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Diffstat (limited to 'doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst')
| -rw-r--r-- | doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst b/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst index 907f08fb6..6d1f8bf27 100644 --- a/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst +++ b/doc/neps/nep-0035-array-creation-dispatch-with-array-function.rst @@ -120,9 +120,9 @@ conversion, ultimately raising a Now we should look at how a library like Dask could benefit from ``like=``. Before we understand that, it's important to understand a bit about Dask basics -and ensures correctness with ``__array_function__``. Note that Dask can perform -computations on different sorts of objects, like dataframes, bags and arrays, -here we will focus strictly on arrays, which are the objects we can use +and how it ensures correctness with ``__array_function__``. Note that Dask can +perform computations on different sorts of objects, like dataframes, bags and +arrays, here we will focus strictly on arrays, which are the objects we can use ``__array_function__`` with. Dask uses a graph computing model, meaning it breaks down a large problem in |