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The __new__() method is called before any object has been created (since object creation is what __new__() does), so it cannot have a self object passed to it since one doesn t yet exist In fact, __new__() is a class method these are similar to normal methods except that they are called on the class rather than on an instance and Python supplies as their rst argument the class they are called on The variable name cls for class is just a convention, in the same way that self is the conventional name for the object itself So when we write f = FuzzyBool(07), under the hood Python calls FuzzyBool__new__(FuzzyBool, 07) to create a new object say, fuzzy and then calls fuzzy__init__() to do any further initialization, and nally returns an object reference to the fuzzy object it is this object reference that f is set to Most of __new__() s work is passed on to the base class implementation, object__new__(); all we do is make sure that the value is in range Class methods are set up by using the built-in classmethod() function used as a decorator But as a convenience we don t have to bother writing @classmethod before def __new__() because Python already knows that this method is always a class method We do need to use the decorator if we want to create other class methods, though, as we will see in the chapter s nal section Now that we have seen a class method we can clarify the different kinds of methods that Python provides Class methods have their rst argument added by Python and it is the method s class; normal methods have their rst argument added by Python and it is the instance the method was called on; and static methods have no rst argument added And all the kinds of methods get any arguments we pass to them (as their second and subsequent arguments in the case of class and normal methods, and as their rst and subsequent arguments for static methods).

def __invert__(self): return FuzzyBool(10 - float(self))

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A typical transaction is illustrated in the event transition diagram in Figure 192, and it consists of the following steps: 1 Using the discovery agent (DA), the user chooses a MIDlet to install The MIDlet will be referenced by a URL that points to either an Java Application Descriptor File (JAD) or a JAR 2 If the URL references an application descriptor, the device downloads it and examines its contents as a preflight check In this way it ensures that the device has suitable capabilities and resources to run the MIDlet before attempting the download of the JAR, which is typically much larger 3 If the URL that the user chose represents a JAR, or if the application descriptor preflight check was successful, the device downloads the JAR and installs it 4 The device sends a notification to the server indicating the installation status, whether successful or not

This method is used to provide support for the bitwise NOT operator (~) just the same as before Notice that instead of accessing a private attribute that holds the FuzzyBool s value we use self directly This is thanks to inheriting float which means that a FuzzyBool can be used wherever a float is expected providing none of the FuzzyBool s unimplemented methods are used, of course

One instance is created per client session and only one thread is created to process requests for that session If the client makes multiple asynchronous calls on a session, they are queued and processed in FIFO order One instance is created per client session and only one thread is created to process requests for that session If the client makes multiple asynchronous calls on a session, they are queued and processed in FIFO order The single thread can leave the method, do other work, and come back later, as may be the case with server-side asynchronous coding One instance is created per client session but multiple threads can run in parallel through the instance If the client makes multiple asynchronous calls on a session, they are processed in parallel Class members must be protected with synchronization code because the same members can be modi ed by multiple threads

def __and__(self, other): return FuzzyBool(min(self, other)) def __iand__(self, other): return FuzzyBool(min(self, other))

The logic for these is also the same as before (although the code is subtly different), and just like the __invert__() method we can use both self and other

[ Team LiB ]

directly as though they were floats We have omitted the OR versions since they differ only in their names (__or__() and __ior__()) and that they use max() rather than min()

One instance is created per call Concurrency mode doesn t matter because each instance will have its own thread of execution

def __repr__(self): return ("{0}({1})"format(self__class____name__, super()__repr__()))

We must reimplement the __repr__() method since the base class version float__repr__() just returns the number as a string, whereas we need the class name to make the representation eval()-able For the strformat() s second argument we cannot just pass self since that will result in an in nite recursion of calls to this __repr__() method, so instead we call the base class implementation We don t have to reimplement the __str__() method because the base class version, float__str__(), is suf cient and will be used in the absence of a FuzzyBool__str__() reimplementation

[ Team LiB ]

def __bool__(self): return self > 05 def __int__(self): return round(self)

One instance is created per call Concurrency mode doesn t matter because each instance will have its own thread of execution

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