clean-architecture

# Clean Architecture Framework

A disciplined approach to structuring software so that business rules remain independent of frameworks, databases, and delivery mechanisms. Apply these principles when designing system architecture, reviewing module boundaries, or advising on dependency management.

## Core Principle

**Source code dependencies must point inward — toward higher-level policies.** Nothing in an inner circle can know anything about an outer circle. This single rule produces systems that are testable and independent of frameworks, UI, database, and any external agency. Business rules are what matter; databases, web frameworks, and delivery mechanisms are details — when details depend on policies, you can defer decisions, swap implementations, and test business logic in isolation.

## Scoring

**Goal: 10/10.** Score one point for each of the seven Quick Diagnostic rows the architecture satisfies (0-7), then map to a 0-10 band: 6-7 satisfied = **9-10** (Dependency Rule holds, business logic is framework- and DB-independent); 4-5 = **6-8** (core is testable but some details leak inward); 2-3 = **3-5** (framework or persistence dictates structure); 0-1 = **0-2** (no boundaries — business rules live in controllers and ORM models). Report the score, the failed diagnostic rows, and the specific inversion needed to fix each.

### 1. Dependency Rule and Concentric Circles

**Core concept:** Organize the architecture as concentric circles — Entities (enterprise business rules) innermost, then Use Cases (application business rules), then Interface Adapters, with Frameworks and Drivers outermost. Source code dependencies always point inward.

**Why it works:** When high-level policies don't depend on low-level details, you can swap the database, web framework, or API style without touching business logic — the system becomes resilient to the most volatile parts of the stack.

**Key insights:**
- Inner circles cannot mention outer circle names — no classes, functions, variables, or data formats from outside
- Data crossing a boundary must be in the form most convenient for the inner circle, never dictated by the outer
- Dependency Inversion (interfaces defined inward, implemented outward) is the mechanism that enforces the rule
- The number of circles is not fixed — four is typical; the rule stays the same
- Frameworks are details, not architecture — they belong in the outermost circle

**Code applications:**

| Context | Pattern | Example |
|---------|---------|---------|
| **Layer direction** | Inner circles define interfaces; outer implement | `UserRepository` interface in Use Cases; `PostgresUserRepository` in Adapters |
| **Data crossing** | DTOs cross boundaries, not ORM entities | Use Case returns `UserResponse` DTO, not an ActiveRecord model |
| **Dependency direction** | Import arrows always point inward | Controller imports Use Case; Use Case never imports Controller |

See [references/dependency-rule.md](references/dependency-rule.md) when an inner-circle import points outward and you need the four-circle code walkthrough, the data-crossing rules, and the four-step dependency-inversion procedure to fix it.

### 2. Entities and Use Cases

**Core concept:** Entities encapsulate enterprise-wide business rules — rules that would exist even without software. Use Cases contain application-specific rules that orchestrate the flow of data to and from Entities.

**Why it works:** Separating what the business does (Entities) from how the application orchestrates it (Use Cases) lets you reuse Entities across applications and change application behavior without altering core business rules.

**Key insights:**
- Entities are not database rows — they are objects or pure functions encapsulating critical business rules
- Use Cases accept Request Models and return Response Models — never framework objects
- Each Use Case is a single application operation (`CreateOrder`, `ApproveExpense`)
- The Interactor pattern: a Use Case class implements an input boundary interface and calls an output boundary interface
- Changes to a Use Case should never affect an Entity; Entity changes may ripple to Use Cases

**Code applications:**

| Context | Pattern | Example |
|---------|---------|---------|
| **Entity design** | Critical business rules, zero framework dependencies | `Order.calculateTotal()` applies tax rules; knows nothing about HTTP |
| **Request/Response** | Simple data structures cross the boundary | `CreateOrderRequest { items, customerId }` — no ORM models |
| **Single responsibility** | One Use Case per operation | `PlaceOrder`, `CancelOrder`, `RefundOrder` as separate classes |
| **Interactor** | Implements Input Port, calls Output Port | `PlaceOrderInteractor implements PlaceOrderInput` |

See [references/entities-use-cases.md](references/entities-use-cases.md) when designing an Interactor or deciding what belongs in an Entity versus a Use Case — full Enterprise vs. Application Business Rules treatment with request/response model examples.

### 3. Interface Adapters and Frameworks

**Core concept:** Interface Adapters convert data between the form convenient for Use Cases/Entities and the form required by external agencies. Frameworks and Drivers are the outermost layer — glue code to the outside world.

**Why it works:** When the web framework, ORM, or message queue is confined to the outer circles, replacing any of them is a localized change. The database is a detail; the web is a detail; details should be plugins to your business rules, not the skeleton of the application.

**Key insights:**
- Controllers translate HTTP into Use Case input; Presenters translate Use Case output into view models
- Gateways implement repository interfaces defined by Use Cases — the inner circle defines the contract, the outer fulfills it
- Business rules never know whether data lives in SQL, NoSQL, or flat files, or that delivery is HTTP
- Treat frameworks with suspicion — they want you to couple to them; ke