
     350                 :            :     Py_ssize_t i, n;
     351                 :            : 
     352                 :            :     /* For heaps likely to be bigger than L1 cache, we use the cache
     353                 :            :        friendly heapify function.  For smaller heaps that fit entirely
     354                 :            :        in cache, we prefer the simpler algorithm with less branching.
     355                 :            :     */
     356                 :          0 :     n = PyList_GET_SIZE(heap);
     357         [ #  # ]:          0 :     if (n > 2500)
     358                 :          0 :         return cache_friendly_heapify(heap, siftup_func);
     359                 :            : 
     360                 :            :     /* Transform bottom-up.  The largest index there's any point to
     361                 :            :        looking at is the largest with a child index in-range, so must
     362                 :            :        have 2*i + 1 < n, or i < (n-1)/2.  If n is even = 2*j, this is
     363                 :            :        (2*j-1)/2 = j-1/2 so j-1 is the largest, which is n//2 - 1.  If
     364                 :            :        n is odd = 2*j+1, this is (2*j+1-1)/2 = j so j-1 is the largest,
     365                 :            :        and that's again n//2-1.
     366                 :            :     */
     367         [ #  # ]:          0 :     for (i = (n >> 1) - 1 ; i >= 0 ; i--)
     368         [ #  # ]:          0 :         if (siftup_func((PyListObject *)heap, i))
     369                 :          0 :             return NULL;
     370                 :          0 :     Py_RETURN_NONE;
     371                 :            : }
     372                 :            : 
     373                 :            : /*[clinic input]
     374                 :            : _heapq.heapify
     375                 :            : 
     376                 :            :     heap: object(subclass_of='&PyList_Type')
     377                 :            :     /
     378                 :            : 
     379                 :            : Transform list into a heap, in-place, in O(len(heap)) time.
     380                 :            : [clinic start generated code]*/
     381                 :            : 
     382                 :            : static PyObject *
     383                 :          0 : _heapq_heapify_impl(PyObject *module, PyObject *heap)
     384                 :            : /*[clinic end generated code: output=e63a636fcf83d6d0 input=53bb7a2166febb73]*/
     385                 :            : {
     386                 :          0 :     return heapify_internal(heap, siftup);
     387                 :            : }
     388                 :            : 
     389                 :            : static int
     390                 :          0 : siftdown_max(PyListObject *heap, Py_ssize_t startpos, Py_ssize_t pos)
     391                 :            : {
     392                 :            :     PyObject *newitem, *parent, **arr;
     393                 :            :     Py_ssize_t parentpos, size;
     394                 :            :     int cmp;
     395                 :            : 
     396                 :            :     assert(PyList_Check(heap));
     397                 :          0 :     size = PyList_GET_SIZE(heap);
     398         [ #  # ]:          0 :     if (pos >= size) {
     399                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
     400                 :          0 :         return -1;
     401                 :            :     }
     402                 :            : 
     403                 :            :     /* Follow the path to the root, moving parents down until finding
     404                 :            :        a place newitem fits. */
     405                 :          0 :     arr = _PyList_ITEMS(heap);
     406                 :          0 :     newitem = arr[pos];
     407         [ #  # ]:          0 :     while (pos > startpos) {
     408                 :          0 :         parentpos = (pos - 1) >> 1;
     409                 :          0 :         parent = Py_NewRef(arr[parentpos]);
     410                 :          0 :         Py_INCREF(newitem);
     411                 :          0 :         cmp = PyObject_RichCompareBool(parent, newitem, Py_LT);
     412                 :          0 :         Py_DECREF(parent);
     413                 :          0 :         Py_DECREF(newitem);
     414         [ #  # ]:          0 :         if (cmp < 0)
     415                 :          0 :             return -1;
     416         [ #  # ]:          0 :         if (size != PyList_GET_SIZE(heap)) {
     417                 :          0 :             PyErr_SetString(PyExc_RuntimeError,
     418                 :            :                             "list changed size during iteration");
     419                 :          0 :             return -1;
     420                 :            :         }
     421         [ #  # ]:          0 :         if (cmp == 0)
     422                 :          0 :             break;
     423                 :          0 :         arr = _PyList_ITEMS(heap);
     424                 :          0 :         parent = arr[parentpos];
     425                 :          0 :         newitem = arr[pos];
     426                 :          0 :         arr[parentpos] = newitem;
     427                 :          0 :         arr[pos] = parent;
     428                 :          0 :         pos = parentpos;
     429                 :            :     }
     430                 :          0 :     return 0;
     431                 :            : }
     432                 :            : 
     433                 :            : static int
     434                 :          0 : siftup_max(PyListObject *heap, Py_ssize_t pos)
     435                 :            : {
     436                 :            :     Py_ssize_t startpos, endpos, childpos, limit;
     437                 :            :     PyObject *tmp1, *tmp2, **arr;
     438                 :            :     int cmp;
     439                 :            : 
     440                 :            :     assert(PyList_Check(heap));
     441                 :          0 :     endpos = PyList_GET_SIZE(heap);
     442                 :          0 :     startpos = pos;
     443         [ #  # ]:          0 :     if (pos >= endpos) {
     444                 :          0 :         PyErr_SetString(PyExc_IndexError, "index out of range");
     445                 :          0 :         return -1;
     446                 :            :     }
     447                 :            : 
     448                 :            :     /* Bubble up the smaller child until hitting a leaf. */
     449                 :          0 :     arr = _PyList_ITEMS(heap);
     450                 :          0 :     limit = endpos >> 1;         /* smallest pos that has no child */
     451         [ #  # ]:          0 :     while (pos < limit) {
     452                 :            :         /* Set childpos to index of smaller child.   */
     453                 :          0 :         childpos = 2*pos + 1;    /* leftmost child position  */
     454         [ #  # ]:          0 :         if (childpos + 1 < endpos) {
     455                 :          0 :             PyObject* a = arr[childpos + 1];
     456                 :          0 :             PyObject* b = arr[childpos];
     457                 :          0 :             Py_INCREF(a);
     458                 :          0 :             Py_INCREF(b);
     459                 :          0 :             cmp = PyObject_RichCompareBool(a, b, Py_LT);
     460                 :          0 :             Py_DECREF(a);
     461                 :          0 :             Py_DECREF(b);
     462         [ #  # ]:          0 :             if (cmp < 0)
     463                 :          0 :                 return -1;
     464                 :          0 :             childpos += ((unsigned)cmp ^ 1);   /* increment when cmp==0 */
     465                 :          0 :             arr = _PyList_ITEMS(heap);         /* arr may have changed */
     466         [ #  # ]:          0 :             if (endpos != PyList_GET_SIZE(heap)) {
     467                 :          0 :                 PyErr_SetString(PyExc_RuntimeError,
     468                 :            :                                 "list changed size during iteration");
     469                 :          0 :                 return -1;
     470                 :            :             }
     471                 :            :         }
     472                 :            :         /* Move the smaller child up. */
     473                 :          0 :         tmp1 = arr[childpos];
     474                 :          0 :         tmp2 = arr[pos];
     475                 :          0 :         arr[childpos] = tmp2;
     476                 :          0 :         arr[pos] = tmp1;
     477                 :          0 :         pos = childpos;
     478                 :            :     }
     479                 :            :     /* Bubble it up to its final resting place (by sifting its parents down). */
     480                 :          0 :     return siftdown_max(heap, startpos, pos);
     481                 :            : }
     482                 :            : 
     483                 :            : 
     484                 :            : /*[clinic input]
     485                 :            : _heapq._heappop_max
     486                 :            : 
     487                 :            :     heap: object(subclass_of='&PyList_Type')
     488                 :            :     /
     489                 :            : 
     490                 :            : Maxheap variant of heappop.
     491                 :            : [clinic start generated code]*/
     492                 :            : 
     493                 :            : static PyObject *
     494                 :          0 : _heapq__heappop_max_impl(PyObject *module, PyObject *heap)
     495                 :            : /*[clinic end generated code: output=9e77aadd4e6a8760 input=362c06e1c7484793]*/
     496                 :            : {
     497                 :          0 :     return heappop_internal(heap, siftup_max);
     498                 :            : }
     499                 :            : 
     500                 :            : /*[clinic input]
     501                 :            : _heapq._heapreplace_max
     502                 :            : 
     503                 :            :     heap: object(subclass_of='&PyList_Type')
     504                 :            :     item: object
     505                 :            :     /
     506                 :            : 
     507                 :            : Maxheap variant of heapreplace.
     508                 :            : [clinic start generated code]*/
     509                 :            : 
     510                 :            : static PyObject *
     511                 :          0 : _heapq__heapreplace_max_impl(PyObject *module, PyObject *heap,
     512                 :            :                              PyObject *item)
     513                 :            : /*[clinic end generated code: output=8ad7545e4a5e8adb input=f2dd27cbadb948d7]*/
     514                 :            : {
     515                 :          0 :     return heapreplace_internal(heap, item, siftup_max);
     516                 :            : }
     517                 :            : 
     518                 :            : /*[clinic input]
     519                 :            : _heapq._heapify_max
     520                 :            : 
     521                 :            :     heap: object(subclass_of='&PyList_Type')
     522                 :            :     /
     523                 :            : 
     524                 :            : Maxheap variant of heapify.
     525                 :            : [clinic start generated code]*/
     526                 :            : 
     527                 :            : static PyObject *
     528                 :          0 : _heapq__heapify_max_impl(PyObject *module, PyObject *heap)
     529                 :            : /*[clinic end generated code: output=2cb028beb4a8b65e input=c1f765ee69f124b8]*/
     530                 :            : {
     531                 :          0 :     return heapify_internal(heap, siftup_max);
     532                 :            : }
     533                 :            : 
     534                 :            : static PyMethodDef heapq_methods[] = {
     535                 :            :     _HEAPQ_HEAPPUSH_METHODDEF
     536                 :            :     _HEAPQ_HEAPPUSHPOP_METHODDEF
     537                 :            :     _HEAPQ_HEAPPOP_METHODDEF
     538                 :            :     _HEAPQ_HEAPREPLACE_METHODDEF
     539                 :            :     _HEAPQ_HEAPIFY_METHODDEF
     540                 :            :     _HEAPQ__HEAPPOP_MAX_METHODDEF
     541                 :            :     _HEAPQ__HEAPIFY_MAX_METHODDEF
     542                 :            :     _HEAPQ__HEAPREPLACE_MAX_METHODDEF
     543                 :            :     {NULL, NULL}           /* sentinel */
     544                 :            : };
     545                 :            : 
     546                 :            : PyDoc_STRVAR(module_doc,
     547                 :            : "Heap queue algorithm (a.k.a. priority queue).\n\
     548                 :            : \n\
     549                 :            : Heaps are arrays for which a[k] <= a[2*k+1] and a[k] <= a[2*k+2] for\n\
     550                 :            : all k, counting elements from 0.  For the sake of comparison,\n\
     551                 :            : non-existing elements are considered to be infinite.  The interesting\n\
     552                 :            : property of a heap is that a[0] is always its smallest element.\n\
     553                 :            : \n\
     554                 :            : Usage:\n\
     555                 :            : \n\
     556                 :            : heap = []            # creates an empty heap\n\
     557                 :            : heappush(heap, item) # pushes a new item on the heap\n\
     558                 :            : item = heappop(heap) # pops the smallest item from the heap\n\
     559                 :            : item = heap[0]       # smallest item on the heap without popping it\n\
     560                 :            : heapify(x)           # transforms list into a heap, in-place, in linear time\n\
     561                 :            : item = heapreplace(heap, item) # pops and returns smallest item, and adds\n\
     562                 :            :                                # new item; the heap size is unchanged\n\
     563                 :            : \n\
     564                 :            : Our API differs from textbook heap algorithms as follows:\n\
     565                 :            : \n\
     566                 :            : - We use 0-based indexing.  This makes the relationship between the\n\
     567                 :            :   index for a node and the indexes for its children slightly less\n\
     568                 :            :   obvious, but is more suitable since Python uses 0-based indexing.\n\
     569                 :            : \n\
     570                 :            : - Our heappop() method returns the smallest item, not the largest.\n\
     571                 :            : \n\
     572                 :            : These two make it possible to view the heap as a regular Python list\n\
     573                 :            : without surprises: heap[0] is the smallest item, and heap.sort()\n\
     574                 :            : maintains the heap invariant!\n");
     575                 :            : 
     576                 :            : 
     577                 :            : PyDoc_STRVAR(__about__,
     578                 :            : "Heap queues\n\
     579                 :            : \n\
     580                 :            : [explanation by Fran\xc3\xa7ois Pinard]\n\
     581                 :            : \n\
     582                 :            : Heaps are arrays for which a[k] <= a[2*k+1] and a[k] <= a[2*k+2] for\n\
     583                 :            : all k, counting elements from 0.  For the sake of comparison,\n\
     584                 :            : non-existing elements are considered to be infinite.  The interesting\n\
     585                 :            : property of a heap is that a[0] is always its smallest element.\n"
     586                 :            : "\n\
     587                 :            : The strange invariant above is meant to be an efficient memory\n\
     588                 :            : representation for a tournament.  The numbers below are `k', not a[k]:\n\
     589                 :            : \n\
     590                 :            :                                    0\n\
     591                 :            : \n\
     592                 :            :                   1                                 2\n\
     593                 :            : \n\
     594                 :            :           3               4                5               6\n\
     595                 :            : \n\
     596                 :            :       7       8       9       10      11      12      13      14\n\
     597                 :            : \n\
     598                 :            :     15 16   17 18   19 20   21 22   23 24   25 26   27 28   29 30\n\
     599                 :            : \n\
     600                 :            : \n\
     601                 :            : In the tree above, each cell `k' is topping `2*k+1' and `2*k+2'.  In\n\
     602                 :            : a usual binary tournament we see in sports, each cell is the winner\n\
     603                 :            : over the two cells it tops, and we can trace the winner down the tree\n\
     604                 :            : to see all opponents s/he had.  However, in many computer applications\n\
     605                 :            : of such tournaments, we do not need to trace the history of a winner.\n\
     606                 :            : To be more memory efficient, when a winner is promoted, we try to\n\
     607                 :            : replace it by something else at a lower level, and the rule becomes\n\
     608                 :            : that a cell and the two cells it tops contain three different items,\n\
     609                 :            : but the top cell \"wins\" over the two topped cells.\n"
     610                 :            : "\n\
     611                 :            : If this heap invariant is protected at all time, index 0 is clearly\n\
     612                 :            : the overall winner.  The simplest algorithmic way to remove it and\n\
     613                 :            : find the \"next\" winner is to move some loser (let's say cell 30 in the\n\
     614                 :            : diagram above) into the 0 position, and then percolate this new 0 down\n\
     615                 :            : the tree, exchanging values, until the invariant is re-established.\n\
     616                 :            : This is clearly logarithmic on the total number of items in the tree.\n\
     617                 :            : By iterating over all items, you get an O(n ln n) sort.\n"
     618                 :            : "\n\
     619                 :            : A nice feature of this sort is that you can efficiently insert new\n\
     620                 :            : items while the sort is going on, provided that the inserted items are\n\
     621                 :            : not \"better\" than the last 0'th element you extracted.  This is\n\
     622                 :            : especially useful in simulation contexts, where the tree holds all\n\
     623                 :            : incoming events, and the \"win\" condition means the smallest scheduled\n\
     624                 :            : time.  When an event schedule other events for execution, they are\n\
     625                 :            : scheduled into the future, so they can easily go into the heap.  So, a\n\
     626                 :            : heap is a good structure for implementing schedulers (this is what I\n\
     627                 :            : used for my MIDI sequencer :-).\n"
     628                 :            : "\n\
     629                 :            : Various structures for implementing schedulers have been extensively\n\
     630                 :            : studied, and heaps are good for this, as they are reasonably speedy,\n\
     631                 :            : the speed is almost constant, and the worst case is not much different\n\
     632                 :            : than the average case.  However, there are other representations which\n\
     633                 :            : are more efficient overall, yet the worst cases might be terrible.\n"
     634                 :            : "\n\
     635                 :            : Heaps are also very useful in big disk sorts.  You most probably all\n\
     636                 :            : know that a big sort implies producing \"runs\" (which are pre-sorted\n\
     637                 :            : sequences, which size is usually related to the amount of CPU memory),\n\
     638                 :            : followed by a merging passes for these runs, which merging is often\n\
     639                 :            : very cleverly organised[1].  It is very important that the initial\n\
     640                 :            : sort produces the longest runs possible.  Tournaments are a good way\n\
     641                 :            : to that.  If, using all the memory available to hold a tournament, you\n\
     642                 :            : replace and percolate items that happen to fit the current run, you'll\n\
     643                 :            : produce runs which are twice the size of the memory for random input,\n\
     644                 :            : and much better for input fuzzily ordered.\n"
     645                 :            : "\n\
     646                 :            : Moreover, if you output the 0'th item on disk and get an input which\n\
     647                 :            : may not fit in the current tournament (because the value \"wins\" over\n\
     648                 :            : the last output value), it cannot fit in the heap, so the size of the\n\
     649                 :            : heap decreases.  The freed memory could be cleverly reused immediately\n\
     650                 :            : for progressively building a second heap, which grows at exactly the\n\
     651                 :            : same rate the first heap is melting.  When the first heap completely\n\
     652                 :            : vanishes, you switch heaps and start a new run.  Clever and quite\n\
     653                 :            : effective!\n\
     654                 :            : \n\
     655                 :            : In a word, heaps are useful memory structures to know.  I use them in\n\
     656                 :            : a few applications, and I think it is good to keep a `heap' module\n\
     657                 :            : around. :-)\n"
     658                 :            : "\n\
     659                 :            : --------------------\n\
     660                 :            : [1] The disk balancing algorithms which are current, nowadays, are\n\
     661                 :            : more annoying than clever, and this is a consequence of the seeking\n\
     662                 :            : capabilities of the disks.  On devices which cannot seek, like big\n\
     663                 :            : tape drives, the story was quite different, and one had to be very\n\
     664                 :            : clever to ensure (far in advance) that each tape movement will be the\n\
     665                 :            : most effective possible (that is, will best participate at\n\
     666                 :            : \"progressing\" the merge).  Some tapes were even able to read\n\
     667                 :            : backwards, and this was also used to avoid the rewinding time.\n\
     668                 :            : Believe me, real good tape sorts were quite spectacular to watch!\n\
     669                 :            : From all times, sorting has always been a Great Art! :-)\n");
     670                 :            : 
     671                 :            : 
     672                 :            : static int
     673                 :          3 : heapq_exec(PyObject *m)
     674                 :            : {
     675                 :          3 :     PyObject *about = PyUnicode_FromString(__about__);
     676         [ -  + ]:          3 :     if (PyModule_AddObject(m, "__about__", about) < 0) {
     677                 :          0 :         Py_DECREF(about);
     678                 :          0 :         return -1;
     679                 :            :     }
     680                 :          3 :     return 0;
     681                 :            : }
     682                 :            : 
     683                 :            : static struct PyModuleDef_Slot heapq_slots[] = {
     684                 :            :     {Py_mod_exec, heapq_exec},
     685                 :            :     {0, NULL}
     686                 :            : };
     687                 :            : 
     688                 :            : static struct PyModuleDef _heapqmodule = {
     689                 :            :     PyModuleDef_HEAD_INIT,
     690                 :            :     "_heapq",
     691                 :            :     module_doc,
     692                 :            :     0,
     693                 :            :     heapq_methods,
     694                 :            :     heapq_slots,
     695                 :            :     NULL,
     696                 :            :     NULL,
     697                 :            :     NULL
     698                 :            : };
     699                 :            : 
     700                 :            : PyMODINIT_FUNC
     701                 :          3 : PyInit__heapq(void)
     702                 :            : {
     703                 :          3 :     return PyModuleDef_Init(&_heapqmodule);
     704                 :            : }

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