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)…How to Implement Graceful Degradation with Feature Disabling in Python
A pattern that disables enhanced features and falls back to basic functionality when a dependency fails, with mock-based testing.
import random
from unittest.mock import patch
class EnhancedFeature:
"""A feature that can gracefully degrade when a dependency is unavailable."""
def __init__(self):
self.feature_enabled = True
def get_enhanced_data(self):
"""Simulate an enhanced feature that depends on external data."…How to Inject Random Latency for Chaos Testing in Python
Mock unreliable services by wrapping functions with a decorator that adds random network-like delays before execution.
import random
import time
from functools import wraps
def inject_latency(func):
@wraps(func)
def wrapper(*args, **kwargs):
latency = random.uniform(0.1, 0.5)
print(f"Injecting {latency:.3f}s latency...")
time.sleep(latency)
return func(*args, **kwargs)
return wrapper
@inje…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 Mock a Circuit Breaker Reset Timeout in Python
This code implements a simple circuit breaker with a reset timeout test, simulating a flaky service to show half-open state transitions.
import time
import random
class CircuitBreaker:
def __init__(self, failure_threshold=3, reset_timeout=5):
self.failure_threshold = failure_threshold
self.reset_timeout = reset_timeout
self.failure_count = 0
self.last_failure_time = None
self.state = "CLOSED" # CLOSED (nor…How to Mock a Timeout per HTTP Request in Python
Simulate a per-request HTTP timeout using unittest.mock to test timeout handling without network access.
import time
from unittest.mock import Mock, patch
# Simulate an HTTP client that might time out
def fetch_data(url, timeout=5):
time.sleep(0.5) # Simulate network delay
return f"Response from {url}"
# Mock to test timeout behavior without real network
def test_timeout():
mock_response = Mock(side_effect…How to retry idempotent operations with a mock in Python
Wrap a flaky idempotent operation in a retry loop with exponential backoff, and use unittest.mock to deterministically test the str's behavior.
import random
import time
from unittest.mock import Mock
def idempotent_operation(value):
"""Simulate an idempotent operation that sometimes fails."""
if random.random() < 0.6: # 60% failure rate
raise ConnectionError("Temporary failure")
return value * 2
def retry_with_backoff(operation, max_…Mock Distributed Rate Limiter with Dict in Python
Simulates a distributed token-bucket rate limiter with a thread-safe dict, useful for testing before moving to Redis.
import time
import threading
from collections import defaultdict
class DistributedRateLimiter:
"""
A mock distributed rate limiter using a dict with thread-safe access.
Implements a token bucket algorithm per user.
"""
def __init__(self, rate_per_second=5, burst_capacity=10):
self.rate_p…Browse by section
Each section groups closely related Python snippets.
Reliability & rate limiting — Python code examples
What you will find here
This page collects reliability & rate limiting snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.