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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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}")
…How to mock the domain center in an onion architecture in Python
Define a repository interface and an in-memory mock to test domain services without touching infrastructure.
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Dict, List, Optional
@dataclass
class Order:
id: int
customer: str
items: List[str]
total: float
class OrderRepository(ABC):
@abstractmethod
def find_by_id(self, order_id: int) -> Optional[Order]:
…How to Add a Correlation ID Tracing Header in Python
A mock middleware generates or preserves a correlation ID header and logs structured JSON messages with it for API request tracing.
import uuid
import json
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class Request:
headers: dict = field(default_factory=dict)
def get(self, key, default=None):
return self.headers.get(key, default)
class CorrelationIdMiddleware:
def __init__(self, header_name…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 Create an RFC 7807 Error JSON in Python
Construct a structured error response using the RFC 7807 Problem Details format with a reusable function.
import json
from typing import Dict
def create_rfc7807_error(
type_: str,
title: str,
status: int,
detail: str,
instance: str,
extra_fields: Dict[str, object] | None = None,
) -> str:
"""
Build a JSON string following RFC 7807 Problem Details format.
"""
problem = {
"t…How to Build a Message Stream Queue in Python
A beginner-friendly MessageStream class built on deque that sends messages one at a time, tracks unread counts, and records sent items.
from collections import deque
import time
class MessageStream:
def __init__(self, messages):
self._queue = deque(messages)
self._sent = []
def send_next(self):
if not self._queue:
return None
message = self._queue.popleft()
self._sent.append(message)
…Consistent Hashing Cache Shard in Python
A minimal consistent hashing ring with virtual nodes that distributes cache keys across shards and minimizes re-mapping when a node is removed.
import hashlib
import bisect
class ConsistentHashRing:
def __init__(self, nodes=None, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
if nodes:
for node in nodes:
self.add_node(node)
def _hash(self, key):
return i…How to Implement an LFU Cache in Python
Implement a Least Frequently Used (LFU) cache with frequency tracking dictionaries to evict the least accessed items when capacity is reached.
class LFUCache:
def __init__(self, capacity: int):
self.capacity = capacity
self.data = {}
self.freq = {}
self.min_freq = 0
def get(self, key: int) -> int:
if key not in self.data:
return -1
self._increment_freq(key)
return self.data[key]
…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 Do Structured JSON Line Logging in Python
Create a simple JSON-lines logger that writes one JSON object per line to stdout with timestamp, level, message, and custom context fields.
import json
import sys
from datetime import datetime
class JsonLineLogger:
def __init__(self, stream=sys.stdout):
self.stream = stream
def log(self, level, message, **context):
record = {
"timestamp": datetime.utcnow().isoformat() + "Z",
"level": level,
"me…How to Do Structured JSON Logging in Python
Create a custom logging formatter that outputs each log entry as a single JSON line with timestamp, level, logger name, and message.
import json
import logging
from datetime import datetime
class JsonFormatter(logging.Formatter):
def format(self, record):
log_entry = {
"timestamp": datetime.utcnow().isoformat() + "Z",
"level": record.levelname,
"logger": record.name,
"message": record.ge…How to Create a Mock Iceberg Snapshot Manifest in Python
Build a mock Iceberg snapshot manifest structure with metadata and data entries using Python dictionaries and JSON.
import json
from datetime import datetime, timezone
def create_mock_manifest(snapshot_id: int, file_paths: list[str]) -> dict:
"""Create a mock Iceberg snapshot manifest structure."""
manifest_file = {
"manifest_path": f"/warehouse/table/metadata/snap-{snapshot_id}-m0.avro",
"manifest_length"…How to Implement a Streaming Watermark in Python
Mock structured streaming watermarks in Python to track late event times and compute a watermark for windowed processing.
from datetime import datetime, timedelta
import time
class StreamingWatermark:
"""Mock watermark tracker for structured streaming."""
def __init__(self, watermark_delay_seconds):
self.watermark_delay = timedelta(seconds=watermark_delay_seconds)
self.max_event_time = None
def observe_even…How to use foreachBatch with a mock sink in PySpark
Demonstrates using Spark Structured Streaming's foreachBatch sink to capture and verify streaming batches by writing them into a custom mock sink object.
from pyspark.sql import SparkSession
from pyspark.sql.functions import col, lit
class MockSink:
def __init__(self):
self.batches = []
def write_batch(self, batch_df, batch_id):
# Collect batch data as list of dicts for verification
records = batch_df.collect()
self.batches…Sliding Window Streaming Mock in Python
A simple Python class that maintains a sliding window of recent streaming values and computes the running average.
import time
import random
class StreamingMock:
"""Produces a stream of numbers using a sliding window."""
def __init__(self, window_size=5):
self.window = []
self.window_size = window_size
def push(self, value):
"""Add a value, sliding the window forward."""
s…How to Mock a Feature Store Online Lookup in Python
This code simulates an online feature store with single and batch retrieval methods, using a dict-backed cache and timestamps.
import random
import time
class OnlineFeatureStore:
def __init__(self):
self.features = {}
def put(self, entity_id: str, feature_name: str, value):
key = (entity_id, feature_name)
self.features[key] = (value, time.time())
def get(self, entity_id: str, feature_name: str):
…Model registry version mock in Python
A simple in-memory model registry that stores model versions with metadata and supports version listing and latest retrieval.
class ModelRegistry:
def __init__(self):
self.models = {}
def register(self, name, version, model_type, metrics=None):
if name not in self.models:
self.models[name] = []
entry = {
"version": version,
"model_type": model_type,
"metrics": m…B-Tree Insert and In-Order Traversal in Python
Simulates a B-tree (order 2) with insert and split logic, then prints keys in sorted order via in-order traversal.
class BTreeNode:
def __init__(self, leaf=False):
self.leaf = leaf
self.keys = []
self.children = []
def is_full(self, t):
return len(self.keys) == 2 * t - 1
class BTree:
def __init__(self, t=2):
self.t = t
self.root = BTreeNode(leaf=True)
def insert(s…How to Simulate a Stable Sort Cursor in Python
Build a MongoDB-style cursor mock that stably sorts records by a key while preserving original order for ties, with next() and rewind() methods.
```python
import random
class CursorStableSortMock:
"""Simulates stable sorting with a cursor-like pointer for MongoDB-style queries."""
def __init__(self, data, sort_key, reverse=False):
self.data = list(data)
self.sort_key = sort_key
self.reverse = reverse
self._index = …How to Mock Image Signing Cost in Python
Create a deterministic mock signing cost calculator that predicts resource usage for image signatures before real signing infrastructure is staged.
import math
import struct
def sign_image_cost(image_signature: bytes) -> int:
"""Deterministic mock signing cost based on image signature bytes."""
if not image_signature:
raise ValueError("Empty image signature")
digest = 0
for byte in image_signature:
digest = (digest * 31 + byte) &…How to Mock Terraform Plan and Apply in Python
This code provides a lightweight Python mock of Terraform's plan and apply commands, helping you simulate infrastructure changes without real cloud resources.
class MockTerraform:
def __init__(self):
self.plans = [
{"id": 1, "action": "create", "resource": "aws_instance.web"},
{"id": 2, "action": "update", "resource": "aws_s3_bucket.data"},
{"id": 3, "action": "destroy", "resource": "aws_iam_user.legacy"}
]
sel…How to Mock an Ingress TLS Certificate Manager in Python
Build a mock TLS certificate manager for ingress that issues, checks, and renews certificates with expiry tracking — useful for testing deployment workflows before touching real infrastructure.
import ssl
import socket
from datetime import datetime, timedelta
class TLSCertManager:
def __init__(self, hostname):
self.hostname = hostname
self.certificates = {}
def request_certificate(self, domain, days_valid=90):
"""Mock a certificate issuance request that stores a cert with e…Browse by section
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