https://github.com/pypr/cyarray

A fast, typed, resizable, Cython array.
https://github.com/pypr/cyarray

Last synced: 5 months ago
JSON representation

A fast, typed, resizable, Cython array.

• Host: GitHub
• URL: https://github.com/pypr/cyarray
• Owner: pypr
• License: other
• Created: 2018-11-30T01:04:58.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2024-12-13T17:57:06.000Z (over 1 year ago)
• Last Synced: 2025-02-24T03:04:19.543Z (over 1 year ago)
• Language: Cython
• Size: 140 KB
• Stars: 9
• Watchers: 2
• Forks: 6
• Open Issues: 2
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.txt

Awesome Lists containing this project

README

          
cyarray: a typed, re-sizable Cython array

------------------------------------------

|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.