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How to memoize a function in Python with lru_cache
Use functools.lru_cache to memoize a recursive Fibonacci function, caching results for a fixed number of calls to avoid repeated computation.
from functools import lru_cache
@lru_cache(maxsize=128)
def fibonacci(n):
if n < 2:
return n
return fibonacci(n - 1) + fibonacci(n - 2)
if __name__ == "__main__":
for i in range(10):
print(f"fib({i}) = {fibonacci(i)}")
print(f"Cache info: {fibonacci.cache_info()}")
How to use Redis MGET MSET pipeline in Python
Store multiple keys atomically and read them efficiently with Redis MSET/MGET, then batch commands with a pipeline to cut round trips.
import redis # v4.x+ required
r = redis.Redis(host="localhost", port=6379, db=0, decode_responses=True)
# Sample data to store
r.flushdb()
data = {"name": "Alice", "age": "30", "city": "Berlin"}
# MSET: store multiple key-value pairs in one command
r.mset(data)
# MGET: fetch multiple keys in one round trip
keys =…
How to Build a Rate Limiter in Python
A beginner-friendly token bucket rate limiter with retry logic for handling API rate limits in Python.
import time
import random
class RateLimiter:
"""Simple token bucket rate limiter for beginners."""
def __init__(self, max_tokens=5, refill_rate=1.0):
self.max_tokens = max_tokens
self.tokens = max_tokens
self.refill_rate = refill_rate # tokens per second
self.last_refill …
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 Deduplicate Messages in Python by ID
This code consumes a mock inbox of JSON messages and deduplicates them by message ID, keeping either the first or last occurrence.
import json
from collections import OrderedDict
mock_inbox = [
{"id": 1, "message": "hello", "timestamp": "2024-01-01T10:00:00Z"},
{"id": 2, "message": "world", "timestamp": "2024-01-01T10:01:00Z"},
{"id": 1, "message": "hello", "timestamp": "2024-01-01T10:00:00Z"},
{"id": 3, "message": "test", "times…
How to Implement Message Visibility Timeout Renewal in Python
Simulate queue message visibility control with timeout renewal using a simple Python class that tracks received time and visibility state.
import time
import uuid
class Message:
def __init__(self, body, visibility_timeout=30):
self.body = body
self.visibility_timeout = visibility_timeout
self.receipt_handle = str(uuid.uuid4())
self.received_at = time.time()
self.deleted = False
def is_visible(self):
…
How to Implement a Dead Letter Queue Replay in Python
A mock Dead Letter Queue that stores failed messages with retry attempts and replays them with a simple retry counter.
import json
from collections import deque
class DeadLetterQueue:
def __init__(self):
self.messages = deque()
def add_message(self, message_id, payload, attempts=3):
"""Add a message to the DLQ with retry metadata."""
self.messages.append({
"id": message_id,
…
How to Implement a Rate Limiter in Python
A beginner-friendly Python class that tracks call timestamps with a deque to allow or block calls based on a max rate per time period.
import time
from collections import deque
class RateLimiter:
"""Simple rate limiter for beginners."""
def __init__(self, max_calls: int, period_seconds: float):
self.max_calls = max_calls
self.period = period_seconds
self.calls = deque()
def allow(self) -> bool:
"""Retur…
How to Implement a Sliding Window Counter in Python
This code implements an approximate sliding window counter using a deque of time-based buckets to track event counts within a recent time window.
from collections import deque
from time import time
class SlidingWindowCounter:
def __init__(self, window_size, bucket_size=1):
self.window_size = window_size
self.bucket_size = bucket_size
self.buckets = deque()
def _evict_expired(self, now):
while self.buckets and self.buck…
How to Implement a Temporary Block in Python
Build a reusable PenaltyBox class that temporarily blocks access after a failure and reports remaining lockout time.
class PenaltyBox:
def __init__(self, block_seconds: int = 30):
self.block_seconds = block_seconds
self._blocked_until = 0.0
self._attempts = 0
def try_access(self, current_time: float) -> bool:
if self._blocked_until and current_time < self._blocked_until:
return Fa…
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 Daily and Monthly Quota Counters in Python
Track daily and monthly API call usage with automatic resets, quota checks, and limits using a Python class.
import random
from datetime import datetime, timedelta
class QuotaCounter:
def __init__(self, daily_limit=1000, monthly_limit=20000):
self.daily_limit = daily_limit
self.monthly_limit = monthly_limit
self.daily_usage = 0
self.monthly_usage = 0
self.current_day = datetime.n…
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 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 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 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 Retry on Specific Exception Tuples in Python
A decorator-based retry pattern that retries a function only when it raises exceptions specified in a tuple, with configurable retries and delay.
import time
import random
from unittest.mock import patch
def retry_on_exceptions(retries=3, exceptions=(ValueError,), delay=0.1):
def decorator(func):
def wrapper(*args, **kwargs):
for attempt in range(retries):
try:
return func(*args, **kwargs)
…
How to Stop Receiving Requests Until Ready in Python
A mock server that refuses requests until a readiness gate is passed, simulating fail-stop behavior for production reliability.
import random
import time
class MockServer:
def __init__(self):
self.ready = False
self.requests_received = 0
def readiness_check(self):
"""Simulates a readiness probe. Returns True only when ready."""
if not self.ready:
return False
return True
def r…
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 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:
…
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…
How to Add Metadata Attributes to a Span in Python
Create a lightweight dataclass-based Span mock that stores key-value metadata attributes for tracing or event logging.
from dataclasses import dataclass, field
from typing import Dict, Any
@dataclass
class Span:
name: str
attributes: Dict[str, Any] = field(default_factory=dict)
def set_attribute(self, key: str, value: Any) -> None:
self.attributes[key] = value
def get_attribute(self, key: str) -> Any…
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