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| author | mattip <matti.picus@gmail.com> | 2020-04-25 21:55:09 +0300 |
|---|---|---|
| committer | mattip <matti.picus@gmail.com> | 2020-04-25 21:56:20 +0300 |
| commit | e2db0a80937bc0e00b35d9b2bf67189dc1ea072d (patch) | |
| tree | 15a086e7d4da055cb4162496caa6959ade9a3a4c | |
| parent | 59984a3596e00e088b10c58f02856e8088fcd4df (diff) | |
| download | numpy-e2db0a80937bc0e00b35d9b2bf67189dc1ea072d.tar.gz | |
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 |