New submission from swanson:
Comparing two array.array objects is much slower than it ought to be.
The whole point of array.array is to be efficient:
"array — Efficient arrays of numeric values"
But comparing them is orders of magnitude less efficient than comparing tuples
or lists of numbers. It would seem that array's __eq__ is converting every
single number into an int, float, etc. first instead of just comparing the
arrays in their native format.
If arrays can be copied efficiently, and bytearray can be copied or compared
efficiently, there's no good reason for array's equality test to be so stupid.
example code:
-------------
from timeit import timeit
setup = '''
from array import array
a = array("I", %s)
ac = a.__copy__
b = ac()
t = tuple(a)
u = t[:1] + t[1:]
'''
for init in ("[1]*10", "[0xffffffff]*10", "[1]*1000", "[0xffffffff]*1000"):
print("\n", init)
for action in ("ac()", "a == b", "a == ac()", "t == u"):
print(("%6.2f" % timeit(action, setup % init)), action)
results:
--------
[1]*10
0.31 ac()
0.50 a == b
0.73 a == ac()
0.17 t == u
[0xffffffff]*10
0.29 ac()
1.59 a == b
1.87 a == ac()
0.15 t == u
[1]*1000
0.84 ac()
37.06 a == b
37.72 a == ac()
2.91 t == u
[0xffffffff]*1000
0.84 ac()
146.03 a == b
145.97 a == ac()
2.90 t == u
----------
components: Library (Lib)
messages: 247234
nosy: swanson
priority: normal
severity: normal
status: open
title: array compare is hideously slow
type: performance
versions: Python 3.4
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Python tracker <[email protected]>
<http://bugs.python.org/issue24700>
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