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Python Code Samples

Easy snippets you can copy, study, and run in the browser editor.

249 matches
Caching & Redis easy

How to cache filtered data in Redis with Python

This code caches filtered list results in Redis using an MD5 hash key, returning cached results when available.

redis caching filtering
Python
import redis
import json
import hashlib
import time

cache = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)

def filter_data(data, predicate_key, predicate_value):
    """Filter a list of dicts by key-value pair, with Redis caching."""
    cache_key = hashlib.md5(
        f"{predicate_key}:{pred…
14 0 Open
Reliability & rate limiting easy

Chaos Inject Random Failures in Python

Simulate random failures in a Python function to test error handling and resilience, using random thresholds and controllable success rates.

chaos-engineering random resilience
Python
import random


def unreliable_function(success_rate: float = 0.7) -> str:
    """Simulate a function that sometimes fails."""
    if random.random() > success_rate:
        raise ConnectionError("Simulated network failure")
    return "Operation completed successfully"


if __name__ == "__main__":
    random.seed(42)…
16 0 Open
Reliability & rate limiting easy

Health Check Mark Unhealthy Stop Traffic Mock in Python

Simulates a health check with a 20% failure rate and automatically stops traffic when the service is unhealthy.

health-check reliability traffic-management
Python
import time
import random

class HealthCheck:
    def __init__(self):
        self.is_healthy = True
        self.stop_traffic = False

    def check_health(self):
        # Simulate health check with random failure rate (20% chance unhealthy)
        self.is_healthy = random.random() > 0.2
        return self.is_heal…
14 0 Open
Reliability & rate limiting easy

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.

dead-letter-queue queue retry
Python
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,
           …
15 0 Open
Reliability & rate limiting easy

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.

rate-limiting penalty-box lockout
Python
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…
15 0 Open
Reliability & rate limiting easy

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.

quota rate-limiting class
Python
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…
18 0 Open
Reliability & rate limiting easy

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.

fault-injection random testing
Python
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):
     …
14 0 Open
Reliability & rate limiting easy

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.

retry decorator exceptions
Python
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)
          …
16 0 Open
Reliability & rate limiting easy

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.

readiness fail-stop mock-server
Python
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…
14 0 Open
Reliability & rate limiting easy

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.

unittest mocking requests
Python
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:
…
16 0 Open
Reliability & rate limiting easy

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.

cache fallback resilience
Python
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 …
15 0 Open
Observability & SRE easy

Check if a Timestamp Falls in a Daily Maintenance Window in Python

A small Python function that returns True when a datetime falls inside a daily maintenance window, and a demo printing yes/no for sample timestamps.

maintenance datetime scheduling
Python
from datetime import datetime, timedelta
from zoneinfo import ZoneInfo


def in_maintenance_window(now: datetime, start_hour: int = 2, duration_hours: int = 4) -> bool:
    """Return True if 'now' falls inside the daily maintenance window."""
    day_start = now.replace(hour=start_hour, minute=0, second=0, microsecond…
19 0 Open
Observability & SRE easy

Generate Synthetic SRE Metrics and Calculate Availability in Python

Create realistic service metrics with random latency, error rate, and request counts, then compute availability and summarize the stream for SLO checks.

sre synthetic-data metrics
Python
from datetime import datetime, timedelta
import random

def generate_service_metrics(service_name: str, minutes: int = 30) -> list[dict]:
    """Generate synthetic SRE metrics for a service across recent minutes."""
    metrics = []
    now = datetime.now()
    
    for i in range(minutes):
        timestamp = now - t…
15 0 Open
Observability & SRE easy

How to Calculate SLO Error Budget in Python

Simulate an SLO error budget by computing allowed downtime from a target availability percentage and mocking monthly incidents.

slo error-budget monitoring
Python
```python
import random


def calculate_error_budget(total_seconds: int, target_availability: float) -> float:
    return (1.0 - target_availability) * total_seconds


def simulate_monthly_availability(seconds_in_month: int, budget_seconds: float) -> float:
    # Mock: randomly consume a fraction of the error budget i…
16 0 Open
Observability & SRE easy

How to Check Service Readiness Dependencies in Python

This code simulates a readiness check for external dependencies (database, cache, queue) with mock availability data and reports readiness status.

readiness dependencies health-check
Python
import sys
from datetime import datetime


def check_dependencies(config):
    results = []
    for dep, required in config.items():
        available = mock_availability(dep)
        status = "READY" if available >= required else "NOT READY"
        results.append((dep, available, required, status))
    return result…
12 0 Open
Observability & SRE easy

How to Compute SRE Metrics Like Error Rate and Availability in Python

Tracks log events in a sliding time window and calculates error rate per second and availability percentage using an easy-to-follow class.

observability sre metrics
Python
from collections import deque
from datetime import datetime, timedelta
from typing import Dict, Deque


class LogMetrics:
    """Simple observability helper to track log events and calculate SRE metrics."""

    def __init__(self, window_seconds: int = 60):
        self.window_seconds = window_seconds
        self.eve…
15 0 Open
Observability & SRE easy

How to Implement Tail Sampling in Python

Sample the slowest subset of calls (tail) for latency analysis using a deque with a random ratio gate.

sampling latency observability
Python
import random
import time
from collections import deque

class TailSampler:
    def __init__(self, tail_ratio=0.1, max_samples=100):
        self.tail_ratio = tail_ratio
        self.max_samples = max_samples
        self.samples = deque(maxlen=max_samples)
        self.total_calls = 0

    def record(self, latency_ms…
14 0 Open
Observability & SRE easy

How to Route Alerts by Severity in Python

Map alert severity levels to routing targets and simulate dispatching alerts to on-call pages, email, Slack, or logs.

observability alerts routing
Python
def main():
    # Severity levels with corresponding alert routing targets
    routing_map = {
        "critical": "call_page",
        "high": "call_page",
        "medium": "email_team",
        "low": "slack_channel",
        "info": "log_only"
    }

    # Simulated alerts with severity
    alerts = [
        {"na…
13 0 Open
Observability & SRE easy

How to mock SLI availability success ratio in Python

Simulate request outcomes with deterministic randomness and compute the SLI availability success ratio to check if a target is met.

sli availability monitoring
Python
import random
from collections import defaultdict

def mock_availability(num_requests=1000, target_ratio=0.995):
    """
    Simulate request outcomes and compute the SLI availability success ratio.
    
    Args:
        num_requests: Total number of requests to simulate
        target_ratio: Target availability rati…
14 0 Open
Observability & SRE easy

Mock Health Endpoint Liveness Check in Python

Simulate a liveness endpoint that reports service health with a configurable failure rate and uptime.

health check mock observability
Python
import time
import random


def liveness_check(service_name: str, failure_rate: float = 0.1) -> dict:
    """Mock health check that returns liveness status with a configurable failure rate."""
    healthy = random.random() > failure_rate
    response = {
        "service": service_name,
        "status": "alive" if he…
18 0 Open
Microservices patterns easy

How to Implement an Outbox Pattern Mock in Python

This code demonstrates a simple in-memory outbox pattern mock for publishing domain events and tracking pending events until they are marked as published.

outbox domain-events microservices
Python
from dataclasses import dataclass, field
from datetime import datetime
from uuid import uuid4


@dataclass
class DomainEvent:
    event_id: str = field(default_factory=lambda: str(uuid4()))
    occurred_at: datetime = field(default_factory=datetime.utcnow)


class Outbox:
    def __init__(self):
        self._events =…
14 0 Open
Microservices patterns easy

How to Mock a GraphQL Backend in Python

Create an in-memory GraphQL mock backend using dataclasses and resolver methods returning plain dictionaries.

graphql mock dataclasses
Python
from dataclasses import dataclass, asdict
from typing import Any, Dict, List


@dataclass
class Product:
    id: int
    name: str
    price: float


@dataclass
class User:
    id: int
    username: str


class MockGraphQLBackend:
    def __init__(self) -> None:
        self.products = [
            Product(id=1, name…
16 0 Open
Microservices patterns easy

How to mock a SPIFFE workload identity in Python

Generate a mock SPIFFE ID and token for a workload using a trust domain, namespace, and service account.

spiffe identity microservices
Python
import hashlib
import json
from dataclasses import dataclass, asdict


@dataclass
class SPIFFEIdentity:
    trust_domain: str
    namespace: str
    service_account: str

    @property
    def id(self) -> str:
        return f"spiffe://{self.trust_domain}/ns/{self.namespace}/sa/{self.service_account}"


def mock_workl…
14 0 Open
Microservices patterns easy

Retry idempotent GET requests in Python

A Python function that retries an idempotent GET request a fixed number of times with a delay between attempts, raising a RuntimeError only after all retries fail.

retry idempotent urllib
Python
import time
import urllib.error
import urllib.request
from http.client import HTTPException

def fetch_with_retry(url, max_retries=3, delay=1.0):
    for attempt in range(1, max_retries + 1):
        try:
            with urllib.request.urlopen(url, timeout=5) as response:
                return response.read().decode…
15 0 Open

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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.