Learning Python - Mark Lutz [124]
Mutable Types Can Be Changed In-Place
The immutable classification is an important constraint to be aware of, yet it tends to trip up new users. If an object type is immutable, you cannot change its value in-place; Python raises an error if you try. Instead, you must run code to make a new object containing the new value. The major core types in Python break down as follows:
Immutables (numbers, strings, tuples, frozensets)
None of the object types in the immutable category support in-place changes, though we can always run expressions to make new objects and assign their results to variables as needed.
Mutables (lists, dictionaries, sets, bytearray)
Conversely, the mutable types can always be changed in-place with operations that do not create new objects. Although such objects can be copied, in-place changes support direct modification.
Generally, immutable types give some degree of integrity by guaranteeing that an object won’t be changed by another part of a program. For a refresher on why this matters, see the discussion of shared object references in Chapter 6. To see how lists, dictionaries, and tuples participate in type categories, we need to move ahead to the next chapter.
Chapter Summary
In this chapter, we took an in-depth tour of the string object type. We learned about coding string literals, and we explored string operations, including sequence expressions, string method calls, and string formatting with both expressions and method calls. Along the way, we studied a variety of concepts in depth, such as slicing, method call syntax, and triple-quoted block strings. We also defined some core ideas common to a variety of types: sequences, for example, share an entire set of operations.
In the next chapter, we’ll continue our types tour with a look at the most general object collections in Python—lists and dictionaries. As you’ll find, much of what you’ve learned here will apply to those types as well. And as mentioned earlier, in the final part of this book we’ll return to Python’s string model to flesh out the details of Unicode text and binary data, which are of interest to some, but not all, Python programmers. Before moving on, though, here’s another chapter quiz to review the material covered here.
Test Your Knowledge: Quiz
Can the string find method be used to search a list?
Can a string slice expression be used on a list?
How would you convert a character to its ASCII integer code? How would you convert the other way, from an integer to a character?
How might you go about changing a string in Python?
Given a string S with the value "s,pa,m", name two ways to extract the two characters in the middle.
How many characters are there in the string "a\nb\x1f\000d"?
Why might you use the string module instead of string method calls?
Test Your Knowledge: Answers
No, because methods are always type-specific; that is, they only work on a single data type. Expressions like X+Y and built-in functions like len(X) are generic, though, and may work on a variety of types. In this case, for instance, the in membership expression has a similar effect as the string find, but it can be used to search both strings and lists. In Python 3.0, there is some attempt to group methods by categories (for example, the mutable sequence types list and bytearray have similar method sets), but methods are still more type-specific than other operation sets.
Yes. Unlike methods, expressions are generic and apply to many types. In this case, the slice expression is really a sequence operation—it works on any type of sequence object, including strings, lists, and tuples. The only difference is that when you slice a list, you get back a new list.
The built-in ord(S) function converts from a one-character string to an integer character code; chr(I) converts from the integer code back to