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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Create a Data Helper Class in Python with OOP
A complete OOP example with User, Post, and Blog classes that manage data relationships and provide clear helper methods.
class User:
def __init__(self, name, email):
self.name = name
self.email = email
self.posts = []
def create_post(self, title, content):
post = Post(title, content, self)
self.posts.append(post)
return post
def get_post_count(self):
return len(self.p…Find the Duplicate Number in Python Using Floyd's Cycle Detection
Detects the duplicate integer in an array of n+1 numbers (values 1 to n) in O(n) time and O(1) space using Floyd's cycle detection algorithm applied to a linked-list model.
def find_duplicate(nums):
slow = nums[0]
fast = nums[0]
# Phase 1: Find intersection point of the cycle
while True:
slow = nums[slow]
fast = nums[nums[fast]]
if slow == fast:
break
# Phase 2: Find the start of the cycle (the duplicate)
slow = nums[0…How to Build a System-User-Assistant Message List in Python
Use dataclasses to model a chat conversation and build the system/user/assistant message list expected by LLM APIs.
from dataclasses import dataclass, field
from typing import List
@dataclass
class Message:
role: str
content: str
@dataclass
class Conversation:
messages: List[Message] = field(default_factory=list)
def add_system(self, content: str) -> None:
self.messages.append(Message(role="system", con…How to Parse Chat Completion JSON in Python
Parse a mock OpenAI chat completion JSON response into a clean dictionary with content, finish reason, and model.
import json
def parse_chat_response(raw: str) -> dict:
data = json.loads(raw)
choice = data["choices"][0]
return {
"content": choice["message"]["content"],
"finish_reason": choice["finish_reason"],
"model": data["model"],
}
if __name__ == "__main__":
mock_response = '''
…How to Parse JSON from LLM Model Output Fence in Python
Extract and parse a JSON object from a language model's output that may be wrapped in triple-backtick fences with an optional language tag.
import json
import re
def parse_json_from_fence(text):
"""
Extract JSON object from a model output that may be wrapped in
triple-backtick fences with optional language tag.
"""
# Match content insideHow to Mock a Whisper API Transcription Stub in Python
Simulate an OpenAI Whisper-style transcription response with a dataclass request model and a mock function that returns structured audio transcription output.
import json
from dataclasses import dataclass
from typing import Optional
@dataclass
class AudioRequest:
file_path: str
language: Optional[str] = None
def to_api_payload(self) -> dict:
return {"file": self.file_path, "language": self.language}
def mock_whisper_transcribe(payload: dict) -> dict:
…Resize Disk Partitions in Python (Mock Script)
A mock disk partition resize script that uses dataclasses to model partitions, validate new sizes, and output the updated layout as JSON.
#!/usr/bin/env python3
"""Mock script to demonstrate disk partition resize logic."""
import json
from dataclasses import dataclass
from typing import Dict
@dataclass
class Partition:
name: str
size_gb: int
mount_point: str
def to_dict(self) -> Dict[str, object]:
return {
"name": …How to perform a star schema join in Python
Denormalize mock fact and dimension tables by building lookup dicts and enriching each sales fact with customer, product, and date attributes.
from datetime import date
# Mock dimension tables
customers = [
{"customer_id": 1, "name": "Alice", "city": "New York"},
{"customer_id": 2, "name": "Bob", "city": "Los Angeles"},
{"customer_id": 3, "name": "Carol", "city": "Chicago"},
]
products = [
{"product_id": 101, "name": "Laptop", "category": "…How to Mock a Factory Boy Model Instance in Python
Create a factory boy factory, then patch its Meta.model with a Mock to control instance behavior in tests.
import factory
from dataclasses import dataclass
from unittest.mock import Mock, patch
import builtins
@dataclass
class User:
name: str
age: int
class UserFactory(factory.Factory):
class Meta:
model = User
name = "Alice"
age = 30
def get_user_name(user):
return user.name
def ma…Domain Driven Design Aggregate Root Example in Python
Model an Order as an aggregate root with invariants enforced through methods, demonstrating DDD principles in Python.
from __future__ import annotations
from dataclasses import dataclass
from typing import List, Optional
from uuid import uuid4
class Money:
def __init__(self, amount: float, currency: str = "USD"):
self.amount = amount
self.currency = currency
def __add__(self, other: Money) -> Money:
…How to Build an MVP Presenter View Mock in Python
A minimal MVP (Model-View-Presenter) mock showing a Presenter controlling a SlideDeck model with slide navigation and typed state via dataclasses.
from dataclasses import dataclass, field
from typing import List
@dataclass
class SlideDeck:
title: str
slides: List[str] = field(default_factory=list)
current_index: int = 0
def next_slide(self) -> str:
if self.current_index < len(self.slides) - 1:
self.current_index += 1
…How to Implement CQRS with Separate Read and Write Models in Python
Implements Command Query Responsibility Segregation (CQRS) by splitting data into separate write and read models with dedicated repositories, using dataclasses for structure.
from dataclasses import dataclass, field
from typing import List, Dict, Optional
@dataclass
class OrderWriteModel:
order_id: int
customer: str
items: List[str] = field(default_factory=list)
def add_item(self, item: str) -> None:
self.items.append(item)
@dataclass
class OrderReadModel:
…How to Implement a Simple MVVM Binding Mock in Python
A minimal Python implementation of the MVVM pattern, mocking data binding so views auto-update when the view model changes.
class BindingMock:
def __init__(self, view_model):
self.view_model = view_model
self.subscribers = []
def bind(self, property_name, callback):
self.subscribers.append((property_name, callback))
def set(self, property_name, value):
setattr(self.view_model, property_name, va…Python MVC Pattern Example (Model-View-Controller)
A minimal, runnable Model-View-Controller (MVC) example in pure Python that separates data, presentation, and logic.
class Model:
def __init__(self):
self.data = {"title": "Initial Title", "content": "Initial Content"}
def get_data(self):
return self.data
def update_data(self, title=None, content=None):
if title:
self.data["title"] = title
if content:
self.data["c…How to mock a CQRS projector read model update in Python
Build a CQRS projector class that maintains denormalized read models by applying domain events in a mock order-processing service.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class OrderReadModel:
order_id: str
customer_name: str
total: float
status: str = "pending"
items: List[Dict] = field(default_factory=list)
def apply_event(self, event_type: str, payload: Dict) -> Non…At Least Once with Idempotent Consumer in Python
Implements a thread-safe idempotent consumer that processes each unique message exactly once, even when a producer sends duplicates under an at-least-once delivery model.
import threading
import time
import uuid
from collections import Counter
class IdempotentConsumer:
def __init__(self):
self.processed = set()
self._lock = threading.Lock()
def consume(self, message_id, payload):
with self._lock:
if message_id in self.processed:
…How to Model Span Events in Python
Define a Span class with timestamped milestone events and a completion marker to track operation lifecycle.
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import List
class SpanStatus(Enum):
STARTED = "started"
COMPLETED = "completed"
@dataclass
class SpanEvent:
name: str
timestamp: float = field(default_factory=time.time)
attributes: dict = field(default_facto…How to Build an Anti-Corruption Layer in Python
Translate messy legacy system data into a clean domain model using an anti-corruption layer in Python.
class MockLegacySystem:
"""Simulates a legacy system with messy data formats."""
def get_user_data(self):
# Legacy format: fields are abbreviated and types are inconsistent
return {
"usr_id": "USR-123",
"usr_nm": "john_doe",
"email_addrs": "John.Doe@example.c…How to Mock a Choreography Saga in Python
Simulate a choreography-based saga with event envelopes, status tracking, and compensating actions to model distributed transactions.
import json
from dataclasses import dataclass, asdict
from typing import List, Optional
from enum import Enum
class SagaStatus(Enum):
PENDING = "PENDING"
COMPLETING = "COMPLETING"
COMPLETED = "COMPLETED"
FAILED = "FAILED"
@dataclass
class EventEnvelope:
event_type: str
order_id: str
sta…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…Bayesian Optimization in Python: A Simplified Mock Implementation
A toy Bayesian optimization loop with a Gaussian process prior, expected improvement acquisition, and noisy sampling to find a function's minimum.
import random
import math
class BayesianOptimizer:
def __init__(self, noise=0.1):
self.noise = noise
self.observations = []
def objective(self, x):
return (math.sin(3*x) + 0.5*x) / (1 + x**2)
def gaussian_process_prior(self, x1, x2, length_scale=0.5):
return math.…Champion Challenger Deployment Mock in Python
Simulates an A/B champion-challenger ML deployment workflow — comparing two mock model accuracies and deciding which to promote to production.
import random
import time
class ModelMocker:
def __init__(self, name="Model", accuracy=0.85):
self.name = name
self.accuracy = accuracy
def predict(self, data):
"""Simulate prediction with some randomness."""
time.sleep(0.005) # simulate compute time
return 1 if rando…Compare Model A vs Model B Metrics in Python
A script that simulates and compares metrics between two ML models, showing a formatted diff table for quick insight.
import random
def compare_a_b(samples=5):
"""Mock comparison of model A vs model B predictions."""
metrics = ["accuracy", "precision", "recall", "f1"]
print(f"{'Metric':<12}{'Model A':>10}{'Model B':>10}{'Diff':>10}")
print("-" * 42)
random.seed(42)
for metric in metrics:
a = round(r…How to Build an sklearn Pipeline with ColumnTransformer in Python
A mock example showing how to chain preprocessing and a regression model into a single sklearn Pipeline, scaling numeric features and one-hot encoding categorical features with ColumnTransformer.
import numpy as np
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LinearRegression
# Mock dataset
X = np.array([[1, 'red'], [2, 'blue'], [3, 'red'], [4, 'green'], [5, 'blue']], dtype=o…Browse by section
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