Schema Validation for Construction Data
Overview
Validate data structures against defined schemas for construction data exchange. Ensure API payloads, file imports, and BIM exports conform to expected formats before processing.
Schema Validation Framework
Core Schema Validator
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
from enum import Enum
import json
import re
from datetime import datetime
class SchemaType(Enum):
STRING = "string"
NUMBER = "number"
INTEGER = "integer"
BOOLEAN = "boolean"
ARRAY = "array"
OBJECT = "object"
DATE = "date"
DATETIME = "datetime"
CSI_CODE = "csi_code"
CURRENCY = "currency"
GUID = "guid"
@dataclass
class SchemaField:
name: str
type: SchemaType
required: bool = True
nullable: bool = False
min_value: Optional[float] = None
max_value: Optional[float] = None
min_length: Optional[int] = None
max_length: Optional[int] = None
pattern: Optional[str] = None
enum_values: Optional[List[Any]] = None
items_schema: Optional['Schema'] = None # For arrays
properties: Optional[Dict[str, 'SchemaField']] = None # For objects
description: str = ""
@dataclass
class Schema:
name: str
version: str
fields: Dict[str, SchemaField]
description: str = ""
@dataclass
class SchemaValidationError:
path: str
message: str
expected: str
actual: Any
@dataclass
class SchemaValidationResult:
is_valid: bool
errors: List[SchemaValidationError] = field(default_factory=list)
schema_name: str = ""
schema_version: str = ""
def add_error(self, path: str, message: str, expected: str, actual: Any):
self.errors.append(SchemaValidationError(path, message, expected, actual))
self.is_valid = False
def to_report(self) -> str:
lines = [
f"Schema Validation: {self.schema_name} v{self.schema_version}",
"=" * 50,
f"Status: {'✓ VALID' if self.is_valid else '✗ INVALID'}",
f"Errors: {len(self.errors)}",
""
]
for error in self.errors:
lines.append(f"❌ {error.path}")
lines.append(f" {error.message}")
lines.append(f" Expected: {error.expected}")
lines.append(f" Actual: {error.actual}")
lines.append("")
return "\n".join(lines)
class SchemaValidator:
"""Validate data against schemas."""
# Custom type patterns
PATTERNS = {
SchemaType.CSI_CODE: r'^\d{2}\s?\d{2}\s?\d{2}$',
SchemaType.GUID: r'^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$',
SchemaType.CURRENCY: r'^-?\d+(\.\d{2})?$',
SchemaType.DATE: r'^\d{4}-\d{2}-\d{2}$',
SchemaType.DATETIME: r'^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}',
}
def validate(self, data: Any, schema: Schema) -> SchemaValidationResult:
result = SchemaValidationResult(
is_valid=True,
schema_name=schema.name,
schema_version=schema.version
)
self._validate_object(data, schema.fields, "", result)
return result
def _validate_object(self, data: Any, fields: Dict[str, SchemaField], path: str, result: SchemaValidationResult):
if not isinstance(data, dict):
result.add_error(path or "root", "Expected object", "object", type(data).__name__)
return
# Check required fields
for field_name, field_schema in fields.items():
field_path = f"{path}.{field_name}" if path else field_name
if field_name not in data:
if field_schema.required:
result.add_error(field_path, "Required field missing", "present", "missing")
continue
value = data[field_name]
# Check nullable
if value is None:
if not field_schema.nullable:
result.add_error(field_path, "Field cannot be null", "non-null", "null")
continue
# Validate type
self._validate_field(value, field_schema, field_path, result)
# Check for extra fields (warning only)
for key in data.keys():
if key not in fields:
# Could add warning here if needed
pass
def _validate_field(self, value: Any, schema: SchemaField, path: str, result: SchemaValidationResult):
# Type validation
if not self._check_type(value, schema.type):
result.add_error(path, f"Invalid type", schema.type.value, type(value).__name__)
return
# String validations
if schema.type == SchemaType.STRING:
if schema.min_length and len(value) < schema.min_length:
result.add_error(path, f"String too short", f"min {schema.min_length}", len(value))
if schema.max_length and len(value) > schema.max_length:
result.add_error(path, f"String too long", f"max {schema.max_length}", len(value))
if schema.pattern and not re.match(schema.pattern, value):
result.add_error(path, "Pattern mismatch", schema.pattern, value)
# Numeric validations
if schema.type in (SchemaType.NUMBER, SchemaType.INTEGER):
if schema.min_value is not None and value < schema.min_value:
result.add_error(path, "Value below minimum", f">= {schema.min_value}", value)
if schema.max_value is not None and value > schema.max_value:
result.add_error(path, "Value above maximum", f"<= {schema.max_value}", value)
# Enum validation
if schema.enum_values and value not in schema.enum_values:
result.add_error(path, "Invalid enum value", str(schema.enum_values), value)
# Array validation
if schema.type == SchemaType.ARRAY and schema.items_schema:
for i, item in enumerate(value):
item_path = f"{path}[{i}]"
if schema.items_schema.fields:
self._validate_object(item, schema.items_schema.fields, item_path, result)
# Nested object validation
if schema.type == SchemaType.OBJECT and schema.properties:
self._validate_object(value, schema.properties, path, result)
# Custom type validation
if schema.type in self.PATTERNS:
pattern = self.PATTERNS[schema.type]
if not re.match(pattern, str(value)):
result.add_error(path, f"Invalid {schema.type.value} format", pattern, value)
def _check_type(self, value: Any, expected: SchemaType) -> bool:
type_checks = {
SchemaType.STRING: lambda v: isinstance(v, str),
SchemaType.NUMBER: lambda v: isinstance(v, (int, float)),
SchemaType.INTEGER: lambda v: isinstance(v, int) and not isinstance(v, bool),
SchemaType.BOOLEAN: lambda v: isinstance(v, bool),
SchemaType.ARRAY: lambda v: isinstance(v, list),
SchemaType.OBJECT: lambda v: isinstance(v, dict),
SchemaType.DATE: lambda v: isinstance(v, str),
SchemaType.DATETIME: lambda v: isinstance(v, str),
SchemaType.CSI_CODE: lambda v: isinstance(v, str),
SchemaType.CURRENCY: lambda v: isinstance(v, (int, float, str)),
SchemaType.GUID: lambda v: isinstance(v, str),
}
return type_checks.get(expected, lambda v: True)(value)Construction Data Schemas
Cost Estimate Schema
# Define schema for cost estimate data
COST_ESTIMATE_SCHEMA = Schema(
name="CostEstimate",
version="1.0",
description="Schema for construction cost estimates",
fields={
"project_id": SchemaField(
name="project_id",
type=SchemaType.STRING,
required=True,
description="Unique project identifier"
),