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  1. Python
  2. Problem Solving: Lists, Dictionaries, and Function-Based Design
Complexity : Program Design
Problem Solving: Lists, Dictionaries, and Function-Based Design

Program Structure

Python programs are typically organized into modules (files) and can be further structured using functions, classes, and control flow statements. Here's a breakdown of the key components:

Modules

  • Files containing Python code.

  • Reusable units of code.

  • Imported using the import statement.

  • Example:

Python

# my_module.py

def greet(name):

  print(f"Hello, {name}!")

 
# main.py

import my_module

 
my_module.greet("Alice")

Functions

  • Reusable blocks of code.

  • Defined using the def keyword.

  • Can take parameters and return values.

  • Example:

Python

def calculate_area(length, width):

  return length * width

Classes

  • Define custom data types and their behavior.

  • Encapsulate data and methods.

  • Example:

Python

class Person:

  def __init__(self, name, age):

    self.name = name

    self.age = age

 
  def greet(self):

    print(f"Hello, my name is {self.name}.")   

Control Flow Statements

  • Conditional statements: if, else, elif.

  • Loops: for, while.

  • Example:

Python

if age >= 18:

  print("You are an adult.")

else:

  print("You are a minor.")

 
for i in range(5):

  print(i)

Best Practices:

  • Modularity: Break down your code into smaller, reusable functions and classes.

  • Readability: Use meaningful names for variables, functions, and classes.

  • Indentation: Use consistent indentation to improve code readability.

  • Comments: Add comments to explain complex logic or non-obvious code.

  • Docstrings: Use docstrings to document functions and classes.

  • Error handling: Use try-except blocks to handle potential exceptions.

  • Testing: Write unit tests to ensure code correctness.

By following these guidelines, you can create well-structured and maintainable Python programs.

 

Complexity Program Design
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