Stefan Krah <[email protected]> added the comment:
Kristján, could you check out the new implementation over at #10181?
I have trouble reproducing a big speed difference between bytearray
and memoryview (Linux, 64-bit). Here are the timings I get for the
current and the new version:
Slicing
-------
1) ./python -m timeit -n 10000000 -s "x = bytearray(b'x'*10000)" "x[:100]"
2) ./python -m timeit -n 10000000 -s "x = memoryview(bytearray(b'x'*10000))"
"x[:100]"
1) cpython: 0.137 usec pep-3118: 0.138 usec
2) cpython: 0.132 usec pep-3118: 0.132 usec
Slicing with overhead for multidimensional capabilities:
--------------------------------------------------------
1) ./python -m timeit -n 10000000 -s "import _testbuffer; x =
_testbuffer.ndarray([ord('x') for _ in range(10000)], shape=[10000])" "x[:100]"
2) ./python -m timeit -n 10000000 -s "import numpy; x =
numpy.ndarray(buffer=bytearray(b'x'*10000), shape=[10000], dtype='B')" "x[:100]"
1) _testbuffer.c: 0.198 usec
2) numpy: 0.415 usec
Slice assignment
----------------
1) ./python -m timeit -n 10000000 -s "x = bytearray(b'x'*10000)" "x[5:10] =
x[7:12]"
2) ./python -m timeit -n 10000000 -s "x = memoryview(bytearray(b'x'*10000))"
"x[5:10] = x[7:12]"
1) cpython: 0.242 usec pep-3118: 0.240 usec
2) cpython: 0.282 usec pep-3118: 0.287 usec
Slice assignment, overhead for multidimensional capabilities
------------------------------------------------------------
1) ./python -m timeit -n 10000000 -s "import _testbuffer; x =
_testbuffer.ndarray([ord('x') for _ in range(10000)], shape=[10000],
flags=_testbuffer.ND_WRITABLE)" "x[5:10] = x[7:12]"
2) ./python -m timeit -n 10000000 -s "import numpy; x =
numpy.ndarray(buffer=bytearray(b'x'*10000), shape=[10000], dtype='B')" "x[5:10]
= x[7:12]"
_testbuffer.c: 0.469 usec
numpy: 1.37 usec
tolist
------
1) ./python -m timeit -n 10000 -s "import array; x = array.array('B',
b'x'*10000)" "x.tolist()"
2) ./python -m timeit -n 10000 -s "x = memoryview(bytearray(b'x'*10000))"
"x.tolist()"
1) cpython, array: 104.0 usec
2) pep-3118, memoryview: 90.5 usec
tolist, struct module overhead
------------------------------
1) ./python -m timeit -n 10000 -s "import _testbuffer; x =
_testbuffer.ndarray([ord('x') for _ in range(10000)], shape=[10000])"
"x.tolist()"
2) ./python -m timeit -n 10000 -s "import numpy; x =
numpy.ndarray(buffer=bytearray(b'x'*10000), shape=[10000], dtype='B')"
"x.tolist()"
_testbuffer.c: 1.38 msec (yes, that's microseconds!)
numpy: 104 usec
----------
nosy: +skrah
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<http://bugs.python.org/issue10227>
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