decorator
Decorators for Humans =====================
The goal of the decorator module is to make it easy to define signature-preserving function decorators and decorator factories. It also includes an implementation of multiple dispatch and other niceties (please check the docs). It is released under a two-clauses BSD license, i.e. basically you can do whatever you want with it but I am not responsible.
Installation
If you are lazy, just perform
`$ pip install decorator
which will install just the module on your system.
If you prefer to install the full distribution from source, including the documentation, clone the GitHub repo or download the tarball, unpack it and run
$ pip install .
in the main directory, possibly as superuser.
.. _tarball: https://pypi.org/project/decorator/#files .. _GitHub repo: https://github.com/micheles/decorator
Testing
If you have the source code installation you can run the tests with
$ python tests/test.py -v
Notice that you may run into trouble if in your system there is an older version of the decorator module; in such a case remove the old version. It is safe even to copy the module decorator.py` over an existing one, since we kept backward-compatibility for a long time.
Repository
The project is hosted on GitHub. You can look at the source here:
https://github.com/micheles/decorator
Documentation
The documentation has been moved to https://github.com/micheles/decorator/blob/master/docs/documentation.md
From there you can get a PDF version by simply using the print functionality of your browser.
Here is the documentation for previous versions of the module:
https://github.com/micheles/decorator/blob/4.3.2/docs/tests.documentation.rst https://github.com/micheles/decorator/blob/4.2.1/docs/tests.documentation.rst https://github.com/micheles/decorator/blob/4.1.2/docs/tests.documentation.rst https://github.com/micheles/decorator/blob/4.0.0/documentation.rst https://github.com/micheles/decorator/blob/3.4.2/documentation.rst
For the impatient
Here is an example of how to define a family of decorators tracing slow operations:
.. code-block:: python
from decorator import decorator
@decorator def warn_slow(func, timelimit=60, args, *kw): t0 = time.time() result = func(args, *kw) dt = time.time() - t0 if dt > timelimit: logging.warning('%s took %d seconds', func.name, dt) else: logging.info('%s took %d seconds', func.name, dt) return result
@warn_slow # warn if it takes more than 1 minute def preprocessinputfiles(inputdir, tempdir): ...
@warn_slow(timelimit=600) # warn if it takes more than 10 minutes def run_calculation(tempdir, outdir): ...
Enjoy!
