Design a Rule Evaluation Engine for Spending Policy Violations

Problem Statement

Design a software component that evaluates incoming transaction requests against a set of spending policies to determine if the transaction should be 'APPROVED' or 'DENIED'.

Requirements

1. Policy Structure: Policies consist of conditions (e.g., amount > 500, category == 'Travel', merchant == 'Amazon').
2. Dynamic Evaluation: Policies should be configurable without requiring a full system deployment.
3. Transaction Context: A transaction includes transaction_id, user_id, amount, currency, category, and merchant_name.
4. Performance: Evaluation must be performed in near real-time (latency < 100ms).

Task

Define an interface or class structure that allows for defining, storing, and evaluating these rules. You must implement an evaluation function that processes a transaction against a list of active rules. Consider how to handle conflicting rules (e.g., a whitelist and a blacklist policy).

Interface

class Rule:
    # Define structure for a rule
    pass

def evaluate_transaction(transaction: dict, rules: list[Rule]) -> str:
    # Returns 'APPROVED' or 'DENIED'
    pass

Example

• Input: Transaction {'amount': 600, 'category': 'Travel'}. Rules: [Rule('amount < 500'), Rule('category == Travel', action='DENY')]
• Output: 'DENIED' (due to the category-based policy).

Constraints

• Assume rules are stored in a database or cache.
• Consider how to handle rule dependencies or sequential order.