def nsmallest(n, iterable, key=None): """Find the n smallest elements in a dataset. Equivalent to: sorted(iterable, key=key)[:n] """ # Short-cut for n==1 is to use min() if n == 1: it = iter(iterable) sentinel = object() result = min(it, default=sentinel, key=key) return [] if result is sentinel else [result] # When n>=size, it's faster to use sorted() try: size = len(iterable) except (TypeError, AttributeError): pass else: if n >= size: return sorted(iterable, key=key)[:n] # When key is none, use simpler decoration if key is None: it = iter(iterable) # put the range(n) first so that zip() doesn't # consume one too many elements from the iterator result = [(elem, i) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: if elem < top: _heapreplace(result, (elem, order)) top, _order = result[0] order += 1 result.sort() return [elem for (elem, order) in result] # General case, slowest method it = iter(iterable) result = [(key(elem), i, elem) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: k = key(elem) if k < top: _heapreplace(result, (k, order, elem)) top, _order, _elem = result[0] order += 1 result.sort() return [elem for (k, order, elem) in result]
def nsmallest(n, iterable, key=None): """Find the n smallest elements in a dataset. Equivalent to: sorted(iterable, key=key)[:n] """ if n == 1: it = iter(iterable) sentinel = object() if key is None: result = min(it, default=sentinel) else: result = min(it, default=sentinel, key=key) return [] if result is sentinel else [result] try: size = len(iterable) except (TypeError, AttributeError): pass else: if n >= size: return sorted(iterable, key=key)[:n] if key is None: it = iter(iterable) result = [(elem, i) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: if elem < top: _heapreplace(result, (elem, order)) top = result[0][0] order += 1 result.sort() return [r[0] for r in result] it = iter(iterable) result = [(key(elem), i, elem) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: k = key(elem) if k < top: _heapreplace(result, (k, order, elem)) top = result[0][0] order += 1 result.sort() return [r[2] for r in result]
def nsmallest(n, iterable, key=None): """Find the n smallest elements in a dataset. Equivalent to: sorted(iterable, key=key)[:n] """ # Short-cut for n==1 is to use min() if n == 1: it = iter(iterable) sentinel = object() if key is None: result = min(it, default=sentinel) else: result = min(it, default=sentinel, key=key) return [] if result is sentinel else [result] # When n>=size, it's faster to use sorted() try: size = len(iterable) except (TypeError, AttributeError): pass else: if n >= size: return sorted(iterable, key=key)[:n] # When key is none, use simpler decoration if key is None: it = iter(iterable) # put the range(n) first so that zip() doesn't # consume one too many elements from the iterator result = [(elem, i) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: if elem < top: _heapreplace(result, (elem, order)) top = result[0][0] order += 1 result.sort() return [r[0] for r in result] # General case, slowest method it = iter(iterable) result = [(key(elem), i, elem) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: k = key(elem) if k < top: _heapreplace(result, (k, order, elem)) top = result[0][0] order += 1 result.sort() return [r[2] for r in result]
size = len(iterable) except (TypeError, AttributeError): pass else: if n >= size: return sorted(iterable, key=key)[:n] # When key is none, use simpler decoration if key is None: it = iter(iterable) # put the range(n) first so that zip() doesn't # consume one too many elements from the iterator result = [(elem, i) for i, elem in zip(range(n), it)] if not result: return result _heapify_max(result) top = result[0][0] order = n _heapreplace = _heapreplace_max for elem in it: if elem < top: _heapreplace(result, (elem, order)) top, _order = result[0] order += 1 result.sort() return [elem for (elem, order) in result] # General case, slowest method it = iter(iterable) result = [(key(elem), i, elem) for i, elem in zip(range(n), it)] if not result:
# # n=[3,2,3,1,2,4,5,5,6] # l=len(n) # k=4 # n.sort() # print(n) # print(n[l-k]) import _heapq n= [1,2,3] k=2 maxheap=_heapq._heapify_max(n) # print(_heapq._heappop_max(n)) # print(_heapq._heappop_max(n)) # print(_heapq._heappop_max(n)) # print(_heapq._heappop_max(n)) for i in range(k): _heapq._heappop_max(n) if i==k-2: print(_heapq._heappop_max(n))