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How to Use Union Type Hints in Python
This code demonstrates how to use Union type hints to specify that a parameter can accept multiple types (int, float, str) and handle them accordingly.
from typing import Union
def process_value(value: Union[int, float, str]) -> str:
if isinstance(value, (int, float)):
return f"Number: {value * 2}"
return f"String: {value.upper()}"
if __name__ == "__main__":
print(process_value(10))
print(process_value(3.14))
print(process_value("hello"))Mock datetime with time-machine in Python
Use the time-machine library to travel to a fixed datetime when running tests or scripts, mocking datetime.utcnow().
from time_machine import travel
from datetime import datetime
@travel("2020-01-01 10:30:00")
def check_date():
return datetime.utcnow()
if __name__ == "__main__":
print(check_date())Idempotent Consumer: Store Processed IDs in Python
Implement an idempotent consumer that persists processed message IDs to a JSON file, skipping duplicates on restart.
import json
from pathlib import Path
class IdempotentStore:
def __init__(self, storage_path: str = "processed_ids.json"):
self.storage_path = Path(storage_path)
self.processed_ids = self._load()
def _load(self) -> set:
if self.storage_path.exists():
with self.storage_path…Generate an OpenAPI Spec from Mock Routes in Python
This Python script generates an OpenAPI 3.0 specification from a simple mock routes dictionary, mapping each HTTP method to response examples.
import json
from pathlib import Path
def generate_openapi_spec(routes: dict, title: str = "Mock API", version: str = "1.0.0") -> dict:
paths = {}
for route, methods in routes.items():
path_item = {}
for method, response_data in methods.items():
method = method.lower()
…Dead Letter Queue Failed Messages List Mock in Python
Implements a simple in-memory dead letter queue to collect, list, and retry failed messages, with JSON serialization for inspection in streaming pipelines.
import json
from collections import deque
class Message:
def __init__(self, message_id, payload, attempts=0):
self.message_id = message_id
self.payload = payload
self.attempts = attempts
def __repr__(self):
return f"Message(id={self.message_id}, attempts={self.attempts})"
c…How to Build a Mock Change Data Capture Event Stream in Python
Generate a deterministic list of mock CDC events with event IDs, stream positions, payloads, and timestamps for testing streaming pipelines.
from itertools import count
from random import choice, randint, seed
from datetime import datetime, timedelta
seed(42) # Make output deterministic
event_types = ["INSERT", "UPDATE", "DELETE"]
table_names = ["users", "orders", "products", "payments"]
counter = count(1)
def mock_cdc_event(stream_index: int) -> dict:
…How to Implement Publish-Subscribe Fanout with Multiple Subscribers in Python
Create a simple publish-subscribe system in Python that broadcasts messages to multiple subscriber callbacks for a given topic.
import time
class PubSub:
def __init__(self):
self.subscribers = {}
def subscribe(self, topic, callback):
if topic not in self.subscribers:
self.subscribers[topic] = []
self.subscribers[topic].append(callback)
def publish(self, topic, message):
if topic in sel…How to Mock MQTT Topic Subscriptions with QoS in Python
Build a lightweight MQTT client mock that tracks topic subscriptions with QoS levels and simulates wildcard message delivery.
import time
from collections import defaultdict
class MockMQTTClient:
def __init__(self):
self.subscriptions = defaultdict(list)
self.messages = []
def subscribe(self, topic, qos=0):
self.subscriptions[topic].append(qos)
print(f"Subscribed to '{topic}' with QoS {qos}")
…How to deduplicate messages by ID in Python
Track seen message IDs in a set to skip duplicate messages and store unique content in a dict, with exact output showing which messages were added or skipped.
import time
class MessageStore:
def __init__(self):
self.seen_ids = set()
self.messages = {}
def add(self, message_id, content, timestamp=None):
timestamp = timestamp or time.time()
if message_id in self.seen_ids:
return False
self.seen_ids.add(message_…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…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 Ship Logs to an Aggregator Endpoint in Python
Ship batched log entries to a mock HTTP aggregator endpoint with proper error handling and response status.
import json
import requests
from datetime import datetime, timezone
LOG_ENTRIES = [
{"timestamp": "2024-01-15T10:00:00Z", "level": "INFO", "message": "Server started"},
{"timestamp": "2024-01-15T10:00:05Z", "level": "WARN", "message": "High memory usage"},
{"timestamp": "2024-01-15T10:00:10Z", "level": "E…Rotate Log Files by Size in Python
A mock log rotation script that renames log files exceeding a size threshold, appending numbered backups.
import os
from pathlib import Path
def rotate_logs(directory: str, max_size: int = 100) -> None:
"""Rotate log files that exceed max_size bytes."""
log_dir = Path(directory)
for log_file in sorted(log_dir.glob("*.log"), key=lambda p: str(p)):
if log_file.stat().st_size > max_size:
for …BFF aggregation pattern: combine multiple service responses in Python
Mock three backend services and aggregate their responses into one unified payload — the BFF pattern every Python microservice gateway relies on.
from dataclasses import dataclass
from typing import Any
@dataclass
class Service:
name: str
data: dict[str, Any]
def get_user_service() -> Service:
return Service("user", {"id": 1, "name": "Alice"})
def get_orders_service() -> Service:
return Service("orders", {"total": 299.99, "count": 2})
de…How to Compose Parallel API Calls in Python with asyncio.gather
Compose multiple mock API responses in parallel using asyncio.gather with per-service simulated latency.
import asyncio
import random
import time
async def mock_api(name: str, delay: float) -> dict:
await asyncio.sleep(delay)
return {"service": name, "value": random.randint(1, 100)}
async def fetch_all():
services = {
"users": mock_api("users", 0.2),
"orders": mock_api("orders", 0.3),
…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…Idempotent Consumer Event Processing in Python
Track processed event IDs to skip duplicates and count event types for a reliable, idempotent consumer.
import json
from collections import defaultdict
class EventProcessor:
def __init__(self):
self.processed_ids = set()
self.counts = defaultdict(int)
def process_event(self, event):
event_id = event["id"]
if event_id in self.processed_ids:
return {"status": "skipped"…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 Implement MapReduce Word Count in Python Using a Dict
Simulate a MapReduce word count pipeline in Python with a mock dict, splitting text into words, shuffling, and reducing to frequency counts.
def map_reduce_word_count(text: str) -> dict:
"""Simulate a MapReduce pipeline to count word frequencies."""
# MAP phase: split into words and emit (word, 1) pairs
mapped = []
for word in text.lower().split():
# Clean word of punctuation
clean_word = ''.join(char for char in word if cha…How to Mock a User-Defined Function (UDF) in Python
Wrap a real UDF implementation with call logging to simulate and track invocations in a data pipeline.
from typing import Any, Callable
# Mock a user-defined function (UDF) that was previously complex or external
def mock_udf(name: str, implementation: Callable[..., Any], *, calls: list[Any]) -> Callable[..., Any]:
"""Wrap a real implementation with call logging to simulate a UDF."""
def wrapper(*args: Any, *…How to Truncate Lineage Back to a Checkpoint in Python
Walks a linked list of lineage nodes upward to find the nearest checkpoint and returns that node, truncating the lineage.
class LineageNode:
def __init__(self, name, parent=None, checkpoint=None):
self.name = name
self.parent = parent
self.checkpoint = checkpoint
def truncate_at_checkpoint(self):
"""Truncate lineage back to the last checkpoint."""
current = self
while current.check…Modeling a Hive Metastore Table Schema in Python
A dataclass that mimics a Hive metastore table schema—columns, partition keys, storage format, and location—with helper methods for description and mutation.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class HiveTable:
"""Simple mock of a Hive metastore table schema."""
name: str
database: str = "default"
columns: List[Dict[str, str]] = field(default_factory=list)
partition_keys: List[Dict[str, str]] = f…Build a Data Helper Class in Python for ML Pipelines
A beginner-friendly Python class that summarizes, filters, and exports ML dataset rows as JSON.
from typing import List, Dict, Any
import json
class DataHelper:
"""Beginner-friendly helpers for ML data pipelines."""
def __init__(self, data: List[Dict[str, Any]]):
self.data = data
self.keys = list(data[0].keys()) if data else []
def summary(self) -> Dict[str, Any]:
"…Browse by section
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