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How to Implement Retry with Exponential Backoff for Cloud API 429 Errors in Python
Implement a retry-with-backoff loop in Python to handle 429 throttling errors from cloud APIs, using exponential delay between attempts.
import time
import random
import requests
def api_call(attempt):
"""Mock cloud API that returns 429 for the first two attempts."""
if attempt < 2:
return 429, "Too Many Requests"
return 200, {"data": "success"}
def retry_with_backoff(api_func, max_retries=3, base_delay=0.1):
for attempt in …Cache Data in Redis with Python
A beginner-friendly Redis cache helper that stores JSON strings with a TTL and retrieves them with the redis-py client.
import redis
class DataCache:
def __init__(self, host="localhost", port=6379, db=0):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
def cache_data(self, key, value, ttl=60):
self.client.setex(key, ttl, value)
def get_cached_data(self, key):
return …How to Cache Function Results with Redis in Python
A RedisCache helper class caches function results using a decorator, with JSON serialization and TTL-based expiry.
import redis
import json
from functools import wraps
class RedisCache:
def __init__(self, host='localhost', port=6379, db=0, ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.ttl = ttl
def cached(self, key_prefix):
def decorator(func):
…How to Use Redis as a Cache in Python
A beginner-friendly RedisCache helper that stores, retrieves, and deletes JSON values with automatic TTL expiration using the redis-py client.
import json
import time
import redis
class RedisCache:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.default_ttl = default_ttl
def set(self, key, value, ttl=None):
"""Store a v…Redis Cache Helper Class in Python with TTL
Build a DataHelper class that caches function results in Redis with a default TTL, using get_or_set and clear methods.
import redis
import json
import time
class DataHelper:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.default_ttl = default_ttl
def get_or_set(self, key, data_func, ttl=None):
c…Redis GET SET EX TTL mock in Python
A thread-safe Python class mimicking Redis GET, SET with EX, and TTL commands for in-memory testing.
import time
import threading
from typing import Optional, Callable
class RedisTTLMock:
def __init__(self):
self._store: dict[str, tuple[str, float]] = {}
self._lock = threading.Lock()
def set(self, key: str, value: str, ex: Optional[int] = None) -> bool:
expiry = time.time() + ex if …Simple Redis Cache Helper in Python
Build a minimal Redis-backed cache with TTL, JSON serialization, and automated fetching to speed up repeated expensive lookups.
import time
import redis
import json
class SimpleCache:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.default_ttl = default_ttl
def get(self, key):
value = self.client.get(key)…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 an idempotency key store in Python
Build an in-memory idempotency key store with TTL that processes a request once and reuses the cached result for duplicate calls.
import hashlib
import time
from typing import Dict, Optional
class IdempotencyStore:
"""Simple in-memory idempotency key store with mock processing."""
def __init__(self, ttl_seconds: int = 3600) -> None:
self.ttl = ttl_seconds
self._store: Dict[str, tuple[str, float]] = {}
def _is_expi…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 -…How to implement rate limiting in Python
A beginner-friendly Python rate limiter that throttles API calls and retries parsing tasks with exponential backoff.
import time
import random
class RateLimiter:
def __init__(self, max_calls, per_seconds):
self.max_calls = max_calls
self.per_seconds = per_seconds
self.timestamps = []
def allow(self):
now = time.time()
self.timestamps = [t for t in self.timestamps if now - t < sel…How to mock short TTL access tokens in Python
Simulate short-lived access tokens with a TTL, issue and validate them, and watch expiry behavior.
import time
import uuid
from datetime import datetime, timedelta
class AccessTokenManager:
def __init__(self, ttl_seconds=30):
self.ttl_seconds = ttl_seconds
self.tokens = {}
def issue_token(self):
token_id = uuid.uuid4().hex
expiry = datetime.now() + timedelta(seconds=self.t…Browse by section
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