• By implementing the special methods (__len__, etc), it hook into built-in operations (len(), etc)
• By implementing special methods combination they build protocols (interfaces)
• By overloading the methods __add__, object participate in operations like +
• Object Customization Hooks: __getattr__

Special Methods

None of special methods is directly called. Python interpreter is the only frequent caller of most special methods.

\_\_repr\_\_: is called by repr, to get the string representation of the object for inspection. returned by \_\_repr\_\_ should be unambiguous and sometimes match the source code necessary to re-create the represented object.

\_\_str\_\_: called by the str() built-in and implicitly used by the print function. It should return a string suitable for display to end users. If \_\_repr\_\_ is user-friendly you don't need to code \_\_str\_\_

If you only implement one of them, choose, \_\_repr\_\_.

To determine whether a value x is truthy or falsy, Python applies bool(x), which returns either True or False.

By default, instances of user-defined classes are considered truthy, unless either \_\_bool\_\_ or \_\_len\_\_ is implemented.

bool(x) will call x.__bool__() and use the result. If \_\_bool\_\_ is not implemented, Python tries to invoke x.__len__(), and if that returns zero, bool returns False. Otherwise bool returns True.

Collection API

• Iterable to support for, unpacking, and ohter forms of iteration.
• Sized to support the len built-in function
• Container to support the in operator

Three important Collections:

• Sequence: formalizing the interface of built-ins like list and str;
• Mapping: implemented by dict, collections.defaultdict, etc
• Set: the interface of the set and frozenset built-in types

String/bytes representation: \_\_repr\_\_, \_\_str\_\_, \_\_format\_\_, \_\_bytes\_\_, \_\_fspath\_\_

Conversation to number: \_\_bool\_\_, \_\_complex\_\_, \_\_int\_\_, \_\_float\_\_, \_\_hash\_\_, \_\_index\_\_

Emulating collections: \_\_len\_\_, \_\_getitem\_\_, \_\_setitem\_\_, \_\_delitem\_\_, \_\_contains\_\_

Iteration: \_\_iter\_\_, \_\_aiter\_\_, \_\_next\_\_, \_\_anext\_\_, \_\_reversed\_\_

• List comprehensions and the basics of generator expressions
• Using tuples as records, versus using tuples as immutable lists
• Sequence unpacking and sequence patterns
• Reading from slices and writing to slices
• Specialized sequence types, like arrays and queues

Sequences:

• Container sequences: Can hold items of different types, including nested containers. Some examples: list, tuple, and collections.deque.
• Flat sequences: Hold items of one simple type: Some examples: str, bytes, and array.array.

A container sequence holds references to the objects it contains, while flat sequence stores the value of its contents in its own memory space, and not as distinct python objects.

特徴：

mutable vs immutable container vs flat

list: a mutable container

List comprehensions