Python Data Types

Data Types

Python has the following built-in data types:

• Numeric Types:
  • int: whole numbers, e.g. 1, 2, 3
  • float: decimal numbers, e.g. 3.14, -0.5
  • complex: complex numbers, e.g. 3+4j, 1-2j
• Sequence Types:
  • str: strings, e.g. "hello", 'hello'
  • list: ordered collections, e.g. [1, 2, 3], ["a", "b", "c"]
  • tuple: ordered, immutable collections, e.g. (1, 2, 3), ("a", "b", "c")
• Mapping Type:
  • dict: unordered collections of key-value pairs, e.g. {"name": "John", "age": 30}
• Set Types:
  • set: unordered collections of unique elements, e.g. {1, 2, 3}, {"a", "b", "c"}
  • frozenset: unordered, immutable collections of unique elements
• Boolean Type:
  • bool: true or false values
• Binary Types:
  • bytes: sequence of integers in the range 0 <= x < 256
  • bytearray: mutable sequence of integers in the range 0 <= x < 256
  • memoryview: used to access the memory of other binary objects

Control Structures

Python's control structures are used to control the flow of a program's execution.

• Conditional Statements:
  • if statement: used to execute a block of code if a condition is true
  • elif statement: used to check another condition if the initial condition is false
  • else statement: used to execute a block of code if all conditions are false
• Loops:
  • for loop: used to iterate over a sequence (e.g. list, tuple, string)
  • while loop: used to execute a block of code as long as a condition is true
• Jump Statements:
  • break statement: used to exit a loop prematurely
  • continue statement: used to skip the current iteration of a loop
  • pass statement: used as a placeholder when a statement is required syntactically
  • return statement: used to exit a function and return a value

Object Oriented Programming

Python supports object-oriented programming (OOP) concepts:

• Classes:
  • A blueprint for creating objects
  • Can contain attributes (data) and methods (functions)
• Objects:
  • Instances of classes
  • Have their own set of attributes and methods
• Inheritance:
  • A child class can inherit attributes and methods from a parent class
  • Allows for code reuse and a more hierarchical organization of code
• Polymorphism:
  • The ability of an object to take on multiple forms
  • Can be achieved through method overriding or method overloading
• Encapsulation:
  • The idea of bundling data and methods that operate on that data within a single unit (class)
  • Helps to hide implementation details and improve code organization

Numeric Types

• int: Represents whole numbers without a decimal point, examples include 1, 2, and 3.
• float: Represents numbers with decimal points, allowing for fractional values like 3.14 and -0.5.
• complex: Used for complex numbers, consisting of a real and an imaginary part, represented as 3+4j or 1-2j.

Sequence Types

• str: Represents strings, which are sequences of characters, seen in examples such as "hello" or 'hello'.
• list: An ordered collection that can hold items of different types, indicated by examples like [1, 2, 3] and ["a", "b", "c"].
• tuple: Similar to lists but immutable (cannot be changed), with examples like (1, 2, 3) and ("a", "b", "c").

Mapping Type

• dict: A collection of key-value pairs that are unordered, as illustrated by {"name": "John", "age": 30}, allowing for quick data retrieval based on keys.

Set Types

• set: Unordered collections that store unique elements, such as {1, 2, 3} and {"a", "b", "c"}, automatically removing duplicates.
• frozenset: An immutable version of sets, maintaining unique elements while preventing modification after creation.

Boolean Type

• bool: Represents truth values, primarily True or False, essential for conditional statements and boolean logic.

Binary Types

• bytes: A sequence of integers within the range of 0 to 255, typically used for handling binary data and file operations.

Explore the different built-in data types in Python, including numeric, sequence, and mapping types.