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Bug#940954: marked as done (ITP: cyarray -- fast, typed, resizable, Cython array)

Your message dated Sun, 22 Sep 2019 17:45:26 +0200
with message-id <ba5ac037-b70c-f943-46a4-a0d0bc968098@tiscali.it>
and subject line Closing
has caused the Debian Bug report #940954,
regarding ITP: cyarray -- fast, typed, resizable, Cython array
to be marked as done.

This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.

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-- 
940954: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=940954
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--- Begin Message --- 
Package: wnpp
Severity: wishlist
Owner: Antonio Valentino <antonio.valentino@tiscali.it>

* Package name    : cyarray
  Version         : 1.1
  Upstream Author : Cyarray Developers <pysph-dev@googlegroups.com>
* URL             : http://github.com/pypr/cyarray
* License         : BSD
  Programming Lang: Python
  Description     : fast, typed, resizable, Cython array

Binary package names: python3-cyarray
 The cyarray package provides a fast, typed, re-sizable, Cython array.
 .
 It currently provides the following arrays: ``IntArray, UIntArray,
 LongArray, FloatArray, DoubleArray``.
 .
 All arrays provide for the following operations:
 .
 - access by indexing.
 - access through get/set function.
 - resizing the array.
 - appending values at the end of the array.
 - reserving space for future appends.
 - access to internal data through a numpy array.
 .
 If you are writing Cython code this is a convenient array to use
 as it exposes the raw underlying pointer to the data.
 For example if you use a ``FloatArray`` and access its ``data``
 attribute it will be a ``float*``.
 .
 Each array also provides an interface to its data through a numpy
 array.
 This is done through the ``get_npy_array`` function. The returned numpy
 array can be used just like any other numpy array but for the following
 restrictions:
 .
 - the array may not be resized.
 - references of this array should not be kept.
 - slices of this array may not be made.
 .
 The numpy array may however be copied and used in any manner.


--
Antonio Valentino

--- End Message ---
--- Begin Message --- 
Duplicate of #940953

-- 
Antonio Valentino

--- End Message ---
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