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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

432 matches
Streaming & messaging easy

How to Mock Kafka Topic Partitions with a Python dict of lists

Mocks a Kafka topic and its partitions using a defaultdict of lists to simulate message production, consumption, and per-partition counts.

kafka mock partitions
Python
from collections import defaultdict

class KafkaTopicPartitionMock:
    """A simple mock for Kafka topic-partition assignment using dict of lists."""

    def __init__(self, topic):
        self.topic = topic
        self.partitions = defaultdict(list)  # partition_id -> list of messages

    def produce(self, message…
16 0 Open
Streaming & messaging medium

How to Mock a Kafka Rebalance Listener in Python

Simulate Kafka consumer rebalance callbacks (on_partitions_revoked and on_partitions_assigned) with a mock consumer to test listener logic.

kafka rebalance mocking
Python
import time
from collections import defaultdict


class MockKafkaConsumer:
    def __init__(self):
        self.assignments = defaultdict(list)
        self.rebalances = 0

    def assign(self, partitions):
        self.rebalances += 1
        self.assignments.clear()
        for partition in partitions:
            s…
16 0 Open
Streaming & messaging medium

Implement the Transactional Outbox Pattern with SQLite in Python

A Python implementation of the transactional outbox pattern using SQLite, ensuring atomic writes of order data and outbox events in a single transaction while supporting reliable message publishing and consumption.

outbox-pattern sqlite transactions
Python
import sqlite3
from dataclasses import dataclass
from datetime import datetime, timezone
import json

@dataclass
class Order:
    order_id: str
    amount: float
    status: str

class TransactionalOutbox:
    def __init__(self, db_path=":memory:"):
        self.conn = sqlite3.connect(db_path)
        self._create_tab…
23 0 Open
Streaming & messaging medium

In-Memory PubSub Topic Subscribe Mock in Python

Build a thread-safe in-memory publish/subscribe mock where handlers subscribe to named topics and receive every message published to them.

pubsub mock events
Python
class PubSub:
    def __init__(self):
        self.topics = {}

    def subscribe(self, topic, callback):
        if topic not in self.topics:
            self.topics[topic] = []
        self.topics[topic].append(callback)

    def publish(self, topic, message):
        for callback in self.topics.get(topic, []):
    …
17 0 Open
Streaming & messaging easy

Redis Pub/Sub Channel Subscribe Mock in Python

A lightweight in-memory mock of Redis pub/sub that lets you subscribe to channels, publish messages, and verify handler behavior in tests without a real Redis server.

redis pubsub testing
Python
class MockRedisPubSub:
    def __init__(self):
        self.channels = {}

    def subscribe(self, channel):
        if channel not in self.channels:
            self.channels[channel] = []
        return self.channels[channel]

    def publish(self, channel, message):
        if channel in self.channels:
            …
12 0 Open
Caching & Redis medium

How to Build a Bloom Filter to Reduce Cache Misses in Python

Implement a probabilistic Bloom filter in Python that lets a cache quickly determine which keys are definitely not present, reducing expensive source lookups on cache misses.

bloom-filter caching probabilistic
Python
import hashlib
import random

class BloomFilter:
    def __init__(self, size=100, num_hashes=3):
        self.size = size
        self.num_hashes = num_hashes
        self.bit_array = [0] * size

    def _hashes(self, item):
        result = []
        for i in range(self.num_hashes):
            hash_value = int(hash…
15 0 Open
Caching & Redis medium

How to Implement Probabilistic Early Expiration in Python

A Python mock of probabilistic early expiration for caches, using a heap-based expiry queue and random eviction to approximate cache stampede protection.

caching expiration heap
Python
import heapq
import random
import time


class ProbabilisticEarlyExpirationMock:
    def __init__(self, capacity=1024, expiration_probability=0.1):
        self.capacity = capacity
        self.expiration_probability = expiration_probability
        self._items = {}
        self._expiry_heap = []
        self._next_id…
15 0 Open
Caching & Redis medium

How to Mock Redis Pub/Sub in Python

Test Redis pub/sub logic without a live server using an in-memory fake that queues published messages per channel.

redis pubsub testing
Python
import redis
import time
import threading


class MockRedisPubSub:
    def __init__(self):
        self.channels = {}

    def publish(self, channel, message):
        if channel not in self.channels:
            return 0
        for subscriber in self.channels[channel]:
            subscriber.put(message)
        ret…
14 0 Open
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
Caching & Redis easy

Redis LPUSH RPOP List Queue Mock in Python

Implements a FIFO queue using Redis lists with LPUSH and RPOP commands, simulating task processing in Python.

redis queue fifo
Python
import redis
import time

r = redis.Redis(host='localhost', port=6379, db=0)
queue_key = 'task_queue'

# Push tasks onto the left side (LPUSH)
r.lpush(queue_key, 'task1')
r.lpush(queue_key, 'task2')
r.lpush(queue_key, 'task3')

# Mock processing: pop from the right side (RPOP) — FIFO order
while r.llen(queue_key) > 0:…
14 0 Open
Reliability & rate limiting easy

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.

rate-limiting time sliding-window
Python
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…
15 0 Open
Reliability & rate limiting medium

How to Implement a Token Bucket Rate Limiter per Client IP in Python

Implements a simple sliding-window rate limiter using a dictionary of timestamp lists per client IP to limit requests per window.

rate-limiting sliding-window ip
Python
from time import time
from collections import defaultdict

class RateLimiter:
    def __init__(self, max_requests: int, window_seconds: int):
        self.max_requests = max_requests
        self.window_seconds = window_seconds
        self.clients = defaultdict(list)

    def allow(self, ip: str) -> bool:
        now…
14 0 Open
Reliability & rate limiting medium

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.

outbox retry messaging
Python
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"…
15 0 Open
Observability & SRE easy

Generate Mock CPU and Memory Metrics in Python

Build a mock_host_metrics() generator that outputs realistic CPU and memory usage percentages for monitoring demos and tests.

mock metrics monitoring
Python
import time
import random


def mock_host_metrics():
    """Generate mock CPU and memory metrics for a host."""
    cpu_percent = round(random.uniform(10.0, 95.0), 1)
    memory_percent = round(random.uniform(20.0, 90.0), 1)
    memory_used_mb = round(random.uniform(512, 8192), 1)

    return {
        "timestamp": in…
20 0 Open
Observability & SRE easy

Generate Synthetic CPU Utilization Metrics in Python

Creates realistic time-series CPU utilization samples with timestamps, noise, and output as structured JSON for observability demos and testing.

observability metrics time-series
Python
from datetime import datetime, timedelta
import random
import json


def generate_metric_samples(base_value, noise, count=60, interval_minutes=1):
    """Generate realistic CPU utilization samples for a given time window."""
    timestamps = []
    values = []

    now = datetime.utcnow()
    start_time = now - timede…
15 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 Percentile Latency in Python

Generate mock latency samples with occasional spikes and compute 50th, 90th, 95th, and 99th percentile values in milliseconds.

percentile latency slo
Python
import random
import statistics

def generate_latency_samples(n=1000):
    """Generate realistic mock latency data (ms) with occasional spikes."""
    samples = []
    for _ in range(n):
        # Normal case: ~50ms with jitter
        base = random.gauss(50, 5)
        # 2% spike chance: slow downstream or GC pause
 …
15 0 Open
Observability & SRE medium

How to Create a TCP DNS Mock Server in Python

This code creates a mock TCP DNS server that listens on a specified port, accepts probe connections, and returns a fixed DNS response header to simulate a live DNS service for testing and observability.

socket dns tcp
Python
import socket
import threading


def handle_client(client_socket, address):
    print(f"[+] Connection from {address}")
    try:
        while True:
            data = client_socket.recv(1024)
            if not data:
                break
            print(f"[*] Received {len(data)} bytes (TCP DNS probe)")
          …
19 0 Open
Observability & SRE easy

How to Mock Database Query Duration in Python

Simulate realistic database query durations with random jitter for testing dashboards, alerts, and SLO calculations.

observability mock metrics
Python
import random
import time


def mock_query_duration(db_name, avg_ms, jitter_ms=5, runs=3):
    """Simulate database query durations with realistic variation."""
    durations = []
    for _ in range(runs):
        # Base duration plus random jitter (can be negative)
        duration = avg_ms + random.uniform(-jitter_m…
15 0 Open
Observability & SRE easy

How to Simulate Trace Sampling Head in Python

Simulate head-based probabilistic trace sampling on mock trace data with a configurable sample rate and optional seed for reproducibility.

tracing sampling observability
Python
import random

def trace_sampling_head(mock_traces, sample_rate=0.5, seed=None):
    """Simulate probabilistic trace sampling (head-based) on mock data.
    
    Args:
        mock_traces: list of trace dictionaries with a unique 'trace_id'
        sample_rate: float 0.0-1.0, probability of keeping a trace
        see…
13 0 Open
Microservices patterns easy

Event Sourcing Store in Python: Append-Only Log Mock

Mock an append-only event store in Python — record events, list them, and fetch by ID using a simple list-backed class.

event-sourcing microservices mock
Python
class EventStore:
    def __init__(self):
        self._events = []

    def append(self, event):
        event_id = len(self._events) + 1
        stored_event = {"id": event_id, "data": event}
        self._events.append(stored_event)
        return stored_event

    def get_events(self):
        return list(self._ev…
14 0 Open
Microservices patterns easy

How to Build a Health Check Service Registry in Python

Build a minimal Python service registry that handles registration, deregistration, health checks, and service listing in one simple class.

microservices health-check service-discovery
Python
import random
import time


class ServiceRegistry:
    def __init__(self):
        self.services = {}

    def register(self, name, address):
        self.services[name] = {
            "address": address,
            "status": "healthy",
            "registered_at": time.time(),
            "checks": 0
        }
    …
15 0 Open
Microservices patterns easy

How to Build an In-Memory Service Registry Mock in Python

A simple in-memory ServiceRegistry class to register, retrieve, list, and unregister microservice endpoints or configs using a dict, with KeyError guards.

service-registry microservices in-memory
Python
class ServiceRegistry:
    def __init__(self):
        self._services = {}

    def register(self, name, service):
        self._services[name] = service

    def unregister(self, name):
        if name not in self._services:
            raise KeyError(f"Service '{name}' not found")
        del self._services[name]

 …
15 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 =…
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.