Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
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 Try Confirm Cancel Pattern in Python
Define a simple class with confirm and cancel methods, execute a try confirm with error handling, and print the final state.
class TCC:
def __init__(self):
self.confirmed = False
self.cancelled = False
def confirm(self):
self.confirmed = True
return "confirmed"
def cancel(self):
self.cancelled = True
return "cancelled"
def try_confirm(self):
try:
result =…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:
…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.