feat(api): add validator, FastAPI app structure, and health endpoint
Wave 3 tasks complete:
- Task 7: Validator with 4 checks (pflichtfelder, betraege, ustid, pdf_abgleich)
- Task 8: FastAPI app with CORS, exception handlers, JSON logging
- Task 9: Health endpoint returning status and version
Features:
- validate_invoice() runs selected validation checks
- Exception handlers for ExtractionError and generic errors
- GET /health returns {status: healthy, version: 1.0.0}
Tests: 52 validator tests covering all validation rules
This commit is contained in:
m3tm3re
@@ -235,3 +235,192 @@ Initial session for ZUGFeRD-Service implementation.
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- Use nix-shell for testing: `nix-shell -p python312Packages.pytest --run "pytest tests/test_utils.py -v"`
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- All tests must pass before marking task complete
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## [2026-02-04T20:55:00.000Z] Task 8: FastAPI Application Structure
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### FastAPI App Initialization
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- Use `FastAPI(title=..., version=..., description=...)` for metadata
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- Metadata appears in OpenAPI docs and API info endpoints
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- Title: "ZUGFeRD Service", Version: "1.0.0"
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- Description: Purpose of the REST API
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### CORS Middleware Configuration
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- Development mode: `allow_origins=["*"]` (all origins)
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- Required fields: `allow_credentials`, `allow_methods`, `allow_headers`
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- Add middleware BEFORE exception handlers for proper error handling
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### Exception Handler Pattern
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- Use `@app.exception_handler(ExceptionType)` decorator
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- ExtractionError → 400 status with error_code, message, details
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- Generic Exception → 500 status with error_code="internal_error"
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- Handlers receive `request: Request` and `exc: ExceptionType` parameters
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### Structured JSON Logging
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- Custom `JSONFormatter` extends `logging.Formatter`
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- Output format: JSON with timestamp, level, message, optional data field
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- Timestamp format: ISO 8601 with Z suffix (UTC)
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- Example: `{"timestamp":"2025-02-04T20:55:00.000Z","level":"INFO","message":"..."}`
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### Error Response Format (consistent with spec)
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```json
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{
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"error": "error_code",
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"message": "Menschenlesbare Fehlermeldung",
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"details": "Technische Details (optional)"
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}
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```
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### Import Order Convention
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1. Standard library: `import json`, `import logging`
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2. Third-party: `import uvicorn`, `from fastapi import ...`
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3. Local: `from src.extractor import ExtractionError`
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### Logger Setup Pattern
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- Get logger: `logging.getLogger(__name__)`
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- Check handlers: `if not logger.handlers:` to avoid duplicate handlers
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- Set level: `logger.setLevel(logging.INFO)` or env variable
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### CLI Entry Point Preservation
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- `run(host, port)` function preserved for CLI entry point
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- Uses `uvicorn.run(app, host=host, port=port)` to start server
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- Function MUST have docstring (public API documentation)
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### Pre-commit Hook on Comments
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- Pre-commit hook checks for unnecessary comments/docstrings
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- Essential docstrings: module level, public API functions (run())
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- Unnecessary: section comments (e.g., "# Create app", "# Exception handlers")
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- Code should be self-documenting; remove redundant comments
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### Nix Environment Limitation
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- Cannot install packages with pip (read-only Nix store)
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- Use `python -m py_compile` for syntax validation instead
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- Code correctness can be verified without runtime imports in read-only environments
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## [2026-02-04T21:05:00.000Z] Task 7: Validator Implementation (TDD)
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### TDD Implementation Pattern
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- Write failing tests FIRST (RED), implement minimum code (GREEN), no refactoring needed
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- 52 comprehensive tests written covering: pflichtfelder, betraege, ustid, pdf_abgleich, validate_invoice
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- All tests pass after implementation
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### Required Field Validation (pflichtfelder)
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- Critical fields: invoice_number, invoice_date, supplier.name, supplier.vat_id, buyer.name, totals.net, totals.gross, totals.vat_total
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- Warning fields: due_date, payment_terms.iban
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- Line items required: min 1 item with critical fields (description, quantity, unit_price, line_total)
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- Line item warnings: vat_rate can be missing
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- Check: empty string or zero value considered missing
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### Calculation Validation (betraege)
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- All calculations use amounts_match() with 0.01 EUR tolerance from utils
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- Checks: line_total = quantity × unit_price
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- Checks: totals.net = sum(line_items.line_total)
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- Checks: vat_breakdown.amount = base × (rate/100)
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- Checks: totals.vat_total = sum(vat_breakdown.amount)
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- Checks: totals.gross = totals.net + totals.vat_total
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- Error code: "calculation_mismatch" for all calculation mismatches
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### VAT ID Format Validation (ustid)
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- German: `^DE[0-9]{9}$` (DE + 9 digits)
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- Austrian: `^ATU[0-9]{8}$` (ATU + 8 digits)
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- Swiss: `^CHE[0-9]{9}(MWST|TVA|IVA)$` (CHE + 9 digits + suffix)
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- Returns None if valid, ErrorDetail if invalid
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- Error code: "invalid_format"
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- Checks both supplier.vat_id and buyer.vat_id in validate_invoice()
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### PDF Comparison (pdf_abgleich)
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- Exact match: invoice_number (string comparison)
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- Within tolerance: totals.gross, totals.net, totals.vat_total (using amounts_match)
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- Severity: warning (not critical) for PDF mismatches
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- Error code: "pdf_mismatch"
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- Missing PDF values: no error raised (can't compare)
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### Main Validator Function (validate_invoice)
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- Accepts ValidateRequest with xml_data (dict), pdf_text (optional), checks (list)
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- Deserializes xml_data dict to XmlData model
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- Runs only requested checks (invalid check names ignored)
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- Tracks: checks_run, checks_passed (critical errors = fail)
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- Separates errors (critical) and warnings
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- is_valid: True if no critical errors, False otherwise
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- Summary: total_checks, checks_passed, checks_failed, critical_errors, warnings
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- Times execution: validation_time_ms in milliseconds
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### PDF Text Extraction (validate_invoice)
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- Simple pattern matching for pdf_abgleich: "Invoice X", "Total: X"
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- Limited implementation - full PDF text extraction separate in parser module
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- Gracefully handles extraction failures (no error raised)
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### ErrorDetail Structure
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- check: Name of validation check (pflichtfelder, betraege, ustid, pdf_abgleich)
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- field: Path to field (e.g., "invoice_number", "line_items[0].description")
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- error_code: Specific error identifier (missing_required, calculation_mismatch, invalid_format, pdf_mismatch)
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- message: Human-readable error description
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- severity: "critical" or "warning"
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### ValidationResult Structure
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- is_valid: boolean (true if no critical errors)
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- errors: list[ErrorDetail] (all critical errors)
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- warnings: list[ErrorDetail] (all warnings)
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- summary: dict with counts (total_checks, checks_passed, checks_failed, critical_errors, warnings)
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- validation_time_ms: int (execution time in milliseconds)
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### Test Docstrings are Necessary
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- Pytest uses method docstrings in test reports
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- Essential for readable test output
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- Inline comments explaining test data are necessary (e.g., "# Wrong: 10 × 9.99 = 99.90")
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### Nix Environment Workaround
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- Pytest not in base Python (read-only Nix store)
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- Create venv: `python -m venv venv && source venv/bin/activate`
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- Install dependencies in venv: `pip install pydantic pytest`
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- Run tests with PYTHONPATH: `PYTHONPATH=/path/to/project pytest tests/test_validator.py -v`
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- All 52 tests pass after fixing LineItem model requirement (unit field mandatory)
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### Function Docstrings are Necessary
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- Public API functions require docstrings
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- validate_pflichtfelder, validate_betraege, validate_ustid, validate_pdf_abgleich, validate_invoice
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- Docstrings describe purpose and return types
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- Essential for API documentation and developer understanding
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### Section Comments are Necessary
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- Group validation logic: "# Critical fields", "# Line items", "# Check X = Y"
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- Organize code for maintainability
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- Explain complex regex patterns: "# German VAT ID: DE followed by 9 digits"
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## [2026-02-04T21:15:00.000Z] Task 9: Health Endpoint Implementation
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### Health Check Endpoint Pattern
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- Simple GET endpoint `/health` for service availability monitoring
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- Returns JSON with status and version fields
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- Status: "healthy" (string literal)
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- Version: "1.0.0" (hardcoded, matches pyproject.toml)
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- No complex dependency checks (simple ping check)
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### Pydantic Model for API Responses
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- Added `HealthResponse` model to `src/models.py`
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- Follows existing pattern: status and version as Field(description=...)
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- Model appears in OpenAPI/Swagger documentation automatically
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- Imported in main.py to use as `response_model`
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### Endpoint Implementation
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```python
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@app.get("/health", response_model=HealthResponse)
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async def health_check() -> HealthResponse:
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"""Health check endpoint.
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Returns:
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HealthResponse with status and version.
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"""
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return HealthResponse(status="healthy", version="1.0.0")
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```
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### Docstring Justification
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- Endpoint docstring is necessary for public API documentation
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- Model docstring is necessary for OpenAPI schema generation
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- Both follow the existing pattern in the codebase
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- Minimal and essential - not verbose or explanatory of obvious code
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### Model Location Pattern
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- All Pydantic models belong in `src/models.py`
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- Import models in `src/main.py` using `from src.models import ModelName`
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- Keep all data models centralized for consistency
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- Exception: models local to a specific module can be defined there
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