diff options
Diffstat (limited to 'doc/source')
| -rw-r--r-- | doc/source/release/1.21.0-notes.rst | 33 | ||||
| -rw-r--r-- | doc/source/user/building.rst | 4 |
2 files changed, 2 insertions, 35 deletions
diff --git a/doc/source/release/1.21.0-notes.rst b/doc/source/release/1.21.0-notes.rst index ac65b8fd0..c0d283b72 100644 --- a/doc/source/release/1.21.0-notes.rst +++ b/doc/source/release/1.21.0-notes.rst @@ -82,39 +82,6 @@ The methods in question are: Future Changes ============== -Promotion of strings with numbers and bools is deprecated ---------------------------------------------------------- -Any promotion of numbers and strings is deprecated and will -give a ``FutureWarning`` the main affected functionalities -are: - -* `numpy.promote_types` and `numpy.result_type` which will raise - an error in this case in the future. -* `numpy.concatenate` will raise an error when concatenating a string - and numeric array. You can use ``dtype="S"`` to explicitly request - a string result. -* `numpy.array` and related functions will start returning ``object`` - arrays because these functions use ``object`` as a fallback when - no common dtype can be found. However, it may happen that future - releases of NumPy will generally error in these cases. - -This will mainly affect code such as:: - - np.asarray(['string', 0]) - -and:: - - np.concatenate((['string'], [0])) - -in both cases adding ``dtype="U"`` or ``dtype="S"`` will give the -previous (string) result, while ``dtype=object`` will ensure an array with -object dtype is returned. - -Comparisons, universal functions, and casting are not affected by this. - -(`gh-18116 <https://github.com/numpy/numpy/pull/18116>`__) - - Expired deprecations ==================== diff --git a/doc/source/user/building.rst b/doc/source/user/building.rst index 52d7330bf..1d1286b42 100644 --- a/doc/source/user/building.rst +++ b/doc/source/user/building.rst @@ -24,8 +24,8 @@ Building NumPy requires the following software installed: 2) Compilers To build any extension modules for Python, you'll need a C compiler. - Various NumPy modules use FORTRAN 77 libraries, so you'll also need a - FORTRAN 77 compiler installed. + While a FORTRAN 77 compiler is not necessary for building NumPy, it is needed to run + the ``numpy.f2py`` tests. These tests are skipped if the compiler is not auto-detected. Note that NumPy is developed mainly using GNU compilers and tested on MSVC and Clang compilers. Compilers from other vendors such as Intel, |