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| author | Ralf Gommers <ralf.gommers@gmail.com> | 2020-04-27 12:16:14 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2020-04-27 12:16:14 +0200 |
| commit | 389f56c80c9d940d79fe4136b7a99f8d29aef8d8 (patch) | |
| tree | dca14b0dc9a23de71a3eeb2b6e265954dd1215d2 | |
| parent | 87964f1c5738492b152e80f7e38010c69214e5ae (diff) | |
| parent | e2db0a80937bc0e00b35d9b2bf67189dc1ea072d (diff) | |
| download | numpy-389f56c80c9d940d79fe4136b7a99f8d29aef8d8.tar.gz | |
Merge pull request #16084 from mattip/protocols
DOC: tweak neps/scope.rst
| -rw-r--r-- | doc/neps/scope.rst | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/doc/neps/scope.rst b/doc/neps/scope.rst index 61eab2ea6..93887c4b1 100644 --- a/doc/neps/scope.rst +++ b/doc/neps/scope.rst @@ -14,7 +14,8 @@ Here, we describe aspects of N-d array computation that are within scope for Num - NumPy is a *de facto* standard for array APIs in Python - Indexing and fast iteration over elements (ufunc) - - Interoperability protocols with other data container implementations (like `__array_ufunc__`). + - Interoperability protocols with other data container implementations (like + :ref:`__array_ufunc__ and __array_function__ <basics.dispatch>`. - **Python API and a C API** to the ndarray's methods and attributes. @@ -35,7 +36,8 @@ Here, we describe aspects of N-d array computation that are within scope for Num - NumPy provides some **infrastructure for other packages in the scientific Python ecosystem**: - - numpy.distutils (build support for C++, Fortran, BLAS/LAPACK, and other relevant libraries for scientific computing) + - numpy.distutils (build support for C++, Fortran, BLAS/LAPACK, and other + relevant libraries for scientific computing) - f2py (generating bindings for Fortran code) - testing utilities |