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Route Messages to Handlers with a Python Dict
This code demonstrates a simple message routing pattern using a dictionary to map topic keys to handler functions, with a default handler for unmatched topics.
def route_message(message, routing_table):
"""Route a message to the correct handler based on the topic key."""
topic = message.get("topic", "default")
handler = routing_table.get(topic, routing_table.get("default"))
return handler(message)
def handle_orders(message):
return f"Orders handler proc…How to Build a Simple Data Helper in Python for API Design
Create a beginner-friendly DataHelper class that demonstrates basic CRUD operations (add, get, list, remove) using an in-memory dictionary, ideal for learning API design concepts.
class DataHelper:
"""Simple data helper for beginners learning API design concepts."""
def __init__(self):
self._data = {}
def add_record(self, key, value):
"""Add a record to the store."""
self._data[key] = value
return f"Added: {key} -> {value}"
def get_…How to Validate JWT Claims (exp, iss, aud) in Python
This code demonstrates how to decode and validate a JWT's essential claims—expiration (exp), issuer (iss), and audience (aud)—using the PyJWT library, returning clear error messages for common validation failures.
import jwt
from datetime import datetime, timezone, timedelta
SECRET = "mock-secret"
def validate_token(token, expected_iss, expected_aud):
try:
decoded = jwt.decode(
token,
SECRET,
algorithms=["HS256"],
options={"require": ["exp", "iss", "aud"]},
…How to mock RabbitMQ queue binding with routing keys in Python
A mock demonstration of binding a queue to an exchange with multiple routing keys in RabbitMQ using Python and pika, without a real broker connection.
import pika
import sys
def bind_queue_with_routing(channel, queue_name, exchange_name, routing_keys):
"""
Mock RabbitMQ queue binding with routing keys.
Prints the binding configuration instead of connecting to a real broker.
"""
for routing_key in routing_keys:
binding = {
"q…Using the retained message flag in MQTT with Python
This script subscribes to an MQTT topic and prints the retained flag for each received message, demonstrating how to distinguish retained messages from normal ones.
import paho.mqtt.client as mqtt
def on_connect(client, userdata, flags, rc):
print(f"Connected with result code {rc}")
# Subscribe to a topic and check retained flag
client.subscribe("test/retained")
print("Subscribed to test/retained")
def on_message(client, userdata, msg):
# msg.retain is the M…Cache Warming with Python: Preload Hot Keys
Demonstrates a simple LRU-like cache with a warm method that preloads hot keys with mock values using OrderedDict.
import time
from collections import OrderedDict
class CacheWarm:
def __init__(self, capacity=3):
self.capacity = capacity
self.cache = OrderedDict()
self.hot_keys = []
def warm(self, keys):
"""Preload hot keys into cache with mock values."""
for key in keys:
…How to Invalidate a Cache in Python with lru_cache
This code demonstrates how to clear the cache of an @lru_cache decorated function in Python using cache_clear(), showing the effect on cached results.
from functools import lru_cache
import time
@lru_cache(maxsize=None)
def expensive_operation(key):
return f"Computed value for {key} at {time.time():.6f}"
def invalidate_cache():
expensive_operation.cache_clear()
if __name__ == "__main__":
print(expensive_operation("alpha"))
print(expensive_operatio…How to Use Redis HSET and HGET in Python
This code demonstrates how to store and retrieve hash data in Redis using Python's redis library with HSET, HGET, HGETALL, and HDEL commands.
import redis
# Connect to Redis (adjust host/port as needed)
r = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
# Clear any existing data for demonstration
r.delete('user:1')
# HSET - Store a hash
r.hset('user:1', mapping={'name': 'Alice', 'age': 30, 'city': 'New York'})
# HGET - Retrieve a …How to Use lru_cache in Python for Cache-on-Miss Population
Demonstrates lru_cache to automatically populate cache on a miss and serve subsequent calls from cache, with cache info stats.
from functools import lru_cache
@lru_cache(maxsize=None)
def fetch_user(user_id):
"""Simulates a slow database fetch."""
print(f"Cache miss: fetching user {user_id} from database")
return {"id": user_id, "name": f"User {user_id}"}
if __name__ == "__main__":
user = fetch_user(1)
print(f"First call…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.
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 …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.
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…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.
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…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.
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…How to Use Log Levels DEBUG INFO WARNING ERROR in Python
Demonstrates Python's logging levels (DEBUG, INFO, WARNING, ERROR) with basicConfig and a logger, showing how severity filtering controls output.
import logging
# Configure a mock logger to demonstrate log levels
logging.basicConfig(level=logging.DEBUG, format="%(levelname)s: %(message)s")
logger = logging.getLogger("mock_logger")
# Simulate events at each severity level
logger.debug("Detailed diagnostic info")
logger.info("General system operation")
logger.w…Mocking a Metrics Gauge's set_value Method in Python
Demonstrates using unittest.mock.Mock with wraps to intercept a gauge's set_value call while verifying arguments and preserving real behavior.
from unittest.mock import Mock
class MetricsGauge:
def __init__(self, name):
self.name = name
self.value = 0.0
def set_value(self, new_value):
self.value = float(new_value)
return self.value
# Usage demonstration with a mock
gauge = MetricsGauge("cpu_usage")
gauge_mock = Mock…How to Demonstrate the Shared Database Antipattern in Python
This code simulates a shared database where multiple services write and read the same SQLite table, illustrating tight coupling and its pitfalls.
import sqlite3
from pathlib import Path
def create_shared_db(db_path: Path) -> None:
"""Mock demonstrating the shared database antipattern where multiple
services access the same database, causing tight coupling."""
conn = sqlite3.connect(db_path)
cur = conn.cursor()
cur.execute("""
CREATE…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.
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 =…How to Use the Adapter Pattern to Mock a Legacy System in Python
This code demonstrates the Adapter pattern, allowing a modern interface to interact with a legacy system by wrapping its outdated method.
class LegacySystem:
def legacy_method(self, data):
return f"Legacy processed: {data}"
class ModernInterface:
def process(self, data):
raise NotImplementedError
class Adapter(ModernInterface):
def __init__(self, legacy):
self.legacy = legacy
def process(self, data):
re…How to Explode an Array Column in Python
This code demonstrates a mock explode operation that converts an array column into multiple rows, similar to Spark's explode function.
import json
def explode_array_column(data, column):
"""Mock explode: split array column into multiple rows."""
exploded = []
for row in data:
values = row.get(column, [])
for value in values:
new_row = dict(row)
new_row[column] = value
exploded.append(n…How to Mock Hive Support in PySpark with unittest.mock
This code demonstrates how to mock Hive support in a PySpark environment using unittest.mock to simulate SQL queries returning fixed data.
from unittest.mock import Mock, patch
def get_hive_tables(spark):
"""Mock Hive support by returning a fixed list of tables."""
return spark.sql("SHOW TABLES").collect()
class HiveTable:
"""Simple class that mimics a Hive table row."""
def __init__(self, database, tableName):
self.database =…Z-Order Optimization in Python
A mock concept demonstrating z-order layout optimization by reassigning z-indices based on areas size.
class ZOrderLayout:
"""
Minimal mock for z-order layout optimization using a stacking score.
Elements overlap; higher z_index is drawn on top.
"""
def __init__(self):
self.elements = []
def add_element(self, name, area, z_index):
self.elements.append({"name": name, "area": area…How to Save and Load PyTorch Model State Dict in Python
This code demonstrates how to save a PyTorch model's state dict to a file and load it back into a new model instance, verifying weights match.
import torch
import torch.nn as nn
class SimpleNet(nn.Module):
def __init__(self):
super().__init__()
self.fc1 = nn.Linear(4, 8)
self.fc2 = nn.Linear(8, 2)
def forward(self, x):
x = torch.relu(self.fc1(x))
return self.fc2(x)
if __name__ == "__main__":
model = Simp…How to do feature selection with VarianceThreshold in Python
This code demonstrates how to use scikit-learn's VarianceThreshold to remove low-variance features from a NumPy array, keeping only those that vary enough to be useful for modeling.
import numpy as np
from sklearn.feature_selection import VarianceThreshold
def main():
# Mock dataset: 4 samples, 5 features
X = np.array([
[0.1, 0.2, 1.0, 1.0, 0.5],
[0.2, 0.2, 0.0, 1.0, 0.4],
[0.1, 0.2, 1.0, 1.0, 0.6],
[0.3, 0.2, 1.0, 0.0, 0.5]
])
# Select features w…Hash index equality mock concept in Python
A simple hash index class in Python that stores key-value pairs in buckets and demonstrates basic equality-based lookup.
class HashIndex:
def __init__(self):
self._buckets = {}
def insert(self, key, value):
"""Insert a key-value pair into the hash index."""
index = hash(key) % 10
if index not in self._buckets:
self._buckets[index] = []
self._buckets[index].append((key, value))…Browse by section
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