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The sequences supplied to a list comprehension don t have to be the same length because they re iterated over their contents using a nested set of for loops, as previously shownThe resulting list contains successive values of expressionsThe if clause is optional; however, if it s used, expression is evaluated and added to the result only if condition is true If a list comprehension is used to construct a list of tuples, the tuple values must be enclosed in parentheses For example, [(x,y) for x in a for y in b] is legal syntax, whereas [x,y for x in a for y in b] is not Finally, it is important to note that in Python 2, the iteration variables defined within a list comprehension are evaluated within the current scope and remain defined after the list comprehension has executed For example, in [x for x in a], the iteration variable x overwrites any previously defined value of x and is set to the value of the last item in a after the resulting list is created Fortunately, this is not the case in Python 3 where the iteration variable remains private

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A generator expression is an object that carries out the same computation as a list comprehension, but which iteratively produces the resultThe syntax is the same as for list comprehensions except that you use parentheses instead of square brackets Here s an example:

This fact has led to the recent development of the Agile OO Methodologies, including XP XP says that since a design will inevitably change, you should embrace change, and adopt an adaptive development process See 9

When you execute the application, the response should be changed (Figure 9 3)

(expression for item1 in iterable1 if condition1 for item2 in iterable2 if condition2 for itemN in iterableN if conditionN)

Unlike a list comprehension, a generator expression does not actually create a list or immediately evaluate the expression inside the parentheses Instead, it creates a generator object that produces the values on demand via iteration Here s an example:

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>>> a = [1, 2, 3, 4] >>> b = (10*i for i in a) >>> b <generator object at 0x590a8> >>> bnext() 10 >>> bnext() 20

Internationalization is the process of preparing an application to support various languages Localization is the process of adapting an internationalized application to support a specific language or locale Although all client user interfaces should be internationalized and localized, it is particularly important for Web clients because of the far-reaching nature of the Web For a good overview of internationalization and localization, see

The difference between list and generator expressions is important, but subtleWith a list comprehension, Python actually creates a list that contains the resulting dataWith a generator expression, Python creates a generator that merely knows how to produce data on demand In certain applications, this can greatly improve performance and memory use Here s an example:

file:///C|/oobook/4html (51 of 51) [13/03/2003 02:55:19 }

# Read a file f = open("datatxt") lines = (tstrip() for t in f) # # # comments = (t for t in lines if t[0] == '#') # for c in comments: print(c) Open a file Read lines, strip trailing/leading whitespace All comments

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In this example, the generator expression that extracts lines and strips whitespace does not actually read the entire file into memoryThe same is true of the expression that extracts comments Instead, the lines of the file are actually read when the program starts iterating in the for loop that follows During this iteration, the lines of the file are produced upon demand and filtered accordingly In fact, at no time will the entire file be loaded into memory during this processTherefore, this would be a highly efficient way to extract comments from a gigabyte-sized Python source file Unlike a list comprehension, a generator expression does not create an object that works like a sequence It can t be indexed, and none of the usual list operations will work (for example, append()) However, a generator expression can be converted into a list using the built-in list() function:

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