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The easiest reimplementation is simply def copy(self): return SortedDict( self) We ve chosen a slightly more complicated solution that avoids re-sorting the already sorted keys We create an empty sorted dictionary, then update it with the items in the original sorted dictionary using the base class dictupdate() to avoid the SortedDictupdate() reimplementation, and replace the dictionary s self__keys SortedList with a shallow copy of the original one When super() is called with no arguments it works on the base class and the self object But we can make it work on any class and any object by passing in a class and an object explicitly Using this syntax, the super() call works on the immediate base class of the class it is given, so in this case the code has the same effect as (and could be written as) dictupdate(d, self) In view of the fact that Python s sort algorithm is very fast, and is particularly well optimized for partially sorted lists, the ef ciency gain is likely to be little or nothing except for huge dictionaries However, the implementation shows that at least in principle, a custom copy() method can be more ef cient than using the copy_of_x = ClassOfX(x) idiom that Python s built-in types support And just as we did for SortedList, we have set __copy__ = copy so that the copycopy() function uses our custom copy method rather than its own code

[ Team LiB ]

def value_at(self, index): return self[self__keys[index]] def set_value_at(self, index, value): self[self__keys[index]] = value

Listing 514 shows a self-hosted service that exposes metadata It is functionally equivalent to the con guration in Listing 513

These two methods represent an extension to the dict API Since, unlike a plain dict, a SortedDict is ordered, it follows that the concept of key index positions is applicable For example, the rst item in the dictionary is at index position 0, and the last at position len(d) - 1 Both of these methods operate on the dictionary item whose key is at the index-th position in the sorted keys list Thanks to inheritance, we can look up values in the SortedDict using the item access op-

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erator ([]) applied directly to self, since self is a dict If an out-of-range index is given the methods raise an IndexError exception We have now completed the implementation of the SortedDict class It is not often that we need to create complete generic collection classes like this, but when we do, Python s special methods allow us to fully integrate our class so that its users can treat it like any of the built-in or standard library classes

Summary

[ Team LiB ]

Implementing Transactions (Operation Behavior)

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This chapter covered all the fundamentals of Python s support for object-oriented programming We began by showing some of the disadvantages of a purely procedural approach and how these could be avoided by using object orientation We then described some of the most common terminology used in objectoriented programming, including many duplicate terms such as base class and super class We saw how to create simple classes with data attributes and custom methods We also saw how to inherit classes and how to add additional data attributes and additional methods, and how methods can be unimplemented Unimplementing is needed when we inherit a class but want to restrict the methods that our subclass provides, but it should be used with care since it breaks the expectation that a subclass can be used wherever one of its base classes can be used, that is, it breaks polymorphism Custom classes can be seamlessly integrated so that they support the same syntaxes as Python s built-in and library classes This is achieved by implementing special methods We saw how to implement special methods to support comparisons, how to provide representational and string forms, and how to provide conversions to other types such as int and float when it makes sense to do so We also saw how to implement the __hash__() method to make a custom class s instances usable as dictionary keys or as members of a set Data attributes by themselves provide no mechanism for ensuring that they are set to valid values We saw how easy it is to replace data attributes with properties this allows us to create read-only properties, and for writable properties makes it easy to provide validation Most of the classes we create are incomplete since we tend to provide only the methods that we actually need This works ne in Python, but in addition it is possible to create complete custom classes that provide every relevant method We saw how to do this for single valued classes, both by using aggregation and more compactly by using inheritance We also saw how to do this for multivalued (collection) classes Custom collection classes can provide the same facilities as the built-in collection classes, including support for in, len(), iter(), reversed(), and the item access operator ([]).

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