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 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:

.. 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 preprocess_input_files(inputdir, tempdir): ...

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

Enjoy!