Python Basics: Multi-Line Comments and Variables

Study Notes

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.

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.

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.

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.

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.

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.

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