One Checker ((exclusive)) Official

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()

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

# Demonstrate a passing case print("\n" + "="*60) print("DEMONSTRATING A PASSING SCENARIO") print("="*60) passing_checker

# Example 4: Check single source of truth sources = { 'database': {'is_primary': True}, 'cache': {'is_primary': False}, 'api': {'is_primary': False} } Since the requirements are open-ended, I'll create a

# Run all checks and generate report checker.run_all_checks() print(checker.generate_report())

# Example 3: Check one-to-one relationship users = [{'user_id': 1, 'name': 'Alice'}, {'user_id': 2, 'name': 'Bob'}] profiles = [{'user_id': 1, 'bio': 'Engineer'}, {'user_id': 1, 'bio': 'Also artist'}] # Multiple profiles for user 1