# one_checker.py """ One Checker - Ensures data consistency and uniqueness across system components """ from typing import Any, Dict, List, Callable, Optional from dataclasses import dataclass from enum import Enum import json
# Example 2: Check active configuration configs = { 'dev': {'active': False, 'env': 'development'}, 'prod': {'active': True, 'env': 'production'}, 'staging': {'active': False, 'env': 'staging'} } one checker
I'll help you develop a "one checker" feature. Since the requirements are open-ended, I'll create a that verifies if something is "one" (unique, consistent, singular) across a system. # one_checker
def check_sot(): return checker.check_single_source_of_truth(sources) Uniqueness Validation - Ensures no duplicate IDs/keys 2
passing_checker.register_check("Clean data uniqueness", clean_check) passing_checker.run_all_checks() print(passing_checker.generate_report()) 1. Uniqueness Validation - Ensures no duplicate IDs/keys 2. Single Active Configuration - Prevents multiple active states 3. One-to-One Relationship Verification - Catches data mapping errors 4. Single Source of Truth - Identifies primary data sources 5. Extensible Design - Easy to add custom checks API Endpoint Example (FastAPI): # api_one_checker.py from fastapi import FastAPI, HTTPException from pydantic import BaseModel from typing import List, Dict, Any app = FastAPI()
