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)

广告：个人专属 VPN，独立 IP，无限流量，多机房切换，还可以屏蔽广告和恶意软件，每月最低仅 5 美元

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.