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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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
…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…Bulkhead Thread Pool per Service Mock in Python
Simulates a bulkhead pattern with per-service thread pools and semaphore-based rejection to isolate failures between dependent services.
import threading
import time
import random
from concurrent.futures import ThreadPoolExecutor
class ServiceBulkhead:
def __init__(self, name, max_threads, max_queue):
self.name = name
self.executor = ThreadPoolExecutor(max_workers=max_threads)
self.semaphore = threading.Semaphore(max_thread…CQRS with Separate Read and Write Repositories in Python
Implement CQRS in Python with separate write and read repositories, using commands for mutations and frozen DTOs for queries.
from dataclasses import dataclass
from typing import Dict, List, Optional
# --- Write side: commands mutate state ---
@dataclass
class CreateUserCommand:
id: int
name: str
class UserWriteRepository:
def __init__(self) -> None:
self._store: Dict[int, Dict[str, object]] = {}
def create(self,…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…How to Build a Microservice Helper in Python
A beginner-friendly Python helper that validates input, normalizes service responses, and simulates user management—showing clean patterns for microservice development.
import json
from typing import Any, Dict, List
class DataValidator:
"""Simple validator for common data patterns."""
@staticmethod
def is_valid_email(value: str) -> bool:
"""Check if value looks like an email."""
return "@" in value and "." in value.split("@")[-1]
@staticmethod
…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 implement the Database per service pattern in Python
Simulate separate databases per microservice in Python using dataclasses and in-memory dictionaries, showing how services own their data independently.
import json
from dataclasses import dataclass, asdict
from typing import Dict, List
@dataclass
class User:
id: int
name: str
email: str
@dataclass
class Order:
id: int
user_id: int
product: str
amount: float
class UserServiceDB:
"""Simulates a separate database for the User servic…Saga pattern orchestration with rollback in Python
Orchestrate a distributed transaction with Saga steps and automated compensation rollback on failure.
import time
import random
class SagaStep:
def __init__(self, name):
self.name = name
self.executed = False
def execute(self):
print(f"Executing {self.name}...")
time.sleep(0.2)
if random.random() < 0.3:
raise RuntimeError(f"{self.name} failed")
sel…Scatter Gather Aggregate Pattern in Python
Simulates a scatter/gather/aggregate pattern by distributing work across items, gathering results, and aggregating them.
import random
def process_items(items, scatter_fn, gather_fn, aggregate_fn):
"""Simple scatter/gather/aggregate pattern simulation."""
scattered = [scatter_fn(item) for item in items]
gathered = [gather_fn(item) for item in scattered]
return aggregate_fn(gathered)
if __name__ == "__main__":
data …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…How to Broadcast a Small Lookup Table in Python
Simulates broadcasting a small lookup table by iterating key-value pairs and emitting packed rows to subscribers with deterministic output.
import random
# Generate a deterministic mock broadcast of a small lookup table
# with 5 keys and random integer values (seeded for reproducibility)
data = {
"sensor_a": 22,
"sensor_b": 87,
"sensor_c": 43,
"sensor_d": 65,
"sensor_e": 31,
}
# Simulate a broadcast to subscribers by iterating and p…How to Mock a File Source Watch Directory in Python
Poll a directory for new files and log changes, simulating a watch directory for data ingestion patterns.
import os
import time
from pathlib import Path
def watch_directory(dir_path: str, poll_interval: float = 1.0, max_iterations: int = 5):
"""
Mock a file-source watch directory by polling for changes.
Returns new files detected during each poll cycle.
"""
directory = Path(dir_path)
directory.mk…How to join assignment logs with outcomes in Python
Merge submission log entries with grading outcomes using left join and full outer join patterns in pure Python.
from datetime import datetime, timedelta
class AssignmentLog:
def __init__(self):
self.logs = [
{"assignment_id": 101, "student_id": "S001", "submitted_at": "2024-03-01 10:30:00"},
{"assignment_id": 101, "student_id": "S002", "submitted_at": "2024-03-02 14:15:00"},
{"as…Cross Shard Query Scatter Gather Mock in Python
Simulate a distributed database cross-shard query using a scatter-gather pattern with a mock Python implementation.
from dataclasses import dataclass
from typing import List, Dict
@dataclass
class NodeResponse:
node_id: int
data: Dict[str, float]
def mock_query_shard(shard_id: int, shard_data: Dict[str, float], query: str) -> NodeResponse:
"""Simulate querying a single shard, returning matches whose value > 50."""
…How to Eager Load with JOIN to Reduce N+1 Queries in Python
Demonstrates eager loading with a SQL JOIN to reduce N+1 query patterns down to a single database call when fetching related data.
import sqlite3
def eager_load_join_reduce(mock_db_path=":memory:"):
"""Demonstrate eager loading where joins reduce query count from N+1 to 1."""
conn = sqlite3.connect(mock_db_path)
cursor = conn.cursor()
cursor.executescript(
"""
CREATE TABLE authors (id INTEGER PRIMARY KEY, name TE…How to mock batch commit of transactions in Python
Simulate a transaction batch writer with commit, rollback, and summary logic to test database write patterns without a real database.
import json
from datetime import datetime, timezone
class TransactionBatch:
def __init__(self):
self.pending = []
self.committed = []
self._log = []
def add(self, operation):
self.pending.append(operation)
def commit(self):
if not self.pending:
return …Mock CQRS Read/Write Split in Python
Separate order mutations from queries using a read model and write model to mock CQRS-style separation of concerns.
from dataclasses import dataclass, field
from typing import List, Dict
@dataclass
class Order:
id: int
amount: float
status: str = "pending"
class OrderWriteModel:
"""Handles all mutations (writes) to orders."""
def __init__(self):
self._orders: Dict[int, Order] = {}
self._next…How to Build a Data Helper for Production Deployment in Python
Build a reusable DataHelper class that loads configs, validates required keys, normalizes string values, and logs schema details — a production-ready data processing pattern.
import json
from pathlib import Path
from typing import Any, Dict
class DataHelper:
"""Common data processing patterns for production deployment."""
def __init__(self, config_path: str | Path):
self.config_path = Path(config_path)
self.config = self._load_config()
def _load_confi…Zero Downtime Migration with Dual Write Pattern in Python
Implement a dual-write pattern that writes user data to both legacy and new systems simultaneously to enable zero-downtime migration.
from datetime import datetime
import json
class UserService:
def __init__(self):
self.legacy_db = {}
self.new_db = {}
self.migration_log = []
def write_user(self, user_id, name, email):
# Write to new system first
user_record = {
"id": user_id,
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