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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Build an Adapter to Translate External API Responses in Python
Build an adapter class that translates a mock external API's response shape into your internal representation, keeping callers decoupled from the external contract.
import json
from typing import Dict, Any
class ExternalAPI:
"""Mock external service returning a different data shape."""
def get_user(self, user_id: int) -> Dict[str, Any]:
return {
"id": user_id,
"full_name": "Jane Doe",
"email_address": "jane@example.com",
…
How to Implement a Simple Event Bus in Python
Create a publish-subscribe event bus using dataclasses and defaultdict to decouple event producers from consumers.
from collections import defaultdict
from dataclasses import dataclass, field
from typing import Callable, Dict, List, Set
@dataclass
class EventBus:
_subscribers: Dict[str, List[Callable]] = field(
default_factory=lambda: defaultdict(list)
)
def subscribe(self, event_type: str, handler: Callable…
How to Implement the Repository Pattern in Python with an In-Memory Dict
Stores, retrieves, updates, and deletes user records in memory using a Repository abstraction over a plain dict, isolating data access from business logic.
class UserRepository:
def __init__(self):
self._storage = {}
self._next_id = 1
def create(self, name, email):
user_id = self._next_id
self._next_id += 1
self._storage[user_id] = {"id": user_id, "name": name, "email": email}
return self._storage[user_id]
def…
How to Structure a Three-Tier Layered Architecture in Python
A mock three-tier architecture with presentation, business, and data layers that process a user request from input to response.
class PresentationLayer:
def __init__(self, business_layer):
self.business = business_layer
def handle_request(self, user_id):
print(f"[Presentation] Received request for user {user_id}")
data = self.business.process_user(user_id)
print(f"[Presentation] Response: {data}")
…
Implement Bulkhead Thread Pool Isolation in Python
Create isolated thread pools with a bulkhead pattern to protect different services from cascading failures.
import threading
import time
import random
from concurrent.futures import ThreadPoolExecutor
class Bulkhead:
"""Simple bulkhead isolation: separate thread pools for different tasks."""
def __init__(self, max_workers):
self.executor = ThreadPoolExecutor(max_workers=max_workers)
self.active = …
Format data in Python using dataclasses like gRPC messages
Convert Python dataclasses to and from dicts and format them gRPC-style for clean data handling.
from dataclasses import dataclass
from typing import Any, Dict, List, Optional
@dataclass
class ProductInfo:
"""Data class representing a gRPC-style product message."""
name: str
price: float
tags: List[str]
description: Optional[str] = None
def to_dict(self) -> Dict[str, Any]:
"""C…
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()
…
How to Decode Basic Auth Credentials in Python
Decode username and password from a Basic Auth header string using base64 and standard string operations.
import base64
def decode_basic_auth(header_value):
"""
Decode credentials from a Basic Auth header value.
Expected format: "Basic base64encoded(username:password)"
Returns a tuple (username, password).
"""
if not header_value.startswith("Basic "):
raise ValueError("Invalid Basic A…
How to Handle Retry-After Header in Python
Parse the Retry-After header from rate-limited API responses and implement retry logic with proper delays in Python.
```python
import time
from datetime import datetime, timedelta
class RetryAfterHandler:
def __init__(self, max_retries=3):
self.max_retries = max_retries
def get_retry_after_seconds(self, response_headers):
retry_after_value = response_headers.get("Retry-After")
if retry_after_value …
Implement If-Match Precondition Update in Python
A mock resource store that uses the If-Match header's ETag to guard updates, preventing overwrites from stale clients.
from dataclasses import dataclass
from typing import Optional
@dataclass
class Resource:
id: str
version: int = 1
data: str = ""
etag: str = "etag-1"
class MockResourceStore:
def __init__(self):
self.resources = {}
def update(self, resource_id: str, new_data: str, if_match: Optiona…
How to Read Redis Streams with XREADGROUP in Python
Read new messages from a Redis stream using a consumer group with XREADGROUP, handling JSON payloads and group creation.
import redis
import json
def read_group_messages(stream_key, group_name, consumer_name, count=10):
r = redis.Redis(host="localhost", port=6379, decode_responses=True)
try:
r.xgroup_create(stream_key, group_name, id="0", mkstream=True)
except redis.exceptions.ResponseError:
pass
messag…
How to Serialize and Deserialize JSON Event Payloads in Python
Define an EventPayload class with custom to_json and from_json methods to convert event objects to JSON strings and back, using datetime parsing.
import json
from datetime import datetime
class EventPayload:
def __init__(self, event_id, event_type, timestamp, data):
self.event_id = event_id
self.event_type = event_type
self.timestamp = timestamp
self.data = data
def to_json(self):
return json.dumps({
…
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 Asides in Python with a Read-Through Loader
Implements a cache-aside pattern with a read-through loader that fetches missing keys from a backing data store and caches them.
class DataStore:
"""Mock database with a few records."""
def __init__(self):
self.data = {1: "Alice", 2: "Bob", 3: "Charlie"}
def get(self, key):
print(f"Loading key {key} from database")
return self.data.get(key)
class CacheAsideLoader:
"""Cache-aside pattern with a read-thr…
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…
How to create a stable cache key from function arguments in Python
Generate a stable SHA-256 cache key from normalized function arguments, with keyword order normalized and tests using mocks.
import hashlib
import json
from unittest.mock import Mock
def make_cache_key(*args, **kwargs):
"""Normalize args/kwargs into a stable hash key for caching."""
normalized = {
"args": [repr(arg) for arg in args],
"kwargs": {key: repr(value) for key, value in sorted(kwargs.items())}
}
pa…
Calculate Error Rate from Log Stream in Python
Parses a mock log stream to count errors and compute the error percentage using a rolling window of recent entries.
import re
from collections import deque
def error_rate_from_log_stream(message):
log_pattern = r'^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] (ERROR|INFO|DEBUG): (.*)$'
recent_entries = deque(maxlen=100)
error_count = 0
total_count = 0
for line in message.strip().split('\n'):
match = re.mat…
How to Calculate Apdex Score from Latency Data in Python
Generate simulated latency samples and compute the Apdex score to gauge user satisfaction with an application's performance.
import random
import statistics
def generate_latencies(count=100, base=100, stddev=30):
return [max(0, random.gauss(base, stddev)) for _ in range(count)]
def apdex(latencies, threshold=200):
satisfied = sum(1 for lat in latencies if lat < threshold)
tolerating = sum(1 for lat in latencies if lat >= thres…
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.
```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…
How to Parse Log Lines with Regex in Python
Extracts timestamp, log level, service name, and message from a log line using compiled regex named groups.
import re
LOG_PATTERN = re.compile(
r'^(?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}) '
r'\[(?P<level>\w+)\] '
r'\((?P<service>[^)]+)\) '
r'(?P<message>.*)$'
)
def parse_log_line(line: str) -> dict:
match = LOG_PATTERN.match(line)
if not match:
return {"error": "invalid log format…
How to Redact Secrets from Log Messages in Python
Build a lightweight RedactingFormatter class that replaces sensitive tokens like passwords and API keys with [REDACTED] before log messages are printed.
class RedactingFormatter:
def __init__(self, secrets):
self.secrets = secrets
def redact(self, message):
for secret in self.secrets:
message = message.replace(secret, "[REDACTED]")
return message
def format(self, record):
message = record["message"]
ret…
How to Track Cache Hit Ratio in Python
Simulate an LRU cache with hit/miss tracking and compute a real-time hit ratio from random access patterns.
import random
import time
from collections import OrderedDict
class LRUCache:
def __init__(self, capacity: int):
self.cache = OrderedDict()
self.capacity = capacity
self.hits = 0
self.misses = 0
def get(self, key):
if key in self.cache:
self.hits += 1
…
Cache-Aside Pattern in Python: Per-Service Mock
A Python mock of the cache-aside pattern for a single microservice—lazy-load from a database into an in-memory cache and invalidate on updates.
class ServiceCache:
def __init__(self):
self.database = {"user:1": "Alice", "user:2": "Bob", "user:3": "Charlie"}
self.cache = {}
def get_user(self, user_id):
cache_key = f"user:{user_id}"
if cache_key in self.cache:
print(f"CACHE HIT: {cache_key}")
retu…
Strangler Fig Migration Pattern in Python
Gradually reroute calls from a legacy service to a modern replacement using a runtime switch and feature detection.
from dataclasses import dataclass
@dataclass
class PaymentService:
def process(self, amount: float) -> str:
return f"Legacy processed ${amount:.2f}"
class StranglerFig:
def __init__(self):
self._new_service = None
def attach_new(self, service):
self._new_service = service
de…
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