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Decoupling code behavior
Observer, and a category of callbacks called “multiple dispatching (not in Design Patterns)” including the Visitor from Design Patterns. Like the other forms of callback, this contains a hook point where you can change code. The difference is in the observer’s completely dynamic nature. It is often used for the specific case of changes based on other object’s change of state, but is also the basis of event management. Anytime you want to decouple the source of the call from the called code in a completely dynamic way.
The observer pattern solves a fairly common problem: What if a group of objects needs to update themselves when some object changes state? This can be seen in the “model-view” aspect of Smalltalk’s MVC (model-view-controller), or the almost-equivalent “Document-View Architecture.” Suppose that you have some data (the “document”) and more than one view, say a plot and a textual view. When you change the data, the two views must know to update themselves, and that’s what the observer facilitates. It’s a common enough problem that its solution has been made a part of the standard java.util library.
There are two types of objects used to implement the observer pattern in Python. The Observable class keeps track of everybody who wants to be informed when a change happens, whether the “state” has changed or not. When someone says “OK, everybody should check and potentially update themselves,” the Observable class performs this task by calling the notifyObservers( ) method for each one on the list. The notifyObservers( )method is part of the base class Observable.
There are actually two “things that change” in the observer pattern: the quantity of observing objects and the way an update occurs. That is, the observer pattern allows you to modify both of these without affecting the surrounding code.
Observer is an “interface” class that only has one member function, update( ). This function is called by the object that’s being observed, when that object decides its time to update all its observers. The arguments are optional; you could have an update( ) with no arguments and that would still fit the observer pattern; however this is more general-it allows the observed object to pass the object that caused the update (since an Observer may be registered with more than one observed object) and any extra information if that’s helpful, rather than forcing the Observer object to hunt around to see who is updating and to fetch any other information it needs.
The “observed object” that decides when and how to do the updating will be called the Observable.
Observable has a flag to indicate whether it’s been changed. In a simpler design, there would be no flag; if something happened, everyone would be notified. The flag allows you to wait, and only notify the Observers when you decide the time is right. Notice, however, that the control of the flag’s state is protected, so that only an inheritor can decide what constitutes a change, and not the end user of the resulting derived Observer class.
Most of the work is done in notifyObservers( ). If the changed flag has not been set, this does nothing. Otherwise, it first clears the changed flag so repeated calls to notifyObservers( ) won’t waste time. This is done before notifying the observers in case the calls to update( ) do anything that causes a change back to this Observable object. Then it moves through the set and calls back to the update( ) member function of each Observer.
At first it may appear that you can use an ordinary Observable object to manage the updates. But this doesn’t work; to get an effect, you must inherit from Observable and somewhere in your derived-class code call setChanged( ). This is the member function that sets the “changed” flag, which means that when you call notifyObservers( ) all of the observers will, in fact, get notified. Where you call setChanged( ) depends on the logic of your program.