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.

Testing

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.

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:

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 preprocess_input_files(inputdir, tempdir):
    ...

@warn_slow(timelimit=600)  # warn if it takes more than 10 minutes
def run_calculation(tempdir, outdir):
    ...

Enjoy!