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CHAPTER 3 WORKING WITH STRINGS
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Sometimes string methods such as lower won t work quite the way you want them to for instance, if you happen to use a non-English alphabet. Let s say you want to convert the uppercase Norwegian word B LLEFR to its lowercase equivalent: >>> print 'B LLEFR '.lower() b llefr As you can see, this didn t really work because Python doesn t consider a real letter. In this case, you can use translate to do the translation: >>> table = maketrans(' ', ' ') >>> word = 'K PES M' >>> print word.lower() k pes m >>> print word.translate(table) K PES M >>> print word.translate(table).lower() k pes m Then again, simply using Unicode might solve your problems: >>> print u' rn ringsl re'.upper() RN RINGSL RE You might also want to check out the locale module for some internationalization functionality.
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In this chapter, you have seen two important ways of working with strings: String formatting: The modulo operator (%) can be used to splice values into a string that contains conversion flags, such as %s. You can use this to format values in many ways, including right or left justification, setting a specific field width and precision, adding a sign (plus or minus), or left-padding with zeros. String methods: Strings have a plethora of methods. Some of them are extremely useful (such as split and join), while others are used less often (such as istitle or capitalize).
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string.capwords(s[, sep]) string.maketrans(from, to)
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Splits s with split (using sep), capitalize items, and join with a single space Makes a translation table for translate
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CHAPTER 3 WORKING WITH STRINGS
What Now
Lists, strings, and dictionaries are three of the most important data types in Python. You ve seen lists and strings, so guess what s next In the next chapter, you see how dictionaries not only support indices, but other kinds of keys (such as strings or tuples) as well. Dictionaries also support a few methods, although not as many as strings.
Dictionaries: When Indices Won t Do
ou ve seen that lists are useful when you want to group values into a structure and refer to each value by number. In this chapter, you learn about a data structure in which you can refer to each value by name. This type of structure is called a mapping. The only built-in mapping type in Python is the dictionary. The values in a dictionary don t have any particular order but are stored under a key, which may be a number, a string, or even a tuple.
Dictionary Uses
The name dictionary should give you a clue about the purpose of this structure. An ordinary book is made for reading from start to finish. If you like, you can quickly open it to any given page. This is a bit like a Python list. On the other hand, dictionaries both real ones and their Python equivalent are constructed so that you can look up a specific word (key) easily, to find its definition (value). A dictionary is more appropriate than a list in many situations. Here are some examples of uses of Python dictionaries: Representing the state of a game board, with each key being a tuple of coordinates Storing file modification times, with file names as keys A digital telephone/address book Let s say you have a list of people: >>> names = ['Alice', 'Beth', 'Cecil', 'Dee-Dee', 'Earl'] What if you wanted to create a little database where you could store the telephone numbers of these people how would you do that One way would be to make another list. Let s say you re storing only their four-digit extensions. Then you would get something like this: >>> numbers = ['2341', '9102', '3158', '0142', '5551'] Once you ve created these lists, you can look up Cecil s telephone number as follows: >>> numbers[names.index('Cecil')] 3158
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