Initial PayGuard fraud detection system implementation
- Complete dual-layer architecture for fraud detection - Phase 1: Docker Compose infrastructure (Kafka, Zookeeper, Redis) - Phase 2: Mock ML models (Layer 1 fast, Layer 2 deep) - Phase 3: FastAPI transaction ingestion with JWT auth - Phase 4: Kafka consumer pipeline with feature extraction - Phase 5: Test transaction producer with demo scenarios - Phase 6: Clean code structure and comprehensive documentation - Phase 7: End-to-end validation and demo readiness Demonstrates key system design patterns: - Microservices architecture with decoupled components - Asynchronous event processing via Kafka - Tiered decision-making (fast path vs deep analysis) - Resilience patterns (circuit breaker for graceful degradation) - Behavioral profiling with Redis caching Ready for academic demonstration with clear pipeline observability. Co-authored-by: Copilot <[email protected]>
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"""
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Test Transaction Producer
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Generates demo transactions with controlled scenarios to showcase the pipeline.
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Scenarios:
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1. Normal transactions: low amounts, regular merchants, regular users
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2. Suspicious transactions: large amounts, unknown merchants
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3. Behavioral anomalies: large deviation from user history
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4. Circuit breaker test: can be triggered manually
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Usage:
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python producer/simulate.py
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"""
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import requests
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import json
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import time
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import logging
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from typing import List, Tuple
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from jose import jwt
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# ══════════════════════════════════════════════════════════════════════════════
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# CONFIGURATION
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# ══════════════════════════════════════════════════════════════════════════════
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API_BASE_URL = "http://localhost:8000"
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SECRET_KEY = "payguard-demo-secret-key-change-in-production"
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ALGORITHM = "HS256"
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# Logging setup
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s [%(levelname)s] %(message)s'
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)
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logger = logging.getLogger(__name__)
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# ══════════════════════════════════════════════════════════════════════════════
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# TOKEN GENERATION
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# ══════════════════════════════════════════════════════════════════════════════
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def generate_token(user_id: str) -> str:
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"""Generate a JWT token for the given user"""
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token = jwt.encode({"sub": user_id}, SECRET_KEY, algorithm=ALGORITHM)
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return token
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# ══════════════════════════════════════════════════════════════════════════════
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# TRANSACTION SCENARIOS
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# ══════════════════════════════════════════════════════════════════════════════
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class TransactionScenario:
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"""Represents a test transaction scenario"""
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def __init__(self, name: str, user_id: str, amount: float,
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merchant: str, description: str = ""):
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self.name = name
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self.user_id = user_id
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self.amount = amount
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self.merchant = merchant
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self.description = description
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def submit(self):
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"""Submit this scenario to the API"""
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token = generate_token(self.user_id)
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headers = {
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"Authorization": f"Bearer {token}",
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"Content-Type": "application/json"
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}
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payload = {
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"amount": self.amount,
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"merchant": self.merchant,
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"description": self.description
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}
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logger.info(f"\n{'='*80}")
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logger.info(f"[SCENARIO] {self.name}")
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logger.info(f"[SCENARIO] User: {self.user_id} | Amount: ${self.amount:.2f} | Merchant: {self.merchant}")
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logger.info(f"{'='*80}")
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try:
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response = requests.post(
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f"{API_BASE_URL}/transaction",
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headers=headers,
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json=payload,
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timeout=5
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)
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if response.status_code == 200:
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result = response.json()
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logger.info(f"[API RESPONSE] ✓ {result['message']}")
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logger.info(f"[TRANSACTION ID] {result['transaction_id']}")
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else:
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logger.error(f"[API RESPONSE] ✗ Status {response.status_code}: {response.text}")
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except requests.exceptions.ConnectionError:
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logger.error("[API RESPONSE] ✗ Cannot connect to API. Is it running on port 8000?")
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except Exception as e:
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logger.error(f"[API RESPONSE] ✗ Error: {str(e)}")
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# ══════════════════════════════════════════════════════════════════════════════
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# TEST SCENARIOS
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# ══════════════════════════════════════════════════════════════════════════════
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def get_demo_scenarios() -> List[TransactionScenario]:
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"""Get all demo scenarios in a logical order"""
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return [
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# Scenario 1: Normal transaction (should be approved fast)
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TransactionScenario(
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name="1. NORMAL TRANSACTION (Low Risk)",
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user_id="user_001",
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amount=75.50,
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merchant="Starbucks Coffee",
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description="Regular coffee purchase"
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),
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# Scenario 2: Another normal transaction from same user
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TransactionScenario(
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name="2. NORMAL TRANSACTION #2 (Low Risk)",
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user_id="user_001",
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amount=120.00,
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merchant="Target Retail",
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description="Grocery shopping"
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),
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# Scenario 3: Large transaction from user with low history (suspicious)
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TransactionScenario(
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name="3. BEHAVIORAL ANOMALY (High Risk)",
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user_id="user_001",
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amount=8500.00,
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merchant="unknown_offshore_merchant.biz",
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description="Large purchase from unknown merchant"
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),
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# Scenario 4: New user, normal transaction
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TransactionScenario(
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name="4. NEW USER, NORMAL AMOUNT (Low Risk)",
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user_id="user_002",
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amount=45.00,
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merchant="McDonald's Restaurant",
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description="Meal purchase"
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),
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# Scenario 5: Existing user, normal range
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TransactionScenario(
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name="5. RETURNING USER, NORMAL (Low Risk)",
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user_id="user_002",
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amount=65.00,
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merchant="CVS Pharmacy",
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description="Pharmacy purchase"
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),
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# Scenario 6: User 3, establish history
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TransactionScenario(
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name="6. NEW USER, SMALL TRANSACTION (Low Risk)",
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user_id="user_003",
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amount=25.00,
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merchant="Uber Eats",
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description="Food delivery"
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),
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# Scenario 7: User 3, escalating pattern
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TransactionScenario(
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name="7. SAME USER, INCREASED AMOUNT (Medium Risk)",
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user_id="user_003",
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amount=150.00,
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merchant="Amazon.com",
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description="Online shopping"
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),
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# Scenario 8: User 3, huge spike (very suspicious)
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TransactionScenario(
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name="8. SUSPICIOUS PATTERN (Very High Risk)",
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user_id="user_003",
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amount=12500.00,
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merchant="LuxuryWatches_CN.ru",
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description="Suspicious high-value purchase"
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),
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]
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# ══════════════════════════════════════════════════════════════════════════════
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# MAIN
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# ══════════════════════════════════════════════════════════════════════════════
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def main():
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"""Run demo scenarios"""
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logger.info("="*80)
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logger.info("PayGuard Demo - Transaction Producer")
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logger.info("="*80)
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logger.info(f"API Base URL: {API_BASE_URL}")
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logger.info("="*80)
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# Check if API is available
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try:
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response = requests.get(f"{API_BASE_URL}/health", timeout=2)
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if response.status_code == 200:
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logger.info("✓ API is healthy and ready\n")
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else:
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logger.error("✗ API health check failed")
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return
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except:
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logger.error("✗ Cannot connect to API. Make sure it's running:")
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logger.error(" uvicorn api.main:app --reload\n")
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return
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scenarios = get_demo_scenarios()
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for i, scenario in enumerate(scenarios, 1):
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scenario.submit()
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# Small delay between scenarios to avoid overwhelming
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if i < len(scenarios):
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logger.info(f"\n[DEMO] Waiting 3 seconds before next scenario...")
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time.sleep(3)
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logger.info(f"\n{'='*80}")
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logger.info("✓ All demo scenarios submitted!")
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logger.info("="*80)
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logger.info("\nCheck the consumer terminal for detailed pipeline execution logs.")
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logger.info("Open another terminal and query Redis to see the results:")
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logger.info(" redis-cli")
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logger.info(" > KEYS result:*")
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logger.info(" > GET result:<transaction_id>")
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if __name__ == "__main__":
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main()
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