# Shared numpy array

**URL:** <https://discuss.ray.io/t/shared-numpy-array/6871>\
**Category:** Ray Core\
**Created:** [July 19, 2022, 1:34am UTC](https://discuss.ray.io/t/shared-numpy-array/6871 "2022-07-19T01:34:22Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![vsraptor](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/vsraptor/32/2841_2.png) [@vsraptor](https://discuss.ray.io/u/vsraptor)\
**Post date:** [July 19, 2022, 1:34am UTC](https://discuss.ray.io/t/shared-numpy-array/6871/1 "2022-07-19T01:34:22Z")

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Does Ray support shared numpy arrays like this

> **[GitHub - widmi/multiprocess-shared-numpy-arrays: Easily share numpy arrays...](https://github.com/widmi/multiprocess-shared-numpy-arrays)**
>
> Easily share numpy arrays between processes. Contribute to widmi/multiprocess-shared-numpy-arrays development by creating an account on GitHub.

[https://docs.python.org/3.4/library/multiprocessing.html?highlight=process#multiprocessing.Array](https://docs.python.org/3.4/library/multiprocessing.html?highlight=process#multiprocessing.Array)

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**Author:** ![Clark\_Zinzow](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/clark_zinzow/32/445_2.png) [@Clark\_Zinzow](https://discuss.ray.io/u/Clark_Zinzow)\
**Post date:** [July 19, 2022, 4:15pm UTC](https://discuss.ray.io/t/shared-numpy-array/6871/2 "2022-07-19T16:15:31Z")

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@vsraptor Yes, NumPy ndarrays stored in Ray’s object store will support zero-copy shared memory access! [Serialization — Ray 3.0.0.dev0](https://docs.ray.io/en/master/ray-core/objects/serialization.html#numpy-arrays)