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Add back list() when iterating over d.items() in a for statement #262

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6 changes: 0 additions & 6 deletions modernize/fixes/fix_dict_six.py
Original file line number Diff line number Diff line change
Expand Up @@ -43,9 +43,3 @@ def transform(self, node, results):
return super().transform(node, results)
else:
return self.transform_iter(node, results)

def in_special_context(self, node, isiter):
# Redefined from parent class to make "for x in d.items()" count as
# in special context; fissix only counts for loops as special context
# for the iter* methods.
return super().in_special_context(node, True)
6 changes: 3 additions & 3 deletions tests/test_fix_dict_six.py
Original file line number Diff line number Diff line change
Expand Up @@ -38,11 +38,11 @@
DICT_IN_LOOP = (
"""\
for k in x.items():
pass
del x[k]
""",
"""\
for k in x.items():
pass
for k in list(x.items()):
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really this should be for k in x.copy().items(): because list(x.items()) isn't threadsafe when x.items() was threadsafe on Python 2

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That’s something to consider. copy() does have the advantage of being atomic and being about 10% faster:

# python3.9
>>> import timeit
>>> timeit.timeit(setup='d = dict(zip(range(10000), range(10000)))', stmt='sum(d.copy().keys())', number=10000)
0.814354999999999
>>> timeit.timeit(setup='d = dict(zip(range(10000), range(10000)))', stmt='sum(list(d.keys()))', number=10000)
0.9197422089999989

Downsides of switching to copy():

The point of this PR is to restore the 2to3 fix_dict behavior which identifies all the items(), keys(), and values() that may need to change. After manual review, you may find statements where the list() is unnecessary (and you could have used iteritems() before) or you may switch to d.copy() for concurrency and performance. I think changing from list() to .copy() warrants a separate PR.

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@graingert are you requesting me to change it to .copy()?

del x[k]
""",
)

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