Advanced Programming Techniques in Java

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In this chapter we will look at a wide variety of different programming techniques and introduce many additional, often more advanced, Python syntaxes Some of the material in this chapter is quite challenging, but keep in mind that the most advanced techniques are rarely needed and you can always skim the rst time to get an idea of what can be done and read more carefully when the need arises The chapter s rst section digs more deeply into Python s procedural features It starts by showing how to use what we already covered in a novel way, and then returns to the theme of generators that we only touched on in 6 The section then introduces dynamic programming loading modules by name at runtime and executing arbitrary code at runtime The section returns to the theme of local (nested) functions, but in addition covers the use of the nonlocal keyword and recursive functions Earlier we saw how to use Python s prede ned decorators in this section we learn how to create our own decorators The section concludes with coverage of function annotations The second section covers all new material relating to object-oriented programming It begins by introducing __slots__, a mechanism for minimizing the memory used by each object It then shows how to access attributes without using properties The section also introduces functors (objects that can be called like functions), and context managers these are used in conjunction with the with keyword, and in many cases (eg, le handling) they can be used to replace try except finally constructs with simpler try except constructs The section also shows how to create custom context managers, and introduces additional advanced object-oriented features, including class decorators, abstract base classes, multiple inheritance, and metaclasses The third section introduces some fundamental concepts of functional programming, and introduces some useful functions from the functools, itertools, 339
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and operator modules This section also shows how to use partial function application to simplify code, and how to create and use coroutines All the previous chapters put together have provided us with the standard Python toolbox This chapter takes everything that we have already covered and turns it into the deluxe Python toolbox , with all the original tools (techniques and syntaxes), plus many new ones that can make our programming easier, shorter, and more effective Some of the tools can have interchangeable uses, for example, some jobs can be done using either a class decorator or a metaclass, whereas others, such as descriptors, can be used in multiple ways to achieve different effects Some of the tools covered here, for example, context managers, we will use all the time, and others will remain ready at hand for those particular situations for which they are the perfect solution
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Most of this section deals with additional facilities relating to procedural programming and functions, but the very rst subsection is different in that it presents a useful programming technique based on what we already covered without introducing any new syntax
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As we noted earlier, functions are objects like everything else in Python, and a function s name is an object reference that refers to the function If we write a function s name without parentheses, Python knows we mean the object reference, and we can pass such object references around just like any others We can use this fact to replace if statements that have lots of elif clauses with a single function call In 12 we will review an interactive console program called dvds-dbmpy, that has the following menu:
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The program has a function that gets the user s choice and which will return only a valid choice, in this case one of a , e , l , r , i , x , and q Here are two equivalent code snippets for calling the relevant function based on the user s choice:
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if action == "a": add_dvd(db) elif action == "e": edit_dvd(db)
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