2009年07月06日 星期一 23:12
fun and useful! ---------- Forwarded message ---------- From: Doug Hellmann <doug.hellmann+feedburner在gmail.com> Date: Mon, Jul 6, 2009 at 20:12 Subject: New command line interface to PyMOTW To: zoomquiet+sns在gmail.com New command line interface to PyMOTW ________________________________ New command line interface to PyMOTW Posted: 05 Jul 2009 06:30 AM PDT The 1.95 release of PyMOTW includes a command line interface to access the documentation for a module. The package can be installed via easy_install or pip: $ pip install PyMOTW Downloading/unpacking PyMOTW Downloading PyMOTW-1.95.tar.gz (2.2Mb): 2.2Mb downloaded Running setup.py egg_info for package PyMOTW warning: no files found matching 'ChangeLog' warning: no files found matching '*.py' under directory 'sphinx/templates' no previously-included directories found matching 'utils' Installing collected packages: PyMOTW Running setup.py install for PyMOTW changing mode of build/scripts-2.6/motw from 644 to 755 warning: no files found matching 'ChangeLog' warning: no files found matching '*.py' under directory 'sphinx/templates' no previously-included directories found matching 'utils' changing mode of /Users/dhellmann/.virtualenvs/testpymotw/bin/motw to 755 Successfully installed PyMOTW and then to use the command line interface, run motw. $ motw -h Usage: motw [options] Options: -h, --help show this help message and exit -t, --text Print plain-text version of help to stdout -w, --web Open HTML version of help from web --html Open HTML version of help from installed file For example, motw abc opens the local version of this week's article. You can also use the "-w" option to go to my web site instead of reading the local version, so you always have the latest version of an article. PyMOTW: abc - Abstract Base Classes Posted: 05 Jul 2009 06:18 AM PDT abc – Abstract Base Classes Purpose:Define and use abstract base classes for API checks in your code. Python Version:2.6 Why use Abstract Base Classes? Abstract base classes are a form of interface checking more strict than individual hasattr() checks for particular methods. By defining an abstract base class, you can define a common API for a set of subclasses. This capability is especially useful in situations where a third-party is going to provide implementations, such as with plugins to an application, but can also aid you when working on a large team or with a large code-base where keeping all classes in your head at the same time is difficult or not possible. How ABCs Work abc works by marking methods of the base class as abstract, and then registering concrete classes as implementations of the abstract base. If your code requires a particular API, you can use issubclass() or isinstance() to check an object against the abstract class. Let’s start by defining an abstract base class to represent the API of a set of plugins for saving and loading data. import abc class PluginBase(object): __metaclass__ = abc.ABCMeta @abc.abstractmethod def load(self, input): """Retrieve data from the input source and return an object.""" return @abc.abstractmethod def save(self, output, data): """Save the data object to the output.""" return Registering a Concrete Class There are two ways to indicate that a concrete class implements an abstract: register the class with the abc or subclass directly from the abc. import abc from abc_base import PluginBase class RegisteredImplementation(object): def load(self, input): return input.read() def save(self, output, data): return output.write(data) PluginBase.register(RegisteredImplementation) if __name__ == '__main__': print 'Subclass:', issubclass(RegisteredImplementation, PluginBase) print 'Instance:', isinstance(RegisteredImplementation(), PluginBase) In this example the PluginImplementation is not derived from PluginBase, but is registered as implementing the PluginBase API. $ python abc_register.py Subclass: True Instance: True Implementation Through Subclassing By subclassing directly from the base, we can avoid the need to register the class explicitly. import abc from abc_base import PluginBase class SubclassImplementation(PluginBase): def load(self, input): return input.read() def save(self, output, data): return output.write(data) if __name__ == '__main__': print 'Subclass:', issubclass(SubclassImplementation, PluginBase) print 'Instance:', isinstance(SubclassImplementation(), PluginBase) In this case the normal Python class management is used to recognize PluginImplementation as implementing the abstract PluginBase. $ python abc_subclass.py Subclass: True Instance: True A side-effect of using direct subclassing is it is possible to find all of the implementations of your plugin by asking the base class for the list of known classes derived from it (this is not an abc feature, all classes can do this). import abc from abc_base import PluginBase import abc_subclass import abc_register for sc in PluginBase.__subclasses__(): print sc.__name__ Notice that even though abc_register is imported, RegisteredImplementation is not among the list of subclasses because it is not actually derived from the base. $ python abc_find_subclasses.py SubclassImplementation Dr. Andr√© Roberge has described using this capability to discover plugins by importing all of the modules in a directory dynamically and then looking at the subclass list to find the implementation classes. Incomplete Implementations Another benefit of subclassing directly from your abstract base class is that the subclass cannot be instantiated unless it fully implements the abstract portion of the API. This can keep half-baked implementations from triggering unexpected errors at runtime. import abc from abc_base import PluginBase class IncompleteImplementation(PluginBase): def save(self, output, data): return output.write(data) PluginBase.register(IncompleteImplementation) if __name__ == '__main__': print 'Subclass:', issubclass(IncompleteImplementation, PluginBase) print 'Instance:', isinstance(IncompleteImplementation(), PluginBase) $ python abc_incomplete.py Subclass: True Instance: Traceback (most recent call last): File "abc_incomplete.py", line 22, inprint 'Instance:', isinstance(IncompleteImplementation(), PluginBase) TypeError: Can't instantiate abstract class IncompleteImplementation with abstract methods load Concrete Methods in ABCs Although a concrete class must provide an implementation of an abstract methods, the abstract base class can also provide an implementation that can be invoked via super(). This lets you re-use common logic by placing it in the base class, but force subclasses to provide an overriding method with (potentially) custom logic. import abc from cStringIO import StringIO class ABCWithConcreteImplementation(object): __metaclass__ = abc.ABCMeta @abc.abstractmethod def retrieve_values(self, input): print 'base class reading data' return input.read() class ConcreteOverride(ABCWithConcreteImplementation): def retrieve_values(self, input): base_data = super(ConcreteOverride, self).retrieve_values(input) print 'subclass sorting data' response = sorted(base_data.splitlines()) return response input = StringIO("""line one line two line three """) reader = ConcreteOverride() print reader.retrieve_values(input) print Since ABCWithConcreteImplementation is an abstract base class, it isn’t possible to instantiate it to use it directly. Subclasses must provide an override for retrieve_values(), and in this case the concrete class massages the data before returning it at all. $ python abc_concrete_method.py base class reading data subclass sorting data ['line one', 'line three', 'line two'] Abstract Properties If your API specification includes attributes in addition to methods, you can require the attributes in concrete classes by defining them with @abstractproperty. import abc class Base(object): __metaclass__ = abc.ABCMeta @abc.abstractproperty def value(self): return 'Should never get here' class Implementation(Base): @property def value(self): return 'concrete property' try: b = Base() print 'Base.value:', b.value except Exception, err: print 'ERROR:', str(err) i = Implementation() print 'Implementation.value:', i.value The Base class in the example cannot be instantiated because it has only an abstract version of the property getter method. $ python abc_abstractproperty.py ERROR: Can't instantiate abstract class Base with abstract methods value Implementation.value: concrete property You can also define abstract read/write properties. import abc class Base(object): __metaclass__ = abc.ABCMeta def value_getter(self): return 'Should never see this' def value_setter(self, newvalue): return value = abc.abstractproperty(value_getter, value_setter) class PartialImplementation(Base): @abc.abstractproperty def value(self): return 'Read-only' class Implementation(Base): _value = 'Default value' def value_getter(self): return self._value def value_setter(self, newvalue): self._value = newvalue value = property(value_getter, value_setter) try: b = Base() print 'Base.value:', b.value except Exception, err: print 'ERROR:', str(err) try: p = PartialImplementation() print 'PartialImplementation.value:', p.value except Exception, err: print 'ERROR:', str(err) i = Implementation() print 'Implementation.value:', i.value i.value = 'New value' print 'Changed value:', i.value Notice that the concrete property must be defined the same way as the abstract property. Trying to override a read/write property in PartialImplementation with one that is read-only does not work. $ python abc_abstractproperty_rw.py ERROR: Can't instantiate abstract class Base with abstract methods value ERROR: Can't instantiate abstract class PartialImplementation with abstract methods value Implementation.value: Default value Changed value: New value Unfortunately, the decorator syntax does not work for read/write abstract properties the way it does with concrete properties. import abc class Base(object): __metaclass__ = abc.ABCMeta @abc.abstractproperty def value(self): return 'Should never see this' @value.setter def value_setter(self, newvalue): return class Implementation(Base): _value = 'Default value' @property def value(self): return self._value @value.setter def value_setter(self, newvalue): self._value = newvalue i = Implementation() print 'Implementation.value:', i.value i.value = 'New value' print 'Changed value:', i.value Notice that the caller cannot set the property value. $ python abc_abstractproperty_rw_deco.py Implementation.value: Default value Traceback (most recent call last): File "abc_abstractproperty_rw_deco.py", line 40, in i.value = 'New value' AttributeError: can't set attribute Collection Types The collections module defines several abstract base classes related to container (and containable) types. General container classes: Container Sized Iterator and Sequence classes: Iterable Iterator Sequence MutableSequence Unique values: Hashable Set MutableSet Mappings: Mapping MutableMapping MappingView KeysView ItemsView ValuesView Miscelaneous: Callable In addition to serving as detailed real-world examples of abstract base classes, Python’s built-in types are automatically registered to these classes when you import collections. This means you can safely use isinstance() to check parameters in your code to ensure that they support the API you need. The base classes can also be used to define your own collection types, since many of them provide concrete implementations of the internals and only need a few methods overridden. Refer to the standard library docs for collections for more details. See also abcThe standard library documentation for this module.PEP 3119Introducing Abstract Base ClassescollectionsThe collections module includes abstract base classes for several collection types.collectionsThe standard library documentation for collections.PEP 3141A Type Hierarchy for NumbersWikipedia: Strategy PatternDescription and examples of the strategy pattern.Plugins and monkeypatchingPyCon 2009 presentation by Dr. Andr√© Roberge PyMOTW Home The canonical version of this article You are subscribed to email updates from Doug Hellmann To stop receiving these emails, you may unsubscribe now.Email delivery powered by Google Google Inc., 20 West Kinzie, Chicago IL USA 60610 -- http://zoomquiet.org 人生苦短,Pythonic!-) 工作的层次(依靠谱程度从低到高)=有做- 做完- 做对- 做好- 帮助他人做好
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