Split the monolithic .architecture-rules.yaml (1700+ lines) into focused domain-specific files in .architecture-rules/ directory: - _main.yaml: Core config, principles, ignore patterns, severity levels - api.yaml: API endpoint rules (API-001 to API-005) - service.yaml: Service layer rules (SVC-001 to SVC-007) - model.yaml: Model rules (MDL-001 to MDL-004) - exception.yaml: Exception handling rules (EXC-001 to EXC-005) - naming.yaml: Naming convention rules (NAM-001 to NAM-005) - auth.yaml: Auth and multi-tenancy rules (AUTH-*, MT-*) - middleware.yaml: Middleware rules (MDW-001 to MDW-002) - frontend.yaml: Frontend rules (JS-*, TPL-*, FE-*, CSS-*) - language.yaml: Language/i18n rules (LANG-001 to LANG-010) - quality.yaml: Code quality rules (QUAL-001 to QUAL-003) Also creates scripts/validators/ module with base classes for future modular validator extraction. The validate_architecture.py loader now auto-detects and merges split YAML files while maintaining backward compatibility with single file mode. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
118 lines
4.0 KiB
YAML
118 lines
4.0 KiB
YAML
# Architecture Rules - Service Layer Rules
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# Rules for app/services/**/*.py files
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service_layer_rules:
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- id: "SVC-001"
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name: "Service must NOT raise HTTPException"
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severity: "error"
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description: |
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Services are business logic layer - they should NOT know about HTTP.
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Raise domain-specific exceptions instead (ValueError, custom exceptions).
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pattern:
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file_pattern: "app/services/**/*.py"
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anti_patterns:
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- "raise HTTPException"
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- "from fastapi import HTTPException"
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- id: "SVC-002"
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name: "Service must use proper exception handling"
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severity: "error"
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description: |
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Services should raise meaningful domain exceptions, not generic Exception.
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Create custom exception classes for business rule violations.
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pattern:
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file_pattern: "app/services/**/*.py"
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discouraged_patterns:
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- "raise Exception\\("
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- id: "SVC-003"
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name: "Service methods must accept db session as parameter"
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severity: "error"
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description: |
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Service methods should receive database session as a parameter for testability
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and transaction control. Never create session inside service.
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pattern:
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file_pattern: "app/services/**/*.py"
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required_in_method_signature:
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- "db: Session"
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anti_patterns:
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- "SessionLocal()"
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- "get_db()"
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- id: "SVC-004"
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name: "Service must use Pydantic models for input validation"
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severity: "warning"
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description: |
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Service methods should accept Pydantic models for complex inputs
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to ensure type safety and validation.
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pattern:
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file_pattern: "app/services/**/*.py"
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encouraged_patterns:
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- "BaseModel"
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- id: "SVC-005"
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name: "Service must scope queries to vendor_id in multi-tenant contexts"
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severity: "error"
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description: |
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All database queries must be scoped to vendor_id to prevent cross-tenant data access.
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pattern:
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file_pattern: "app/services/**/*.py"
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check: "vendor_scoping"
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- id: "SVC-006"
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name: "Service must NOT call db.commit()"
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severity: "warning"
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description: |
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Services should NOT commit transactions. Transaction control belongs at the
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API endpoint level where one request = one transaction.
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This allows:
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- Composing multiple service calls in a single transaction
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- Clean rollback on any failure
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- Easier testing of services in isolation
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The endpoint should call db.commit() after all service operations succeed.
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pattern:
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file_pattern: "app/services/**/*.py"
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anti_patterns:
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- "db.commit()"
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exceptions:
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- "log_service.py"
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- id: "SVC-007"
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name: "Service return types must match API response schemas"
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severity: "error"
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description: |
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When a service method's return value will be used as an API response,
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the returned dict keys MUST match the corresponding Pydantic schema fields.
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This prevents the common bug where:
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- Service returns {"total_imports": 5, "completed_imports": 3}
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- Schema expects {"total": 5, "completed": 3}
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- Frontend receives wrong/empty values
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RECOMMENDED PATTERNS:
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1. Return Pydantic model directly from service:
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def get_stats(self, db: Session) -> StatsResponse:
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return StatsResponse(total=count, completed=done)
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2. Return dict with schema-matching keys:
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def get_stats(self, db: Session) -> dict:
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return {"total": count, "completed": done} # Matches StatsResponse
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3. Document the expected schema in service docstring:
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def get_stats(self, db: Session) -> dict:
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"""
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Returns dict compatible with StatsResponse schema.
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Keys: total, pending, completed, failed
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"""
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TESTING: Write tests that validate service output against schema:
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result = service.get_stats(db)
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StatsResponse(**result) # Raises if keys don't match
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pattern:
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file_pattern: "app/services/**/*.py"
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check: "schema_compatibility"
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