Book Excerpt: The Python Standard Library by Example
Acquiring Function Properties for Decorators
Updating the properties of a wrapped callable is especially useful when used in a decorator, since the transformed function ends up with properties of the original “bare” function.
import functools def show_details(name, f): """Show details of a callable object.""" print ’%s:’ % name print ’ object:’,f print ’ __name__:’, try: print f.__name__ except AttributeError: print ’(no __name__)’ print ’ __doc__’, repr(f.__doc__) print return def simple_decorator(f): @functools.wraps(f) def decorated(a=’decorated defaults’, b=1): print ’ decorated:’, (a, b) print ’’, f(a, b=b) return return decorated def myfunc(a, b=2): "myfunc() is not complicated" print ’ myfunc:’, (a,b) return # The raw function show_details(’myfunc’, myfunc) myfunc(’unwrapped, default b’) myfunc(’unwrapped, passing b’, 3) print # Wrap explicitly wrapped_myfunc = simple_decorator(myfunc) show_details(’wrapped_myfunc’, wrapped_myfunc) wrapped_myfunc() wrapped_myfunc(’args to wrapped’, 4) print # Wrap with decorator syntax @simple_decorator def decorated_myfunc(a, b): myfunc(a, b) return show_details(’decorated_myfunc’, decorated_myfunc) decorated_myfunc() decorated_myfunc(’args to decorated’, 4)
functools provides a decorator, wraps(), that applies update_wrapper() to the decorated function.
$ python functools_wraps.py myfunc: object: <function myfunc at 0x100da3488> __name__: myfunc __doc__ ’myfunc() is not complicated’ myfunc: (’unwrapped, default b’, 2) myfunc: (’unwrapped, passing b’, 3) wrapped_myfunc: object: <function myfunc at 0x100da3500> __name__: myfunc __doc__ ’myfunc() is not complicated’ decorated: (’decorated defaults’, 1) myfunc: (’decorated defaults’, 1) decorated: (’args to wrapped’, 4) myfunc: (’args to wrapped’, 4) decorated_myfunc: object: <function decorated_myfunc at 0x100da35f0> __name__: decorated_myfunc __doc__ None decorated: (’decorated defaults’, 1) myfunc: (’decorated defaults’, 1) decorated: (’args to decorated’, 4) myfunc: (’args to decorated’, 4)
Practical Task Scheduling Deployment
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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|The Firebird Project's Firebird Relational Database||Jul 29, 2016|
|Stunnel Security for Oracle||Jul 28, 2016|
|SUSE LLC's SUSE Manager||Jul 21, 2016|
|My +1 Sword of Productivity||Jul 20, 2016|
|Non-Linux FOSS: Caffeine!||Jul 19, 2016|
|Murat Yener and Onur Dundar's Expert Android Studio (Wrox)||Jul 18, 2016|
- Stunnel Security for Oracle
- The Firebird Project's Firebird Relational Database
- Murat Yener and Onur Dundar's Expert Android Studio (Wrox)
- SUSE LLC's SUSE Manager
- Managing Linux Using Puppet
- My +1 Sword of Productivity
- Non-Linux FOSS: Caffeine!
- Google's SwiftShader Released
- SuperTuxKart 0.9.2 Released
- Doing for User Space What We Did for Kernel Space
With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide