Python Object

Python object is a logical representation used to represent the physical data stored in memory.

Objects are never explicitly destroyed; however, when they become unreachable they may be garbage-collected. An implementation is allowed to postpone garbage collection or omit it altogether -- it is a matter of implementation quality how garbage collection is implemented, as long as no objects are collected that are still reachable. (Implementation note: the current implementation uses a reference-counting scheme which collects most objects as soon as they become unreachable, but never collects garbage containing circular references.)

Note that the use of the implementation's tracing or debugging facilities may keep objects alive that would normally be collectable. Also note that catching an exception with a `try...except' statement may keep objects alive.

Some objects contain references to ``external'' resources such as open files or windows. It is understood that these resources are freed when the object is garbage-collected, but since garbage collection is not guaranteed to happen, such objects also provide an explicit way to release the external resource, usually a close() method. Programs are strongly recommended to explicitly close such objects. The `try...finally' statement provides a convenient way to do this.

Python Object Property

The three basic properties of Python object are identity, type, and value.

Identity Property

Identity is an unique integer value used to represent a Python object. Since the identity of an object also represents the logical physical location of the corresponding object value, the identity of a Python object remains unchange once the identity has been created. The identity property of a Python object can be returned by the id() function.

Type Property

Type is a predefined type name of the stored data value. Type is used to specify the allowed data type that can be stored in the object and operations that are supported by object type. The type of a Python object remains unchange once the data type are specified. The type property of a Python object can be returned by the type() function.

Types affect almost all aspects of object behavior. Even the importance of object identity is affected in some sense: for immutable types, operations that compute new values may actually return a reference to any existing object with the same type and value, while for mutable objects this is not allowed. E.g., after "a = 1; b = 1", a and b may or may not refer to the same object with the value one, depending on the implementation, but after "c = []; d = []", c and d are guaranteed to refer to two different, unique, newly created empty lists. (Note that "c = d = []" assigns the same object to both c and d.) 

Value Property

Value is the logical value of an object. Depending on the Python type property, the Python value property can be divived into two catalogues, mutable and immutable according to the immutability of data object.

Python Object Data Types

Python object data types can be divived into two catalogues, mutable and immutable object data types according to the immutability of data type.

Immutable Data Types

Value of immutable data types can not be changed after creation. Typical immutable types are numeric data types, strings, bytes, frozen sets, and tuples.

Numeric Data Types

Booleans

Integers

Floats

Complex Numbers

Fractions

Decimals

Strings

Unicode String

Bytes

Frozen Sets

Tuples

Mutable Data Types

Value of mutable data types can be changed after creation. Typical mutable types are lists, byte arrays, sets, and dictionaries. These are mutable sequence.

Lists

Byte Arrays

Sets

Dictionaries

Source and Reference

• https://www.python.org
• https://docs.python.org/3.8/reference/datamodel.html
• https://docs.python.org/2.0/ref/objects.html
• https://www.geeksforgeeks.org/data-abstraction-and-data-independence/