[issue5141] C API for appending to arrays

Change by Jeffrey Kintscher : -- nosy: +Jeffrey.Kintscher ___ Python tracker ___ ___ Python-bugs-list mailing list Unsubscribe: http

[issue5141] C API for appending to arrays

Change by STINNER Victor : -- components: +C API ___ Python tracker ___ ___ Python-bugs-list mailing list Unsubscribe: https://mail.

[issue5141] C API for appending to arrays

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[issue5141] C API for appending to arrays

Changes by Ramchandra Apte : -- components: +Library (Lib) ___ Python tracker ___ ___ Python-bugs-list mailing list Unsubscribe: http:

[issue5141] C API for appending to arrays

kxroberto added the comment: A first thing would be to select a suitable prefix name for the Array API. Because the Numpy people have 'stolen' PyArray_ instead of staying home with PyNDArray_ or so ;-) In case sb goes into this: Other than PyList_ like stuff and existing members, think for spee

[issue5141] C API for appending to arrays

Antoine Pitrou added the comment: This has more chances of seeing some progress if you propose a patch. -- nosy: +pitrou ___ Python tracker ___ __

[issue5141] C API for appending to arrays

kxroberto added the comment: I had a similar problem creating a C-fast array.array interface for Cython. The array.pxd package here (latest zip file) http://trac.cython.org/cython_trac/ticket/314 includes a arrayarray.h file, which provides ways for efficient creation and growth from C (extend,

[issue5141] C API for appending to arrays

Hrvoje Nikšić added the comment: Yes, and I use it in the second example, but the buffer interface doesn't really help with adding new elements into the array. ___ Python tracker ___

[issue5141] C API for appending to arrays

Gabriel Genellina added the comment: Arrays already support the buffer interface -- nosy: +gagenellina ___ Python tracker ___ ___ Pyth

[issue5141] C API for appending to arrays

New submission from Hrvoje Nikšić : The array.array type is an excellent type for storing a large amount of "native" elements, such as integers, chars, doubles, etc., without involving the heavy machinery of numpy. It's both blazingly fast and reasonably efficient with memory. The one thing mis