Language versions supported by NumPy 1.20.0 include Python 3.7 through Python 3.9 support has been dropped for Python 3.6. Installation instructions for NumPy can be found at.
Python type annotations code#
Cleanups have been made pertaining to removing Python 2.7, with code readability improved and technical debt removed. Inexact matches for mode and searchside have been deprecated. Use of aliases of built-in types such as np.int has been deprecated. When creating or assigning to arrays, in all revelant cases NumPy scalars now will be cast identically to NumPy arrays. The sliding_window_view function offers a sliding window view for NumPy arrays. Types in numpy.typing now can be imported at runtime. A where keyword argument has been added, to only consider specified elements or subaxes from an array in the Boolean evaluation of all and any. Indexing errors shall be reported even when the index result is empty. The randon.Generator class has a new permuted function. Preliminary support for version 3.0 of the Cython language for writing C extensions for Python. Preliminary work on changing the dtype (data type object) and casting implementations to provide for extending dtypes. Other additions and improvements in NumPy 1.20.0 include: In addition, improvements have been made to pave the way to NEP-38 (NumPy Enhancement Proposal) SIMD performance optimizations. Work was done to introduce universal functions that will ease the use of modern features on different hardware platforms. Wider use of SIMD in NumPy increases execution speed of universal functions (ufuncs). Currently available types include ArrayLike, for objects that can be coerced into an array, and DtypeLike, for objects that can be coerced into a dtype. 
There also is a new numpy.typing module containing useful types for end users.
Before Python 3. Release notes for NumPy 1.20.0 indicate type annotations have been added for large parts of NumPy. The focus of this tutorial is to talk about PEP 604, which makes writing union types easier when adding type annotation (AKA: type hinting) to your codebase. NumPy 1.20.0, described as the largest-ever release of the scientific computing package for Python, has arrived, introducing new capabilities such as type annotations and expanded use of SIMD (single instruction, multiple data).
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