Common Features of All Data Types

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∟Common Features of All Data Types

This section describes some common features of all data types: unique identifiers, id(object) and type(object) functions, data type categories, casting to Boolean values, etc.

What Are Common Features of All Data Types? All data types share the following common features:

1. Every object of every data type has a unique identifier, which can be viewed as the object’s address in memory. You can use the id(object) function to return the identifier of the given object:

>>> id(None)
4547296864

>>> id(1)
4547439248

>>> id(2)
4547439280

# 1+1 returns the same object as 2
>>> id(1+1)
4547439280

>>> id(True)
4547219352

# 1==1 returns the same object as True
>>> id(1==1)
4547219352

# "id" is the variable name referring to the id() function object
>>> id(id)
4548982640

You can use "is" and "is not" operator to perform identity comparisons between 2 data objects of any data types.

# "int" literal returns the same object for the same value.
>>> 1 is 1
<stdin>:1: SyntaxWarning: "is" with a literal. Did you mean "=="?
True

# "str" literal returns the same object for the same value.
>>> 'hello' is 'hello'
<stdin>:1: SyntaxWarning: "is" with a literal. Did you mean "=="?
True

# [] always creates a new object
>>> [] is []
False

2. If you are not sure what is the type of a data object, you can use the type(object) function to find out:

>>> type(314)
<class 'int'>

>>> type(3.14)
<class 'float'>

>>> type(True)
<class 'bool'>

>>> type(None)
<class 'NoneType'>

>>> type(type(None))
<class 'type'>

# "type" is the variable name referring to the type() function object
>>> type(type)
<class 'type'>

>>> type(type(type))
<class 'type'>

3. Every object of every data type stores a data value. Based on the nature of their data values, data types can be categorized as:

Primitive Data Types - A primitive data type can be used to store a single piece of information. For example, "bool", "int" and "float" are primitive data types.

Structured Data Types - A structured data type can be used to store multiple pieces of information. For example, "str" and "list" are structured data types.

Mutable Data Types - The value stored in a mutable data type is changeable. For example, "list" and "dict" are mutable data types.

Immutable Data Types - The value stored in an immutable data type is unchangeable. For example, "int" and "tuple" are immutable data types.

Container Data Types - The value stored in a container data type is a reference to another object. For example, "list" and "tuple" are container data types.

4. Every object of every data type can be implicitly casted to a Boolean value in a Boolean context. Here is the casting logic for an object represented by "obj":

Casted to the returned value of obj.__bool__() function, if it is defined.
Else, casted to obj.__len__() > 0, if it is defined.
Else, casted to False, if obj == None.
Else, casted to obj, if type(obj).__name__ == 'bool'.
Else, casted to obj == 0, if type(obj).__name__ == 'int'.
Else, casted to obj == 0.0, if type(obj).__name__ == 'float'.
Else, casted to obj == 0j, if type(obj).__name__ == 'complex'.
Else, casted to True.

5. Every object of every data type occupies certain amount of storage in memory. You can use the sys.getsizeof(object) to find out the storage size of any given data object.

>>> import sys
>>> sys.getsizeof(10)
28
>>> sys.getsizeof(1)
28
>>> sys.getsizeof(0)
24
>>> sys.getsizeof(-1)
28

>>> sys.getsizeof([1])
64
>>> sys.getsizeof([0])
64
>>> sys.getsizeof([0,1])
72