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image_re = recompile(r""" <img\s+ # start of tag [^>]* # non-src attributes src= # start of src attribute ( : ( P<quote>["']) # opening quote ( P<qimage>[^\1>]+ ) # image filename ( P=quote) # closing quote | # ---or alternatively--( P<uimage>[^"' >]+) # unquoted image filename ) [^>]* # non-src attributes > # end of the tag """, reIGNORECASE|reVERBOSE) image_files = [] for match in image_refinditer(text): image_filesappend(matchgroup("qimage") or matchgroup("uimage"))

Again we use the finditer() method to retrieve each match and the match object s group() function to retrieve the captured texts Each time a match is made we don t know which of the image groups ("qimage" or "uimage") has matched, but using the or operator provides a neat solution for this Since the case insensitivity applies only to img and src, we could drop the reIGNORECASE ag and use [Ii][Mm][Gg] and [Ss][Rr][Cc] instead Although this would make the regex less clear, it might make it faster since it would not require the text being matched to be set to upper- (or lower-) case but it is likely to make a difference only if the regex was being used on a very large amount of text

Using the low-level user interface API, an application can: control precisely what is drawn on the display,

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WCF clients can call any standards-based service regardless of the target hosting environment Web services built on the NET 11 Framework (ASMX) are fully compatible The standard de ned by WS-I Basic Pro le 11 ensures they are callable from WCF clients

result and this may not be a Boolean (although it can be converted to a Boolean); not always returns either True or False We can test for membership of sequence types, including strings, lists, and tuples, using the in and not in operators Membership testing uses a slow linear search on lists and tuples, and a potentially much faster hybrid algorithm for strings, but performance is rarely an issue except for very long strings, lists, and tuples In 3 we will learn about Python s associative array and set collection data types, both of which provide very fast membership testing It is also possible to nd out an object variable s type (ie, the type of object the object reference refers to) using type() but this function is normally used only for debugging and testing Python provides several control structures, including conditional branching with if elif else, conditional looping with while, looping over sequences with for in, and exception-handling with try except blocks Both while and for in loops can be prematurely terminated using a break statement, and both can switch control to the beginning using continue The usual arithmetic operators are supported, including +, -, *, and /, although Python is unusual in that / always produces a oating-point result even if both its operands are integers (The truncating division that many other languages use is also available in Python as //) Python also provides augmented assignment operators such as += and *=; these create new objects and rebind behind the scenes if their left-hand operand is immutable The arithmetic operators are overloaded by the str and list types as we noted earlier Console I/O can be achieved using input() and print(); and using le redirection in the console, we can use these same built-in functions to read and write les In addition to Python s rich built-in functionality, its extensive standard library is also available, with modules accessible once they have been imported using the import statement One commonly imported module is sys, which holds the sysargv list of command-line arguments And when Python doesn t have the function we need we can easily create one that does what we want using the def statement By making use of the functionality described in this chapter it is possible to write short but useful Python programs In the following chapter we will learn more about Python s data types, going into more depth for ints and strs and introducing some entirely new data types In 3 we will learn more about tuples and lists, and also about some of Python s other collection data types Then, in 4 we will cover Python s control structures in much more detail, and will learn how to create our own functions so that we can package up functionality to avoid code duplication and promote code reuse.

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