Files
orion/.architecture-rules/service.yaml
Samir Boulahtit 33c5875bc8 refactor: split architecture rules into domain-specific files
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>
2025-12-13 22:36:33 +01:00

118 lines
4.0 KiB
YAML

# Architecture Rules - Service Layer Rules
# Rules for app/services/**/*.py files
service_layer_rules:
- id: "SVC-001"
name: "Service must NOT raise HTTPException"
severity: "error"
description: |
Services are business logic layer - they should NOT know about HTTP.
Raise domain-specific exceptions instead (ValueError, custom exceptions).
pattern:
file_pattern: "app/services/**/*.py"
anti_patterns:
- "raise HTTPException"
- "from fastapi import HTTPException"
- id: "SVC-002"
name: "Service must use proper exception handling"
severity: "error"
description: |
Services should raise meaningful domain exceptions, not generic Exception.
Create custom exception classes for business rule violations.
pattern:
file_pattern: "app/services/**/*.py"
discouraged_patterns:
- "raise Exception\\("
- id: "SVC-003"
name: "Service methods must accept db session as parameter"
severity: "error"
description: |
Service methods should receive database session as a parameter for testability
and transaction control. Never create session inside service.
pattern:
file_pattern: "app/services/**/*.py"
required_in_method_signature:
- "db: Session"
anti_patterns:
- "SessionLocal()"
- "get_db()"
- id: "SVC-004"
name: "Service must use Pydantic models for input validation"
severity: "warning"
description: |
Service methods should accept Pydantic models for complex inputs
to ensure type safety and validation.
pattern:
file_pattern: "app/services/**/*.py"
encouraged_patterns:
- "BaseModel"
- id: "SVC-005"
name: "Service must scope queries to vendor_id in multi-tenant contexts"
severity: "error"
description: |
All database queries must be scoped to vendor_id to prevent cross-tenant data access.
pattern:
file_pattern: "app/services/**/*.py"
check: "vendor_scoping"
- id: "SVC-006"
name: "Service must NOT call db.commit()"
severity: "warning"
description: |
Services should NOT commit transactions. Transaction control belongs at the
API endpoint level where one request = one transaction.
This allows:
- Composing multiple service calls in a single transaction
- Clean rollback on any failure
- Easier testing of services in isolation
The endpoint should call db.commit() after all service operations succeed.
pattern:
file_pattern: "app/services/**/*.py"
anti_patterns:
- "db.commit()"
exceptions:
- "log_service.py"
- id: "SVC-007"
name: "Service return types must match API response schemas"
severity: "error"
description: |
When a service method's return value will be used as an API response,
the returned dict keys MUST match the corresponding Pydantic schema fields.
This prevents the common bug where:
- Service returns {"total_imports": 5, "completed_imports": 3}
- Schema expects {"total": 5, "completed": 3}
- Frontend receives wrong/empty values
RECOMMENDED PATTERNS:
1. Return Pydantic model directly from service:
def get_stats(self, db: Session) -> StatsResponse:
return StatsResponse(total=count, completed=done)
2. Return dict with schema-matching keys:
def get_stats(self, db: Session) -> dict:
return {"total": count, "completed": done} # Matches StatsResponse
3. Document the expected schema in service docstring:
def get_stats(self, db: Session) -> dict:
"""
Returns dict compatible with StatsResponse schema.
Keys: total, pending, completed, failed
"""
TESTING: Write tests that validate service output against schema:
result = service.get_stats(db)
StatsResponse(**result) # Raises if keys don't match
pattern:
file_pattern: "app/services/**/*.py"
check: "schema_compatibility"