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How to Retry LLM Calls on Rate Limit Errors in Python
Implement a retry mechanism with exponential backoff for LLM API calls that raises a custom RateLimitError, using a mock function to demonstrate the pattern.
import time
import random
def mock_llm_call():
"""Simulates an LLM API call that may raise a rate limit error."""
if random.random() < 0.4: # 40% chance of rate limit
raise RateLimitError("Rate limit exceeded. Try again later.")
return {"response": "Hello world from mock LLM"}
class RateLimitE…Build a Complete Web Scraper with Requests and BeautifulSoup in Python
Scrape multiple paginated pages from a website using Requests and BeautifulSoup, with retry logic, error handling, and CSV export.
import requests
from bs4 import BeautifulSoup
import csv
import time
from typing import List, Dict, Optional
class WebScraper:
def __init__(self, base_url: str, output_file: str = "scraped_data.csv"):
self.base_url = base_url
self.output_file = output_file
self.session = requests.Session()…Python Exponential Backoff Retry Example
Retry a flaky function with exponential backoff and jitter-free delays, printing each attempt and finally returning the successful result.
import random
import time
def flaky_function():
if random.random() < 0.6:
raise ConnectionError("Temporary network error")
return "success"
def retry_with_exponential_backoff(func, max_retries=5, base_delay=1.0):
for attempt in range(max_retries + 1):
try:
return func()
…Exponential Backoff with Jitter for Cloud API Calls in Python
A Python snippet demonstrating exponential backoff with jitter for retrying transient cloud API failures, using a simulated client that has a configurable success rate.
import random
import time
def exponential_backoff_with_jitter(retries=5, base_delay=0.5, max_delay=4.0, jitter_factor=0.3):
for attempt in range(1, retries + 1):
delay = min(max_delay, base_delay * (2 ** (attempt - 1)))
jitter = delay * random.uniform(-jitter_factor, jitter_factor)
effect…How to Implement Retry with Exponential Backoff and Jitter in Python
This code demonstrates a retry mechanism with exponential backoff and optional full jitter, using a flaky mock network call for testing.
import random
import time
def retry_with_backoff(func, max_attempts=5, base_delay=0.1, jitter=True):
"""
Retry a function with exponential backoff and optional full jitter.
"""
for attempt in range(max_attempts):
try:
return func()
except Exception as e:
if att…How to Handle Retry-After Header in Python
Parse the Retry-After header from rate-limited API responses and implement retry logic with proper delays in Python.
```python
import time
from datetime import datetime, timedelta
class RetryAfterHandler:
def __init__(self, max_retries=3):
self.max_retries = max_retries
def get_retry_after_seconds(self, response_headers):
retry_after_value = response_headers.get("Retry-After")
if retry_after_value …How to Implement At-Least-Once Delivery with Acknowledgment in Python
This code demonstrates a mock message broker with at-least-once delivery, including retry logic and acknowledgment after successful processing.
import time
import uuid
from collections import deque
class MockMessageBroker:
def __init__(self):
self.queue = deque()
self.acked = set()
def publish(self, payload: str) -> str:
msg_id = str(uuid.uuid4())
self.queue.append((msg_id, payload))
return msg_id
def po…Implement a retry queue with visibility timeout in Python
This code simulates a message queue with a visibility timeout, allowing messages to be retried if not deleted before the timeout expires.
import time
from collections import deque
class SimpleQueue:
def __init__(self, visibility_timeout=2):
self.queue = deque()
self.in_flight = {}
self.visibility_timeout = visibility_timeout
def send(self, message):
self.queue.append(message)
def receive(self):
if …How to Cap Retry Attempts in Python with a Decorator
Build a reusable retry decorator that caps attempts, adds delays, and lets flaky services fail fast instead of hanging.
import random
from functools import wraps
from time import sleep
def retry(max_attempts, delay=0.1):
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
attempts = 0
while attempts < max_attempts:
try:
return func(*args, **kw…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 Simulate an Outbox Pattern with Reliable Retry in Python
This code implements a mock outbox pattern with records, delivery attempts, and retries to simulate reliable message publishing.
import time
import itertools
class Outbox:
def __init__(self):
self._records = []
self._seq = itertools.count(1)
def publish(self, topic, payload):
record = {
"id": next(self._seq),
"topic": topic,
"payload": payload,
"status": "pending"…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_…Retry with Exponential Backoff and Jitter in Python
A decorator-style retry wrapper that retries a flaky function with exponential backoff plus random jitter, then raises after the last attempt fails.
import random
import time
def retry_with_backoff(func, max_retries=3, base_delay=0.5, max_jitter=0.1):
for attempt in range(max_retries + 1):
try:
return func()
except Exception as e:
if attempt == max_retries:
raise
delay = base_delay * (2 ** at…How to Build a GitOps Argo CD Sync Mock in Python
Simulate Argo CD-style GitOps deployment sync with Python dataclasses, random success rates, and force-sync retry logic.
import random
import time
from dataclasses import dataclass, field
from typing import List, Dict
@dataclass
class Application:
name: str
source_repo: str
target_revision: str
synced: bool = False
health_status: str = "Healthy"
history: List[Dict] = field(default_factory=list)
def sync(se…Browse by section
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