[Numpy-discussion] Numpy on Python3
Sun Nov 22 23:35:52 CST 2009
$ mkdir -p $PWD/dist/lib/python3.1/site-packages
$ python3 setup.py install --prefix=$PWD/dist
$ cd $PWD/dist/lib/python3.1/site-packages && python3
Python 3.1.1+ (r311:74480, Oct 11 2009, 20:22:16)
[GCC 4.4.1] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
XXX: 3K: numpy.random is disabled for now, uses PyString_*
XXX: 3K: numpy.ma is disabled for now -- some issues
>>> numpy.array([1., 2, 3, 4])
array([ 1., 2., 3., 4.])
>>> _ + 10
array([ 11., 12., 13., 14.])
>>> numpy.ones((4,), dtype=complex)/4
array([ 0.25+0.j, 0.25+0.j, 0.25+0.j, 0.25+0.j])
>>> numpy.array([object(), object()])
array([<object object at 0xb7778810>, <object object at 0xb7778d90>],
Things were fairly straightforward this far, just many tiny changes.
What's left is then sorting out the bigger problems :)
This is still far from being complete:
- Most use of PyString_* needs auditing (note e.g. the b'object' in the
dtype print above...).
I simply added convenience wrappers for PyString -> PyBytes,
but this is not the correct choice at all points.
- Also, should dtype='S' be Bytes or Unicode? I chose Bytes for now.
- Whether to inherit Numpy ints from PyLong_* needs some thinking,
as they are quite different objects. Now, I dropped the inheritance,
but I wonder if this will break something.
- PyFile_AsFile has disappeared, and AsFileDescriptor+fdopen doesn't
seem to cut it -- don't know exactly what's wrong here.
- Integer -> String formatting does not seem to work
- Larger-than-long-long Python ints probably cause problems
- The new buffer interface needs to be implemented -- currently there
are just error-raising stubs.
I remember Dag was working on this a bit: how far did it go?
- Relative imports + 2to3 is a bit of a pain. A pity we can't have
them in the mainline code because of python2.4.
- I didn't check for semantic changes in tp_* interface functions.
This we need still to do.
- And probably many other issues lurking.
Also, I didn't yet try checking how far the test suite passes on
Python3. (It still passes completely on Python2, so at least I didn't
break that part.)
It might be nice to have this merged in at some point after 1.4.0 (after
the most obvious glaring bugs have been fixed), so that we could perhaps
start aiming for Python3 compatibility in Numpy 1.5.0.
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