openKylin python-wrapt package

python-wrapt 1.11.2-ok1 source package in openKylin

python-wrapt (1.11.2-ok1) yangtze; urgency=medium

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Series	Pocket	Published	Component	Section

File	Size	SHA-256 Checksum
python-wrapt_1.11.2.orig.tar.xz	96.9 KiB	0017aac5241e4be9c1a8d4cec49977c698fb5c37227c03dc9fc1ddb6cf02ce9f
python-wrapt_1.11.2-ok1.debian.tar.xz	4.1 KiB	df2dffbeea56c4ce1b0075ab7c9d94e74f941f98b24e291d8de096df4e5b2289
python-wrapt_1.11.2-ok1.dsc	2.0 KiB	c25a4dffd670e3bc916c021d1aa2eda9b95e736c2783228e29c437ab53f51613

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.