Python Basics: Multi-Line Comments and Variables

Multi-Line Comments in Python

• Multi-line comments can be created with triple quotes (''' or """).
• Typically used for documentation strings (docstrings) rather than comments.

Variables in Python

• Variable Naming Rules

  • Identifiers must start with a letter or underscore; can include letters, numbers, and underscores.
  • Avoid using reserved keywords like class, try, and return for variable names.
  • Follow conventions like snake_case for improved readability.

• Dynamic Typing

  • Variables can change types without explicit declarations, enhancing flexibility.
  • Requires careful management to avoid type-related errors.

• Variable Assignment

  • Python infers variable types during assignment.

• Multiple Assignments

  • Supports assigning values to multiple variables in a single line for concise code.

• Type Casting

  • Built-in functions like int(), float(), and str() allow conversion between data types, essential for user input and calculations.

Control Structures: Conditional Statements

• If Statements
  • Basic if statement executes a block of code if the condition (e.g., x > 0) is true.
  • Else provides an alternative block if the if condition is false.
  • Elif checks additional conditions if the previous if condition is false, facilitating multiple condition checks.
  • Nested if statements add complexity by allowing if statements within other if statements.

Control Structures: Loops

• For Loop

  • Iterates over a sequence (like a list or range) for repetitive tasks, facilitating operations on collections.

• While Loop

  • Continues execution as long as the condition is true, suited for situations where the iteration count is unknown (e.g., user input).

• Break Statement

  • Exits the loop immediately, skipping remaining iterations.

Functions in Python

• Types of Functions

  • Built-in functions (e.g., print(), len(), type()) simplify common tasks, providing performance and reliability.
  • User-defined functions allow customization and modularity for specific tasks.

• Defining and Calling Functions

  • Functions are defined with the def keyword and execute their bodies when called.

• Parameters and Arguments

  • Functions can take parameters to personalize actions, enhancing functionality.

• Return Statement

  • Returns results from a function, crucial for calculations and data passage back to the main program.

• Multiple Return Values

  • Functions can return multiple values, which can be unpacked and utilized independently.

• Lambda Functions

  • Small, anonymous functions defined with the lambda keyword, capable of accepting multiple arguments but executing a single expression.

Object-Oriented Programming (OOP) in Python

• OOP uses objects to represent real-world entities, encapsulating data and behavior for modular, reusable code.

• Classes and Objects

  • A class acts as a blueprint for objects, defining their attributes and methods.

• Inheritance

  • Allows classes to inherit from parent classes, acquiring their attributes and methods.

• Polymorphism

  • Enables classes to utilize methods from parent classes in their own unique contexts.

Modules and Packages

• A module is a file containing Python definitions and statements, aiding in code organization.
• Any .py file can function as a module, enhancing maintainability and reusability.
• Example: A file named mymodule.py could define a function greet(), which could be imported and reused in other programs.