python.md

In general, leading and trailing double underscores is the naming pattern
Python uses for implementation details. The names without the underscores in
this list are the callable methods on string objects.
This is related to the idea of polymorphism mentioned earlier, and it stems
from Python’s lack of type declarations. As you’ll learn, in Python, we code to
object interfaces (operations supported), not to types. That is, we care what
an object does, not what it is. Not caring about specific types means that code
is automatically applicable to many of them—any object with a compatible
interface will work, regardless of its specific type. Although type checking is
supported—and even required in some rare cases—you’ll see that it’s not usually
the “Pythonic” way of thinking. In fact, you’ll find that polymorphism is
probably the key idea behind using Python well.
More formally, there are three major type (and operation) categories in Python
that have this generic nature:

Numbers (integer, floating-point, decimal, fraction, others)
Support addition, multiplication, etc.
Sequences (strings, lists, tuples)
Support indexing, slicing, concatenation, etc.
Mappings (dictionaries)
Support indexing by key, etc.

[...]

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.