python-in-60-days

A project of Python studying from a Java developer perspective

📅 Evolution Summary

Day	Date	Learning Summary
01	22/04/2026	Variables, F-Strings, Lists, and the in operator.
02	24/04/2026	Dynamic Data Structures (List, Dict, Set, Tuple), Unpacking, and Pythonic Mapping.
03	04/05/2026	List and Dict Comprehensions (Pythonic way of doing streams/filters) and Ternary Operators.

🚀 Roadmap: 60 Days of Python (Java Developer Edition)

Phase 1: Java -> Python Transition (Days 2-10)

Focus: Syntax, Dynamic vs Static Typing, and Environment Management.

• Day 2: Dynamic Data Structures: Lists, Dicts, Sets, and Tuplas (and when to use each).
• Day 3: List Comprehensions and Dict Comprehensions (the "Pythonic way" of doing streams/filters).
• Day 4: Functions: *Args, **Kwargs, and Type Hinting (essential for Java developers).
• Day 5: Virtual Environments: Venv, Poetry, and dependency management.
• Day 6: Object-Oriented Programming (OOP): Classes, Mixins, and "Self" vs "This".
• Day 7: Error Handling: Try/Except/Finally vs Java's Exception model.
• Day 8: Modules and Packages: How Python organizes the classpath.
• Day 9: File Handling and Context Managers (the with statement).
• Day 10: Lab 1: Create a CLI script that reads a JSON and generates a formatted report.

Phase 2: Intermediate Python & Tooling (Days 11-25)

Focus: What happens "under the hood".

• Day 11: Decorators: Understanding annotations (equivalent to Spring's @Annotations).
• Day 12: Iterators and Generators: Memory efficiency in large data volumes.
• Day 13: Dunder Methods (Magic Methods): __init__, __str__, __repr__, __call__.
• Day 14: Multithreading vs Multiprocessing: The impact of GIL (Global Interpreter Lock).
• Day 15: Asynchronous Programming (AsyncIO): The Event Loop model.
• Day 16-20: Unit Testing: PyTest (fixtures, mocks, and parametrization).
• Day 21-25: Short Project: Create an asynchronous logging system that writes to multiple destinations.

Phase 3: Microservices Ecosystem (Days 26-40)

Focus: Replacing Spring Boot/Jakarta EE.

• Day 26: FastAPI: The "new standard" for fast and typed APIs.
• Day 27: Pydantic: Data validation and Data Transfer Objects (DTOs).
• Day 28: SQLAlchemy or SQLModel: The "Hibernate" of the Python world.
• Day 29: Migrations with Alembic.
• Day 30: Dependency Injection in Python (fastapi-users, dependency-injector).
• Day 31-35: Dockerizing Python applications (image and layer optimization).
• Day 36-40: Lab 2: Create the "skeleton" of the microservice you plan to migrate.

Phase 4: AI, Agents, and Automation (Days 41-55)

Focus: TigerAI and Integrations.

• Day 41: Integration with LLM APIs (OpenAI, Gemini SDK).
• Day 42: LangChain or CrewAI: Agent orchestration.
• Day 43: MCP (Model Context Protocol): Creating MCP servers in Python.
• Day 44: Vector Databases: ChromaDB or Pinecone with Python.
• Day 45-55: Intensive development of your TigerAI project sub-agents.

Phase 5: Refinement & Final Migration (Days 56-60)

• Day 56: Performance Tuning: Python code profiling.
• Day 57: Security: Bandit and Safety for code auditing.
• Day 58: CI/CD for Python: GitHub Actions and Linting (Ruff/Black).
• Day 59: Finalization of the microservice migration.
• Day 60: Final Review and Retrospective.