03.8 Introduction to Python.pdf

Understanding Python Syntax, Variables, Control Structures, Functions, OOP, Modules, and Exception Handling Prepared by: JOEMARIE COMEROS AMPARO Brief History of Python Creation: Python was developed by Guido v...

Understanding Python Syntax, Variables, Control Structures, Functions, OOP, Modules, and Exception Handling Prepared by: JOEMARIE COMEROS AMPARO Brief History of Python Creation: Python was developed by Guido van Rossum and first released in 1991. Philosophy: Python was designed with the philosophy of simplicity and readability, often summarized in the Zen of Python (PEP 20). Evolution: Python has grown to be one of the most popular programming languages, with continuous updates and a strong community. Why Python is Popular Readability: Python’s syntax emphasizes readability, reducing the cost of program maintenance. Versatility: Python is versatile and can be used in web development, data science, AI, automation, and more. Community and Support: A large community offers extensive libraries, frameworks, and documentation, making it easier to learn and use. Python Key Features Interpreted Language: Python code is executed line by line, which makes debugging easier. Dynamically Typed: Variable types are determined at runtime, providing flexibility in coding. High-Level Language: Python abstracts complex details of the computer’s operations, allowing you to focus on programming logic. Python Syntax Indentation Structure: Python uses indentation to define the structure of the code. Blocks of code, like those within loops or functions, must be indented consistently. Error Prevention: Incorrect indentation leads to syntax errors, ensuring that code structure is explicit and clear. Python Syntax Case Sensitivity Variables and Functions: Python is case-sensitive, meaning that `Variable` and `variable` are considered different identifiers. Best Practices: It’s essential to maintain consistent naming conventions to avoid errors related to case sensitivity. Python Syntax Use of Colons Syntax Definition: Colons are used in Python to define the start of an indented block, such as after `if`, `for`, `while`, or function definitions. Code Readability: This consistent use of colons makes Python code more readable and structured. Python Syntax Comments Single-Line Comments: Use the # symbol to add comments for documentation and explanation of code. Multi-Line Comments: While Python doesn’t have a specific syntax for multi-line comments, you can use triple quotes `'‘’` or `""“` to comment out blocks of text, though this is typically used for documentation strings (docstrings). Variables in Python Variable Naming Rules Identifiers: Variable names must start with a letter or underscore and can contain letters, numbers, and underscores. Keywords: Avoid using Python reserved keywords (e.g., `class`, `try`, `return`) as variable names. Conventions: Follow naming conventions like `snake_case` for variables and functions to enhance code readability. Variables in Python Dynamic Typing Type Flexibility: Python allows variables to change types, making it easier to handle different data types without explicit declarations. Implications: This flexibility can make code more adaptable but requires careful management to avoid type-related errors. Variables in Python Examples of Variable Use Variable Assignment: Assigning values to variables is straightforward, with Python inferring the type. Variables in Python Examples of Variable Use Multiple Assignments: Python supports multiple assignments in a single line, allowing concise and efficient code. Variables in Python Examples of Variable Use Type Casting: Python provides built-in functions like int(), float(), and str() to convert data types, which is crucial for handling user input and performing calculations. Control Structures: Conditional Statements If Statements Basic If: Execute a block of code if a specified condition is true. The code inside the if block runs only if x is greater than 0. Control Structures: Conditional Statements If Statements Else: Provide an alternative block of code if the if condition is false. The else block ensures that one of the two code blocks will execute. Control Structures: Conditional Statements If Statements Elif: Check additional conditions if the previous if condition is false. The elif allows for multiple conditions to be checked sequentially. Control Structures: Conditional Statements If Statements Nested If: You can nest if statements within each other to handle complex decision-making processes. The inner if only runs if the outer if condition is true, allowing more granular control. Control Structures: Conditional Statements Loops Statements For Loop: The for loop iterates over a sequence (like a list or a range), making it easy to repeat actions. Commonly used for iterating over collections, running code a specific number of times, or processing items in a sequence. Control Structures: Conditional Statements Loops Statements While Loop: The while loop continues running as long as the condition remains true, offering flexibility in repetitive tasks. Ideal for scenarios where the number of iterations isn’t known in advance, such as waiting for user input or monitoring conditions. Control Structures: Conditional Statements Loops Statements Break Statement: Immediately exits the loop, skipping any remaining iterations. The loop stops when i equals 5, and only the numbers 1, 2, 3, 4 are printed. Functions in Python Types of Functions Built-in Functions: Python comes with a rich set of built-in functions that perform common tasks, like print(), len(), and type(). These functions save time and effort, as they are optimized for performance and reliability. User-Defined Functions: You can create custom functions to perform specific tasks that aren’t covered by built-in functions. User-defined functions make your code more modular and easier to understand, especially when used to break down complex tasks. Functions in Python Examples Defining and Calling Functions: Syntax: Example: The function greet() is defined using the def keyword. When called, it executes the print statement inside it. Functions in Python Examples Parameters and Arguments: Syntax: Example: The function greet(name) takes a single parameter name. When called with an argument, it personalizes the greeting. Functions in Python Examples Return Statement: The return statement is used to send back a result from a function to the caller. The function add(a, b) returns the sum of a and b, which is then printed. The return statement is crucial for functions that perform calculations or need to pass data back to the main program. Functions in Python Examples Multiple Return Values: Syntax: Example: Python functions can return multiple values, which can be unpacked and used separately. This is useful in scenarios where you need to return related data, such as an object's properties. Functions in Python Examples Lambda Functions: Syntax: Example: Lambda functions are small, anonymous functions defined with the lambda keyword. They can have any number of arguments but only one expression. This example adds 10 to the argument a and returns the result. Functions in Python: Practical Example Functions in Python Examples Lambda Functions: Syntax: Example: Lambda functions are small, anonymous functions defined with the lambda keyword. They can have any number of arguments but only one expression. This example adds 10 to the argument a and returns the result. Object-Oriented Programming (OOP) in Python OOP Concepts Object-Oriented Programming (OOP) is a paradigm that uses "objects" to represent real-world entities. These objects encapsulate data and behavior, making code more modular, reusable, and easier to maintain. Benefits include: Object-Oriented Programming (OOP) in Python Classes and Objects A class is a blueprint for creating objects. It defines the attributes (variables) and methods (functions) that the objects created from the class will have. Syntax: Object-Oriented Programming (OOP) in Python Inheritance Inheritance allows a class to inherit attributes and methods from another class, known as the parent or superclass. Syntax: Object-Oriented Programming (OOP) in Python Polymorphism Inheritance allows a class to inherit attributes and methods from another class, known as the parent or superclass. Syntax: Modules and Packages A module is a file containing Python definitions and statements. It allows you to organize your code into separate files, making it more modular and easier to maintain. Benefits: Creating a Module A module is simply a.py file containing Python code. Any Python file can be treated as a module. Suppose you create a file named mymodule.py: This file defines a function greet() that can be reused in other programs. Importing a Module The mymodule is imported, and the greet() function is called. This demonstrates how you can use functions from another file in your program. Only the greet() function is imported, allowing you to call it directly without using the module name. Packages A package is a collection of modules organized in directories that provide a way to structure Python’s module namespace using “dotted module names”. A package is simply a directory that contains a special __init__.py file and multiple modules. The mypackage directory is a package that contains two modules: module1.py and module2.py. The __init__.py file can be empty or contain initialization code for the package. Importing a Package This imports module1 from the mypackage and allows you to use its functions. Using Standard Library Modules Python’s standard library includes many modules that provide a wide range of functionalities, such as file I/O, system calls, data compression, and more. The os module from Python’s standard library provides a way to interact with the operating system. Exception Handling An exception is an error that occurs during the execution of a program. Python provides a way to handle these errors using exception handling mechanisms, ensuring that the program can recover or fail gracefully. Common Exceptions: Exception handling is crucial for writing robust programs that can deal with unexpected situations, such as invalid user input or resource limitations. Using Try-Except Block Syntax: The try block contains code that may raise exceptions. The except blocks catch and handle specific exceptions, ensuring the program doesn’t crash.