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cyarray: a typed, re-sizable Cython array
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|CI Status| |Documentation Status|
.. |CI Status| image:: https://github.com/pypr/cyarray/actions/workflows/tests.yml/badge.svg
:target: https://github.com/pypr/cyarray/actions/workflows/tests.yml
.. |Documentation Status| image:: https://readthedocs.org/projects/cyarray/badge/?version=latest
:target: https://cyarray.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
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.
Installation
------------
cyarray can be installed using pip_::
$ pip install cyarray
The package requires ``Cython``, ``numpy``, and ``mako`` to be installed and
also requires a suitably configured C/C++ compiler.
.. _pip: http://www.pip-installer.org
Usage
-----
In Python one may import and use the package as::
from cyarray.api import IntArray
a = IntArray(10)
Here ``a`` is an array of 10 integers.
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