Better living through Python with decorators
Project description
Decorator module
=================
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](
https://github.com/micheles/decorator) or download the
[tarball](http://pypi.python.org/pypi/decorator), 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 GitHub: https://raw.githubusercontent.com/micheles/decorator/master/docs/documentation.md
From there you can get a PDF version by simply using the print
functionality of your browser.
For the impatient
-----------------
Here is an example of how to define a family of decorators tracing slow
operations:
```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.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):
...
```
Enjoy!
=================
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](
https://github.com/micheles/decorator) or download the
[tarball](http://pypi.python.org/pypi/decorator), 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 GitHub: https://raw.githubusercontent.com/micheles/decorator/master/docs/documentation.md
From there you can get a PDF version by simply using the print
functionality of your browser.
For the impatient
-----------------
Here is an example of how to define a family of decorators tracing slow
operations:
```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.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):
...
```
Enjoy!
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