From 6e7a5f9a2b16394843e1cc800d91a0d68a479bc0 Mon Sep 17 00:00:00 2001 From: medusa Date: Tue, 20 Aug 2024 04:34:18 +0000 Subject: [PATCH] Add tech_docs/python/learning_python.md --- tech_docs/python/learning_python.md | 154 ++++++++++++++++++++++++++++ 1 file changed, 154 insertions(+) create mode 100644 tech_docs/python/learning_python.md diff --git a/tech_docs/python/learning_python.md b/tech_docs/python/learning_python.md new file mode 100644 index 0000000..3b485db --- /dev/null +++ b/tech_docs/python/learning_python.md @@ -0,0 +1,154 @@ +### Complete Resource for Fine-Tuning Programming and Problem-Solving Skills + +--- + +#### **Study Plan Overview** + +**Objective**: Master programming and problem-solving skills through a structured, deep learning approach using Python and gamified learning tools. + +**Duration**: 16 weeks + +**Daily Commitment**: 4 hours per day + +--- + +### **Weeks 1-4: Foundations and Efficiency** + +#### **Primary Resource: The Farmer Was Replaced** +- **Focus Areas**: + - **Basic Control Structures**: Learn `if-else` statements, loops, and functions. + - **Automation**: Write scripts to automate repetitive tasks. + - **Code Optimization**: Refine code to minimize complexity and improve efficiency. + - **Debugging**: Practice identifying and fixing errors in your code. + +- **Study Plan**: + - **Days 1-5**: Understand basic commands and automate simple tasks. Experiment with different control structures. + - **Days 6-10**: Optimize your code for efficiency. Focus on writing concise code that accomplishes tasks with fewer lines. + - **Days 11-15**: Introduce error handling and debugging. Make deliberate mistakes and practice fixing them. + - **Days 16-20**: Reflect on your progress, write down effective strategies, and refine your approach. + +#### **Secondary Resource: CheckiO** +- **Focus Areas**: + - **Problem Decomposition**: Break down problems into smaller parts. + - **Data Structures**: Use lists, dictionaries, and sets. + - **Logic and Control Flow**: Implement loops, conditionals, and functions. + +- **Study Plan**: + - **Days 1-5**: Solve simple challenges, focusing on problem decomposition and basic control structures. + - **Days 6-10**: Practice using data structures to simplify problem-solving. + - **Days 11-15**: Work on challenges that require complex control flow. + - **Days 16-20**: Review and compare your solutions with others to learn alternative approaches. + +--- + +### **Weeks 5-8: Advanced Control Structures and Algorithms** + +#### **Primary Resource: CheckiO** +- **Focus Areas**: + - **Recursion**: Master functions that call themselves to solve smaller problems. + - **Algorithm Design**: Optimize algorithms for efficiency. + - **Peer Learning**: Learn from community solutions to improve your coding style. + +- **Study Plan**: + - **Days 21-25**: Start with simple recursion problems, understanding base cases and recursive steps. + - **Days 26-30**: Tackle more complex recursion challenges, such as backtracking. + - **Days 31-35**: Focus on algorithm design, optimizing your solutions for better performance. + - **Days 36-40**: Review and refine your solutions based on peer feedback. + +#### **Secondary Resource: Exercism** +- **Focus Areas**: + - **Debugging**: Identify and fix errors efficiently. + - **Code Refinement**: Improve readability, efficiency, and maintainability. + - **Mentorship Feedback**: Use feedback to refine solutions. + +- **Study Plan**: + - **Days 21-25**: Work on exercises focusing on recursion and get mentor feedback. + - **Days 26-30**: Practice debugging exercises, introducing and fixing errors deliberately. + - **Days 31-35**: Tackle more complex exercises and refine your code. + - **Days 36-40**: Reflect on mentor feedback and apply it to improve your coding style. + +--- + +### **Weeks 9-12: Algorithmic Thinking and Competitive Coding** + +#### **Primary Resource: Project Euler** +- **Focus Areas**: + - **Graph Algorithms**: Learn to implement graph algorithms like shortest path and depth-first search. + - **Dynamic Programming**: Solve problems with overlapping subproblems. + - **Efficiency and Complexity**: Optimize your solutions for time and space complexity. + +- **Study Plan**: + - **Days 41-45**: Solve introductory problems involving graph algorithms. + - **Days 46-50**: Implement more complex graph algorithms. + - **Days 51-55**: Tackle dynamic programming problems, focusing on optimization. + - **Days 56-60**: Review and optimize your solutions for performance. + +#### **Secondary Resource: CodinGame** +- **Focus Areas**: + - **Real-Time Problem Solving**: Solve problems quickly and accurately under time constraints. + - **Competitive Programming**: Develop strategies for solving problems in competitive environments. + - **Optimization Techniques**: Implement techniques like greedy algorithms and heuristics. + +- **Study Plan**: + - **Days 41-45**: Participate in simpler CodinGame challenges, focusing on speed and accuracy. + - **Days 46-50**: Work on more complex challenges requiring optimization techniques. + - **Days 51-55**: Engage in multiplayer challenges and learn from other players' strategies. + - **Days 56-60**: Reflect on your performance and identify areas for improvement. + +--- + +### **Weeks 13-16: Mastering OOP and Best Practices** + +#### **Primary Resource: Exercism** +- **Focus Areas**: + - **Object-Oriented Programming (OOP)**: Master classes, inheritance, polymorphism, and encapsulation. + - **Test-Driven Development (TDD)**: Write tests before implementing code. + - **Code Review and Refinement**: Refine code for better design and maintainability. + +- **Study Plan**: + - **Days 61-65**: Work on OOP exercises, focusing on encapsulation, inheritance, and polymorphism. + - **Days 66-70**: Practice TDD by writing tests before coding. + - **Days 71-75**: Refine your OOP solutions using best practices like SOLID principles. + - **Days 76-80**: Review and refactor previous solutions, applying OOP and TDD principles. + +#### **Secondary Resource: Project Euler** +- **Focus Areas**: + - **Real-World Application**: Apply OOP and TDD principles to solve complex problems. + - **Code Review**: Continuously review and improve previous solutions. + +- **Study Plan**: + - **Days 61-65**: Solve a problem using an OOP approach, focusing on classes and inheritance. + - **Days 66-70**: Refactor your solution, improving maintainability and readability. + - **Days 71-75**: Reflect on your progress and set goals for further improvement. + - **Days 76-80**: Apply TDD principles to a new problem, ensuring your code is well-tested and optimized. + +--- + +### **Key Concepts and Tips** + +#### **Object-Oriented Programming (OOP)** +- **Classes and Objects**: Understand the relationship between classes (blueprints) and objects (instances). +- **Encapsulation**: Bundle data and methods, restricting direct access to some components. +- **Inheritance**: Reuse code by inheriting attributes and methods from parent classes. +- **Polymorphism**: Allow objects to be treated as instances of their parent class. +- **Abstraction**: Focus on exposing essential features while hiding the complex implementation details. +- **Composition**: Build complex classes by combining simpler ones. +- **SOLID Principles**: Follow best practices in OOP to create maintainable and scalable code. + +#### **Recursion** +- **Base Case**: Always define a clear base case to prevent infinite recursion. +- **Smaller Problems**: Break down the problem into smaller instances of the same problem. +- **Execution Flow**: Trace the function calls to understand how the recursion unfolds. +- **Avoid Redundancy**: Use memoization to avoid recalculating results for the same input. +- **Tail Recursion**: Refactor to tail recursion if supported, to optimize space complexity. + +--- + +### **Weekly Reflection** +- Spend 30-60 minutes at the end of each week reviewing your progress. +- Write down key lessons, challenges faced, and areas needing further review. +- Adjust your study plan for the next week based on your reflection. + +--- + +This plan provides a structured, detailed roadmap for mastering programming and problem-solving skills. By following this approach, you'll build a strong foundation, progressively deepen your expertise, and achieve a high level of proficiency in Python and problem-solving. \ No newline at end of file