./devel/py-makefun, Small library to dynamically create python functions

[ CVSweb ] [ Homepage ] [ RSS ] [ Required by ] [ Add to tracker ]


Branch: CURRENT, Version: 1.15.4, Package name: py311-makefun-1.15.4, Maintainer: pkgsrc-users

makefun helps you create functions dynamically, with the signature
of your choice. It was largely inspired by decorator and functools,
and created mainly to cover some of their limitations.

The typical use cases are:

* creating signature-preserving function wrappers - just like
functools.wraps but with accurate TypeError exception raising when
user-provided arguments are wrong, and with a very convenient way
to access argument values.

* creating function wrappers that have more or less arguments that
the function they wrap. A bit like functools.partial but a lot more
flexible and friendly for your users. For example, I use it in my
pytest plugins to add a requests parameter to users' tests or
fixtures when they do not already have it.

* more generally, creating functions with a signature derived from
a reference signature,

* or even creating functions with a signature completely defined
at runtime.


Master sites:

Filesize: 70.469 KB

Version history: (Expand)


CVS history: (Expand)


   2023-11-26 15:22:06 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-makefun: updated to 1.15.2

1.15.2 - bugfix

- Fixed `SyntaxError` happening when the name of a native coroutine function to \ 
create contains `'return'`.
   2023-04-30 20:35:37 by Thomas Klausner | Files touched by this commit (1)
Log message:
py-makefun: not for python 2
   2023-04-13 14:29:36 by Thomas Klausner | Files touched by this commit (1)
Log message:
py-makefun: try fixing PLIST for python2
   2023-03-12 14:39:01 by Thomas Klausner | Files touched by this commit (4)
Log message:
devel/py-makefun: import py-makefun-1.15.1

makefun helps you create functions dynamically, with the signature
of your choice. It was largely inspired by decorator and functools,
and created mainly to cover some of their limitations.

The typical use cases are:

* creating signature-preserving function wrappers - just like
functools.wraps but with accurate TypeError exception raising when
user-provided arguments are wrong, and with a very convenient way
to access argument values.

* creating function wrappers that have more or less arguments that
the function they wrap. A bit like functools.partial but a lot more
flexible and friendly for your users. For example, I use it in my
pytest plugins to add a requests parameter to users' tests or
fixtures when they do not already have it.

* more generally, creating functions with a signature derived from
a reference signature,

* or even creating functions with a signature completely defined
at runtime.