Abstractions and Patterns – Short Notes

 

1. Abstractions in Programming

• Definition: Abstraction is the process of hiding complex details and showing only the essential features.

• Purpose: Simplifies understanding, reduces complexity, and improves modularity.

• Examples:

  • Built-in types: int, float, str, list in Python.

  • Custom data types: Creating your own classes or structures.

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2. Finding Patterns in Programs

• Definition: Patterns are reusable solutions to common programming problems.

• Helps in writing efficient and predictable code.

• Example: Looping over a list, handling input validation, or sorting.

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3. Creating Your Own Data Types

• Purpose: To represent complex information in a structured way.

• Example:

  class Student:
      def __init__(self, name, marks):
          self.name = name
          self.marks = marks
  

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4. Ready-Made Patterns

• Definition: Predefined solutions or code structures used repeatedly.

• Examples:

  • Iteration patterns: for loops, while loops

  • Data structure patterns: stacks, queues

  • Design patterns: Singleton, Factory

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Key Idea:

Abstractions and patterns reduce complexity, improve code reusability, and make programs easier to understand and maintain.