Reliability & rate limiting
Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.
How to Build a Rate Limiter in Python
Implements a simple sliding-window rate limiter that caps the number of calls per period, used to throttle processing of a data list.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.timestamps = []
def allow(self):
now = time.time()
self.timestamps = [t for t in self.timestamps if now - t < self.period]
if len(self.tim…How to Implement a Circuit Breaker in Python
A Python dataclass that provides circuit breaker logic with closed, open, and half-open states to fail fast on repeated errors.
from dataclasses import dataclass
from datetime import datetime, timedelta
import time
@dataclass
class CircuitBreaker:
failure_threshold: int = 3
timeout_seconds: float = 5.0
failures: int = 0
state: str = "closed"
last_failure: datetime = None
def call(self, func):
if self.state ==…How to Mock a Slow Startup Probe in Python
Simulate slow service initialization with a configurable mock delay to test readiness probes.
import time
from dataclasses import dataclass, field
@dataclass
class StartupProbe:
name: str
min_wait_sec: float = 0.5
max_wait_sec: float = 2.0
_ready: bool = field(default=False, init=False, repr=False)
def initialize(self) -> None:
"""Simulate slow startup with a fixed mock delay."""…How to implement rate limiting in Python
Build a simple sliding-window rate limiter in Python that enforces a max number of calls per time period and formats data with timestamps.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.calls = []
def allow(self):
now = time.time()
# Remove calls older than the period window
self.calls = [t for t in self.calls if now -…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 …Rate Limiting in Python with a Sliding Window
A beginner-friendly dataclass-based sliding window rate limiter that controls how many calls are allowed per time window.
import time
from dataclasses import dataclass
@dataclass
class RateLimiter:
max_calls: int
window_seconds: float = 1.0
def __post_init__(self):
self.calls = []
self._start = time.monotonic()
def _update(self, now):
self.calls = [t for t in self.calls if now - t < self.window…Browse by section
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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.
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