openKylin python-wrapt package

python-wrapt 1.15.0-ok1 source package in openKylin

python-wrapt (1.15.0-ok1) nile; urgency=medium

  * Build for openKylin.

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Series	Pocket	Published	Component	Section
Nile V2.0	release	on 2024-06-06	main	python
Nile V2.0	proposed	on 2024-05-07	main	python

File	Size	SHA-256 Checksum
python-wrapt_1.15.0.orig.tar.xz	106.4 KiB	20b278b8f45f2daafad221f998aa21ce89f3ffabe14583495949ab435501f6e0
python-wrapt_1.15.0-ok1.debian.tar.xz	4.4 KiB	8cefbaa548ebb83e01359f6a81895e885ac18edab80145a79252f9bbf8a63844
python-wrapt_1.15.0-ok1.dsc	2.1 KiB	aba334a0005136087d9287ca0ca62677af607b6fcebf36b9757867f11a924c39

python-wrapt-doc: decorators, wrappers and monkey patching. - doc: The aim of the wrapt module is to provide a transparent object proxy for
Python, which can be used as the basis for the construction of function
wrappers and decorator functions.
.
The wrapt module focuses very much on correctness. It therefore goes way
beyond existing mechanisms such as functools.wraps() to ensure that decorators
preserve introspectability, signatures, type checking abilities etc. The
decorators that can be constructed using this module will work in far more
scenarios than typical decorators and provide more predictable and consistent
behaviour.
.
To ensure that the overhead is as minimal as possible, a C extension module is
used for performance critical components. An automatic fallback to a pure
Python implementation is also provided where a target system does not have a
compiler to allow the C extension to be compiled.
.
This package contains the documentation.

python3-wrapt: decorators, wrappers and monkey patching. - Python 3.x: The aim of the wrapt module is to provide a transparent object proxy for
Python, which can be used as the basis for the construction of function
wrappers and decorator functions.
.
The wrapt module focuses very much on correctness. It therefore goes way
beyond existing mechanisms such as functools.wraps() to ensure that decorators
preserve introspectability, signatures, type checking abilities etc. The
decorators that can be constructed using this module will work in far more
scenarios than typical decorators and provide more predictable and consistent
behaviour.
.
To ensure that the overhead is as minimal as possible, a C extension module is
used for performance critical components. An automatic fallback to a pure
Python implementation is also provided where a target system does not have a
compiler to allow the C extension to be compiled.
.
This package contains the Python 3.x module.