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Improve clarity (and small speed-up) by using tuple unpacking (#3289)

This commit is contained in:
Raymond Hettinger 2017-09-04 11:47:58 -07:00 committed by GitHub
parent 5ce1063345
commit 1bfbe78b03
1 changed files with 8 additions and 8 deletions
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16
Lib/heapq.py
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@ -498,10 +498,10 @@ def nsmallest(n, iterable, key=None):
for elem in it:
if elem < top:
_heapreplace(result, (elem, order))
top = result[0][0]
top, _order = result[0]
order += 1
result.sort()
return [r[0] for r in result]
return [elem for (elem, order) in result]
# General case, slowest method
it = iter(iterable)
@ -516,10 +516,10 @@ def nsmallest(n, iterable, key=None):
k = key(elem)
if k < top:
_heapreplace(result, (k, order, elem))
top = result[0][0]
top, _order, _elem = result[0]
order += 1
result.sort()
return [r[2] for r in result]
return [elem for (k, order, elem) in result]
def nlargest(n, iterable, key=None):
"""Find the n largest elements in a dataset.
@ -559,10 +559,10 @@ def nlargest(n, iterable, key=None):
for elem in it:
if top < elem:
_heapreplace(result, (elem, order))
top = result[0][0]
top, _order = result[0]
order -= 1
result.sort(reverse=True)
return [r[0] for r in result]
return [elem for (elem, order) in result]
# General case, slowest method
it = iter(iterable)
@ -577,10 +577,10 @@ def nlargest(n, iterable, key=None):
k = key(elem)
if top < k:
_heapreplace(result, (k, order, elem))
top = result[0][0]
top, _order, _elem = result[0]
order -= 1
result.sort(reverse=True)
return [r[2] for r in result]
return [elem for (k, order, elem) in result]
# If available, use C implementation
try: