Some of you may have noticed that things have been changing rapidly in the NumPy world (if you were out of the office in June then all the activity may seem overwhelming).
All of this activity is based on the fact that the upcoming beta release will mean a feature freeze for NumPy. As a review: The biggest changes over the past 3 months have been 1) Capitalized-type-names (Float32, Complex64, Int8, etc) are now only available in the numpy.oldnumeric namespace (this is the namespace that convertcode.py replaces for Numeric). We are trying to wean you off character codes as much as possible. They are still there, of course but should only be used in special cases not as a general rule. 2) Un-specified data-types now default to floating point. To help with code you have that relies on integer data-types you can either use functions from numpy.oldnumeric where the functions are still defined with the integer-default data-types or use functions in numpy/lib/convdtype to replace type-less versions of ones, zeros, empty with empty(..., dtype=int). 3) C-API names have prefix PyArray_ (like always), NPY_ or npy_. The NPY_ and npy_ prefixes are new and were done to remove the likelihood of name collisions when NumPy is used with another library. The old (and un-prefixed) names are accessible by importing numpy/noprefix.h instead of numpy/arrayobject.h It is fine to use noprefix.h in-place of arrayobject.h if you expect to have no naming conflicts. This is what NumPy itself does. 4) The flag combinations with _FLAGS in the name have the _FLAGS removed (but are prefixed with NPY_). Again the old names are still available in numpy/noprefix.h 5) The Numarray C-API is now available as numpy/libnumarray.h as long as you use the directory returned from numpy.get_numarray_include() as an argument to -I in the compile command. More minor changes: 1) ctypes attribute added for ease of working with ctypes data 2) T attribute added as a convenience for .transpose() Personally, I don't want to make any more changes so that we can make a 1.0 beta release that will freeze the API. Because of my guarantee to keep SVN versions of NumPy/SciPy/matplotlib working, changes probably cause more headache for me than anyone else. Unless there is a serious issue pointed out, the only thing that should be changed at this point are bug-fixes, documentation strings, and added tests. Once 1.0b1 is released nothing but those things can be added. I'd like July to be a much more calm month. We should get the 1.0b1 out in the next couple of weeks. That way perhaps 1.0b2 can be out by the SciPy conference. I can see the beta release period taking several months with only bug-fixes/docstring/testing improvements happening over that time. So, take this message as a warning for the up-coming feature freeze on NumPy and an invitation to contribute docstrings and unit-tests. I hope the rapid pace of June development did not scare too many people. Please voice your concerns if you have them. Best regards, -Travis O. Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
