What will you learn in Clean Architecture in Python Course
- Grasp the principles of Clean Architecture and hexagonal design in Python
- Separate concerns using entities, use cases, interfaces, and frameworks layers
- Write maintainable, testable code with dependency inversion and boundary definitions
- Implement repositories, controllers, and presenters for robust application structure
- Apply SOLID principles and design patterns to real-world Python applications
Program Overview
Module 1: Introduction to Clean Architecture
⏳ 1 week
Topics: History and benefits, layer responsibilities, SOLID recap
Hands-on: Sketch out the high-level architecture for a sample domain
Module 2: Defining Entities & Use Cases
⏳ 1 week
Topics: Entity models, business rules, use case interactors
Hands-on: Build Python classes for core domain entities and use-case methods
Module 3: Interfaces & Gateways
⏳ 1 week
Topics: Defining ports, repository and service adapters, interface segregation
Hands-on: Create abstract repository interfaces and in-memory adapters
Module 4: Frameworks & Delivery Mechanisms
⏳ 1 week
Topics: Web frameworks (FastAPI/Django), CLI, and background jobs integration
Hands-on: Wire up a FastAPI controller implementing the use-case boundary
Module 5: Dependency Injection & Inversion
⏳ 1 week
Topics: Inversion of control, DI containers, factory patterns
Hands-on: Configure a simple Python DI container for your adapters
Module 6: Testing Strategies & Test Doubles
⏳ 1 week
Topics: Unit vs. integration tests, mocks, stubs, test layers
Hands-on: Write tests for entities, use cases, and adapter integration
Module 7: Applying Patterns & Best Practices
⏳ 1 week
Topics: Repository, factory, strategy, and observer patterns within layers
Hands-on: Refactor existing modules to apply design patterns appropriately
Module 8: Capstone Project & Architecture Review
⏳ 1 week
Topics: End-to-end application design, code review, anti-pattern identification
Hands-on: Build a small CRUD service following Clean Architecture, then peer-review
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Job Outlook
Clean Architecture expertise is highly valued for senior backend, Python, and microservices roles
Roles include Software Architect, Senior Python Developer, and Backend Engineer
Salaries range from $100,000 to $160,000+ depending on experience and location
Organizations prioritize maintainable codebases for long-lived systems, increasing demand
Specification: Clean Architecture in Python Course
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FAQs
- Requires solid Python knowledge to follow code examples effectively.
- Prior experience with OOP concepts like classes, inheritance, and polymorphism helps.
- Understanding basic design patterns accelerates learning.
- Hands-on exercises involve implementing entities, use cases, and interfaces.
- Beginners may need supplemental Python practice before starting.
- Teaches separation of concerns via entities, use cases, interfaces, and frameworks.
- Covers dependency inversion, DI containers, and factory patterns.
- Hands-on labs implement controllers, repositories, and presenters.
- Testing strategies include unit tests, integration tests, and test doubles.
- Capstone project reinforces end-to-end maintainable architecture.
- Focuses on scalable architecture and maintainable codebases.
- Emphasizes SOLID principles and industry-standard design patterns.
- Builds expertise relevant to Software Architect and Senior Python Developer roles.
- Provides hands-on experience applicable to microservices and enterprise systems.
- Teaches code review and anti-pattern identification for team collaboration.
- Limited coverage of async and event-driven architectures.
- Focuses on synchronous, layered Clean Architecture principles.
- Emphasizes maintainable, testable code over advanced concurrency.
- Suggests additional learning for event-driven systems or async frameworks.
- Solid foundation prepares learners to adopt async patterns independently.
- Dedicate 4–6 hours weekly to complete modules and exercises.
- Focus on one architecture layer or design principle per session.
- Implement hands-on labs incrementally for better retention.
- Document design decisions, patterns, and code examples.
- Review capstone project and peer feedback to consolidate understanding.
