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In Python 2.4, a relative of list comprehension (see 5) was introduced: generator comprehension (or generator expressions). It works in the same way as list comprehension, except that a list isn t constructed (and the body isn t looped over immediately). Instead, a generator is returned, allowing you to perform the computation step by step: >>> g = ((i+2)**2 for i in range(2,27)) >>> g.next() 16 As you can see, this differs from list comprehension in the use of plain parentheses. In a simple case such as this, I might as well have used a list comprehension. However, if you wish to wrap an iterable object (possibly yielding a huge number of values), a list comprehension would void the advantages of iteration by immediately instantiating a list. A neat bonus is that when using generator comprehension directly inside a pair of existing parentheses, such as in a function call, you don t need to add another pair. In other words, you can write pretty code like this: sum(i**2 for i in range(10))

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It s important to decide whether an XML application should use client-side XML, server-side XML, or some combination of the two types of processing. So far, you ve seen several clients that can work with XML content. In s 5 to 10, you ll look at client-side communication in more detail. s 11 to 13 will examine server-side applications. In this section, I ll cover different approaches for client-side and server-side interactions in XML applications.

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The generator I designed in the previous section could deal only with lists nested two levels deep, and to do that it used two for loops. What if you have a set of lists nested arbitrarily deeply Perhaps you use them to represent some tree structure, for example. (You can also do that with specific tree classes, but the strategy is the same.) You need a for loop for each level of nesting, but because you don t know how many levels there are, you must change your solution to be more flexible. It s time to turn to the magic of recursion: def flatten(nested): try: for sublist in nested: for element in flatten(sublist): yield element except TypeError: yield nested When flatten is called, you have two possibilities (as is always the case when dealing with recursion): the base case and the recursive case. In the base case, the function is told to flatten a single element (for example, a number), in which case the for loop raises a TypeError (because you re trying to iterate over a number), and the generator simply yields the element. If you are told to flatten a list (or any iterable), however, you need to do some work. You go through all the sublists (some of which may not really be lists) and call flatten on them. Then you yield all the elements of the flattened sublists by using another for loop. It may seem slightly magical, but it works: >>> list(flatten([[[1],2],3,4,[5,[6,7]],8])) [1, 2, 3, 4, 5, 6, 7, 8]

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