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authorHameer Abbasi <hameerabbasi@yahoo.com>2019-07-31 20:35:18 +0500
committerHameer Abbasi <hameerabbasi@yahoo.com>2019-07-31 20:35:18 +0500
commit014c5ef4c3b0eae2558391d94466ec648992132f (patch)
tree9163f95ddcdb1caf12c21532b46af43ec59a91aa
parent3691300fac685afe3677449c78c7334011d18406 (diff)
downloadnumpy-014c5ef4c3b0eae2558391d94466ec648992132f.tar.gz
Complete incomplete sentence.
-rw-r--r--doc/neps/nep-0030-uarray.rst6
1 files changed, 4 insertions, 2 deletions
diff --git a/doc/neps/nep-0030-uarray.rst b/doc/neps/nep-0030-uarray.rst
index b3883492a..f32c6e781 100644
--- a/doc/neps/nep-0030-uarray.rst
+++ b/doc/neps/nep-0030-uarray.rst
@@ -32,9 +32,11 @@ This NEP takes a more holistic approach: It assumes that there are parts of the
overridable, and that these will grow over time. It provides a general framework and a mechanism to
avoid a design of a new protocol each time this is required.
-The second is to ease the creation of new duck-arrays,
+The second is to ease the creation of new duck-arrays, by providing default implementations of many
+functions that can be easily expressed in terms of others, as well as a repository of utility functions
+that help in the implementation of duck-arrays that most duck-arrays would require.
-The second is the existence of actual, third party dtype packages, and
+The third is the existence of actual, third party dtype packages, and
their desire to blend into the NumPy ecosystem. `[6]`_. This is a separate
issue compared to the C-level dtype redesign proposed in `[7]`_, it's about
allowing third-party dtype implementations to work with NumPy, much like third-party array