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--- stacks_queues [2020/01/14 02:11] – jrseti
+++ stacks_queues [2020/01/14 02:16] (current) – jrseti
@@ Line 4: / Line 4: @@
 ====heapqueue====
-  heapq.**__heappush__**(heap, item)
+https://docs.python.org/2/library/heapq.html
+  heapq.heappush(heap, item)
   Push the value item onto the heap, maintaining the heap invariant.
-  heapq.**__heappop__**(heap)
+  heapq.heappop(heap)
   Pop and return the smallest item from the heap, maintaining the heap invariant. If the heap is empty, IndexError
   is raised. To access the smallest item without popping it, use heap[0].
-  heapq.**__heappushpop__**(heap, item)
+  heapq.heappushpop(heap, item)
-  Push item on the heap, then pop and return the smallest item from the heap. The combined action runs more
+  Push item on the heap, then pop and return the smallest item from the heap. The
-  efficiently than heappush() followed by a separate call to heappop().
+  combined action runs more efficiently than heappush() followed by a separate call
+  to heappop().
-  heapq.__heapify__(x)
+  heapq.heapify(x)
   Transform list x into a heap, in-place, in linear time.
-  heapq.**__heapreplace__**(heap, item)
+  heapq.heapreplace(heap, item)
-  Pop and return the smallest item from the heap, and also push the new item. The heap size doesn’t change. If the
+  Pop and return the smallest item from the heap, and also push the new item. The
-  heap is empty, IndexError is raised.
+  heap size doesn’t change. If the heap is empty, IndexError is raised.
-  This one step operation is more efficient than a heappop() followed by heappush() and can be more appropriate
+  This one step operation is more efficient than a heappop() followed by heappush()
-  when using a fixed-size heap. The pop/push combination always returns an element from the heap and replaces it
+  and can be more appropriate when using a fixed-size heap. The pop/push combination
+  always returns an element from the heap and replaces it
   with item.
-  The value returned may be larger than the item added. If that isn’t desired, consider using heappushpop() instead. Its push/pop combination returns the smaller of the two values, leaving the larger value on the heap.
+  The value returned may be larger than the item added. If that isn’t desired,
+  consider using heappushpop() instead. Its push/pop combination returns the smaller
-The module also offers three general purpose functions based on heaps.
+  of the two values, leaving the larger value on the heap.
-heapq.**__merge__**(*iterables)
+  The module also offers three general purpose functions based on heaps.
-Merge multiple sorted inputs into a single sorted output (for example, merge timestamped entries from multiple log files). Returns an iterator over the sorted values.
+  heapq.merge(*iterables)
-Similar to sorted(itertools.chain(*iterables)) but returns an iterable, does not pull the data into memory all at once, and assumes that each of the input streams is already sorted (smallest to largest).
+  Merge multiple sorted inputs into a single sorted output (for example, merge
+  timestamped entries from multiple log files). Returns an iterator over the sorted values.
-heapq.**__nlargest__**(n, iterable[, key])
-Return a list with the n largest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in the iterable: key=str.lower Equivalent to: sorted(iterable, key=key, reverse=True)[:n]
+  Similar to sorted(itertools.chain(*iterables)) but returns an iterable, does not pull
+  the data into memory all at once, and assumes that each of the input streams is already
-heapq.**__nsmallest__**(n, iterable[, key])
+  sorted (smallest to largest).
-Return a list with the n smallest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in the iterable: key=str.lower Equivalent to: sorted(iterable, key=key)[:n]
+  heapq.nlargest(n, iterable[, key])
+  Return a list with the n largest elements from the dataset defined by iterable. key,
+  if provided, specifies a function of one argument that is used to extract a comparison
+  key from each element in the iterable: key=str.lower Equivalent to:
+    sorted(iterable, key=key, reverse=True)[:n]
+  heapq.nsmallest(n, iterable[, key])
+  Return a list with the n smallest elements from the dataset defined by iterable. key,
+  if provided, specifies a function of one argument that is used to extract a comparison
+  key from each element in the iterable: key=str.lower
+    Equivalent to: sorted(iterable, key=key)[:n]