Consider using literal syntax to create the data structure PTC-W0019
Performance
Minor
4 years ago
—
4 years old
unnecessary
dict call - write as literal 85 cache_valid = path_hash == self._path_checksum
86 self._path_checksum = path_hash
87 # did aliases change?
88 alss = getattr(builtins, "aliases", dict()) 89 al_hash = hash(frozenset(alss))
90 cache_valid = cache_valid and al_hash == self._alias_checksum
91 self._alias_checksum = al_hashunnecessary
list call - write as literal 69
70 @staticmethod
71 def remove_dups(p):
72 ret = list() 73 for e in p:
74 if e not in ret:
75 ret.append(e)
Description
Using the literal syntax can give minor performance bumps compared to using function calls to create dict, list and tuple.
In [1]: timeit.timeit(stmt="dict()", number=100000000)
Out[1]: 9.560388602000103
In [2]: timeit.timeit(stmt="{}", number=100000000)
Out[2]: 1.685333584000091
In [3]: timeit.timeit(stmt="tuple()", number=100000000)
Out[3]: 4.509182139000131
In [4]: timeit.timeit(stmt="()", number=100000000)
Out[4]: 0.5455615430000762
In [5]: timeit.timeit(stmt="list()", number=100000000)
Out[5]: 7.356000728000254
In [6]: timeit.timeit(stmt="[]", number=100000000)
Out[6]: 1.573771306999788
This is because here, the name dict must be looked up in the global scope in case it has been rebound.
Same goes for the other two types list() and tuple().