Data Type - 'int' for Integer Values

This section describes the 'int' data type, which has infinite number of objects covering all integer values.

What Is the "int" Data Type? "int" is the Integer data type in Python. It has infinite number of objects covering all integer values.

"int" data type has the following main Features.

1. "int" data objects can be created in several ways:

Here are some examples on how to create "int" objects:

>>> 255, -255, 0
(255, -255, 0)

>>> 0xff, -0xff, 0x0
(255, -255, 0)

>>> 0o377, -0o377, 0o0
(255, -255, 0)

>>> 0b11111111, -0b11111111, 0b0
(255, -255, 0)

>>> int(1.1), int('1')
(1, 1)

2. "int" data type is an immutable data type. Once an "int" data object is created to store an integer value, this value will never change.

Don't get confused about "int" immutability and "int" variable re-assignment capability. An "int" variable can be re-assigned with different "int" objects many times.

# new object is created for 1 and assigned to x
>>> x = 1
>>> id(x)
4547439248

# assign the same object to y
>>> y = x
>>> id(y)
4547439248

# new object is created for 2 and assigned to x
>>> x = 2
>>> id(x)
4547439280

# the first object for 1 is still there in memory
>>> y
1
>>> id(y)
4547439248

3. Because "int" data type is immutable, an object created for a given integer value is not allowed to change its value. This allow "int" objects to be cached in memory and reused later whenever they are needed again. Reusing objects will reduce execution time and memory consumption.

On my macOS computer, "int" objects for smaller integers are cached and reused, since they are used more frequently. For example, "int" object for integer 1 is cached and reused. No matter how you create it, you will get the same object.

>>> x = 1
>>> y = 1
>>> (id(x), id(y), id(1), id(int(1.1)), id(int('1')))
(4547439248, 4547439248, 4547439248, 4547439248, 4547439248)

However, "int" objects for large integers are not cached, since their likelihood of being reused is very low. Caching them is actually wasting memory.

>>> id(1234567801234567890), id(1234567801234567890)
(4459214720, 4459214720)

>>> id(1234567801234567890), id(1234567801234567890)
(4459213472, 4459213472)

4. "int" objects support the following arithmetic operations:

Syntax   Operation         Resulting Type
------   ---------         --------------
 x + y   Addition          int
 x - y   Subtraction       int
 x * y   Multiplication    int
 x / y   Division          float
x // y   Floored Quotient  int
 x % y   Remainder         int

Here are some examples of "int" arithmetic operations:

>>> 2 + 3
5

>>> 5 - 7
-2

>>> 2*5
10

>>> 11/3
3.6666666666666665

>>> 11//3
3

>>> 11%3
2

5. "int" objects support the following comparison operations.

Syntax   Operation
------   ---------
x <  y   Less than
x <= y   Less than or equal
x >  y   Greater than
x >= y   Greater than or equal
x == y   Equal
x != y   Not equal

Here are some examples of "int" comparison operations:

>>> 5 < 6
True

>>> 5 <= 6
True

>>> 5 > 6
False

>>> 5 >= 6
False

>>> 5 == 6
False

>>> 5 != 6
True

6. "int" objects support the following bitwise operations. They are performed by representing integers in the two’s complement format with length limitation.

Syntax   Operation
------   ---------
 x | y   Bitwise OR
 x ^ y   Bitwise XOR
 x & y   Bitwise AND
x << n   Left shift
x >> n   Right shift
   ~ x   Bitwise NOT

Here are some examples of "int" arithmetic operations:

# '01010' | '00100' = '01110'
>>> 10 | 4
14

# '01010' ^ '00100' = '01110'
>>> 10 ^ 4
14

# '01010' & '00100' = '00000'
>>> 10 & 4
0

# '01010' << 1 = '10100'
>>> 10 << 1
20

# '01010' >> 1 = '00101'
>>> 10 >> 1
5

# ~'01010' > '10101'
>>> ~10
-11

7. Some built-in functions are provided for "int" objects.

8. Some class/instance methods are provided for "int" objects.

Table of Contents

 About This Book

 Running Python Code Online

 Python on macOS Computers

 Python on Linux Computers

Built-in Data Types

 Introduction to Data Type

 Common Features of All Data Types

 Data Type - NoneType for Nothing

 Data Type - 'bool' for Boolean Values

Data Type - 'int' for Integer Values

 Data Type - 'float' for Real Numbers

 Data Type - 'bytes' for Byte Sequence

 Data Type - 'str' for Character String

 Data Type - 'tuple' for Immutable List

 Data Type - 'list' for Mutable List

 Data Type - 'dict' for Dictionary Table

 Variables, Operations and Expressions

 Statements - Execution Units

 Function Statement and Function Call

 Iterators, Generators and List Comprehensions

 Classes and Instances

 Modules and Module Files

 Packages and Package Directories

 "sys" and "os" Modules

 "pathlib" - Object-Oriented Filesystem Paths

 "pip" - Package Installer for Python

 SciPy.org - Python Libraries for Science

 pandas - Data Analysis and Manipulation

 Anaconda - Python Environment Manager

 Jupyter Notebook and JupyterLab

 References

 Full Version in PDF/EPUB