Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
Chaos Inject Random Failures in Python
Simulate random failures in a Python function to test error handling and resilience, using random thresholds and controllable success rates.
import random
def unreliable_function(success_rate: float = 0.7) -> str:
"""Simulate a function that sometimes fails."""
if random.random() > success_rate:
raise ConnectionError("Simulated network failure")
return "Operation completed successfully"
if __name__ == "__main__":
random.seed(42)…Health Check Mark Unhealthy Stop Traffic Mock in Python
Simulates a health check with a 20% failure rate and automatically stops traffic when the service is unhealthy.
import time
import random
class HealthCheck:
def __init__(self):
self.is_healthy = True
self.stop_traffic = False
def check_health(self):
# Simulate health check with random failure rate (20% chance unhealthy)
self.is_healthy = random.random() > 0.2
return self.is_heal…How to Implement a Dead Letter Queue Replay in Python
A mock Dead Letter Queue that stores failed messages with retry attempts and replays them with a simple retry counter.
import json
from collections import deque
class DeadLetterQueue:
def __init__(self):
self.messages = deque()
def add_message(self, message_id, payload, attempts=3):
"""Add a message to the DLQ with retry metadata."""
self.messages.append({
"id": message_id,
…How to Implement a Temporary Block in Python
Build a reusable PenaltyBox class that temporarily blocks access after a failure and reports remaining lockout time.
class PenaltyBox:
def __init__(self, block_seconds: int = 30):
self.block_seconds = block_seconds
self._blocked_until = 0.0
self._attempts = 0
def try_access(self, current_time: float) -> bool:
if self._blocked_until and current_time < self._blocked_until:
return Fa…How to Mock Daily and Monthly Quota Counters in Python
Track daily and monthly API call usage with automatic resets, quota checks, and limits using a Python class.
import random
from datetime import datetime, timedelta
class QuotaCounter:
def __init__(self, daily_limit=1000, monthly_limit=20000):
self.daily_limit = daily_limit
self.monthly_limit = monthly_limit
self.daily_usage = 0
self.monthly_usage = 0
self.current_day = datetime.n…How to Mock Fault Injection Percentage in Python
Simulate a service with a 30% failure rate using random.random to test error handling and retries.
import random
class Service:
def call(self):
if random.random() < 0.3: # 30% failure rate
raise ConnectionError("Simulated network fault")
return "ok"
def main():
svc = Service()
random.seed(42) # deterministic for demonstration
results = []
for _ in range(10):
…How to Retry on Specific Exception Tuples in Python
A decorator-based retry pattern that retries a function only when it raises exceptions specified in a tuple, with configurable retries and delay.
import time
import random
from unittest.mock import patch
def retry_on_exceptions(retries=3, exceptions=(ValueError,), delay=0.1):
def decorator(func):
def wrapper(*args, **kwargs):
for attempt in range(retries):
try:
return func(*args, **kwargs)
…How to Stop Receiving Requests Until Ready in Python
A mock server that refuses requests until a readiness gate is passed, simulating fail-stop behavior for production reliability.
import random
import time
class MockServer:
def __init__(self):
self.ready = False
self.requests_received = 0
def readiness_check(self):
"""Simulates a readiness probe. Returns True only when ready."""
if not self.ready:
return False
return True
def r…How to mock a fallback return value in Python
Test a function that returns a default value on failure by mocking requests.get and its side effects.
from unittest.mock import Mock, patch
import requests
def fetch_data(url, default=None):
try:
response = requests.get(url)
response.raise_for_status()
return response.json()
except (requests.RequestException, ValueError):
return default
with patch("requests.get") as mock_get:
…Implementing Fallback with Cached Stale Data in Python
This code demonstrates a resilient data-fetching pattern that caches successful responses, falls back to cached data when the external API fails, and returns stale data as a last-resort fallback.
import random
import time
# Simulated cache dictionary: key -> (value, timestamp)
_cache = {}
_CACHE_TTL = 3 # seconds
# Mock data source (simulates an unreliable external API)
def fetch_mock_data(key):
failure = random.random() < 0.4 # 40% chance of failure
if failure:
raise ConnectionError("Mock …Browse by section
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Reliability & rate limiting — Python code examples
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