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.
If you are lazy, just perform
$ pip install decorator
which will install just the module on your system.
$ pip install .
in the main directory, possibly as superuser.
If you have the source code installation you can run the tests with
$ python src/tests/test.py -v
or (if you have setuptools installed)
$ python setup.py test
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.
The project is hosted on GitHub. You can look at the source here:
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:
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.warn('%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 preprocess_input_files(inputdir, tempdir): ... @warn_slow(timelimit=600) # warn if it takes more than 10 minutes def run_calculation(tempdir, outdir): ...