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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Build a Secure Password Strength Checker in Python
A Python function that evaluates password strength based on length and character diversity, returning Weak, Moderate, or Strong.
import re
def password_strength(password: str) -> str:
score = 0
if len(password) >= 8:
score += 1
if re.search(r'[a-z]', password):
score += 1
if re.search(r'[A-Z]', password):
score += 1
if re.search(r'\d', password):
score += 1
if re.search(r'[!@#$%^&*(),.?":…
How to Find the Mode in a Python List
Find the most frequent value (mode) in a Python list using the collections.Counter class, handling empty lists and ties.
from collections import Counter
def find_mode(numbers):
if not numbers:
return None
counts = Counter(numbers)
max_count = max(counts.values())
modes = [num for num, count in counts.items() if count == max_count]
return modes[0] if len(modes) == 1 else modes
if __name__ == "__main__":
…
How to Write Bytes to a File in Python with 'wb'
Write a bytearray buffer to a binary file using Python's open() in 'wb' mode, then read it back to confirm the data.
data = bytearray([0x48, 0x65, 0x6c, 0x6c, 0x6f, 0x20, 0x57, 0x6f, 0x72, 0x6c, 0x64])
with open("output.bin", "wb") as f:
f.write(data)
with open("output.bin", "rb") as f:
content = f.read()
print(f"Written {len(data)} bytes: {content}")
print(f"As string: {content.decode('ascii')}")
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…
Python Adapter Class: Wrap Legacy Interface
Convert a legacy system's interface into a modern one using the Adapter pattern in Python, translating method calls and data formats.
class LegacySystem:
"""Legacy interface - old method names and parameter format."""
def query_employee_info(self, emp_id, emp_name):
return f"Legacy: {emp_id} - {emp_name}"
def update_employee_department(self, emp_id, department_code):
return f"Legacy: Updated {emp_id} to dept {department_…
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 Filter Blocked Words in Python
Scans input text against a moderation blocklist, returning blocked terms and their counts.
MODERATION_BLOCKLIST = {"spam", "scam", "fraud", "phishing", "malware", "abuse"}
def scan_text(text: str) -> dict:
normalized = text.lower()
words = normalized.replace(".", " ").replace(",", " ").replace("!", " ").replace("?", " ").split()
found_terms = []
for word in words:
if word in MO…
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 inside
JSON Mode Prompt Schema Output in Python
Extract a user object to JSON with explicit schema keys, ready for LLM JSON-mode prompts.
import json
from typing import Any, Dict
def extract_user_as_json(user: Dict[str, Any]) -> str:
"""Extract a user object and return it as JSON using explicit schema keys."""
schema_fields = ("id", "name", "email", "is_active")
user_subset = {key: user[key] for key in schema_fields if key in user}
ret…
How 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 isort Output to Test Import Sorting in Python
Uses isort with check mode and a unittest mock to verify whether a Python source string has correctly sorted imports.
import isort
from unittest.mock import patch
code = """
import os
import sys
import json
import pathlib
"""
def check_imports_sorted(code_str):
with patch("isort.api.output") as mock_output:
isort.code(code_str, check=True, show_diff=True)
return mock_output.called
if __name__ == "__main__":
…
How to Parse and Extract Nested Data in Python
Load JSON files with Path and recursively extract values by key from nested Python structures using modern typing and standard library.
import json
from pathlib import Path
from typing import Any, Dict, List, Union
def load_data(filepath: Union[str, Path]) -> Union[Dict[str, Any], List[Any]]:
"""Load JSON data from a file with modern Path handling."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not f…
How to set up mypy strict mode in Python
Demonstrates how to configure and run mypy in strict mode to enforce full type annotation coverage across a Python project.
from typing import Dict, Optional
def describe_user(name: str, age: int, email: Optional[str] = None) -> Dict[str, object]:
"""Build a user description dictionary with strict type annotations."""
user: Dict[str, object] = {"name": name, "age": age}
if email is not None:
user["email"] = email
…
Format Data with Type Hints in Python
Build a validated person dict with modern type hints and optional list handling.
from typing import Any, Dict, List, Optional, Union
JsonValue = Union[str, int, float, bool, None, List["JsonValue"], Dict[str, "JsonValue"]]
def format_person(name: str, age: int, hobbies: Optional[List[str]] = None) -> Dict[str, Any]:
"""Build a person dict with validated typing."""
if not name or age < 0:…
How to Filter Data in Python with Type Hints
A reusable filter_data helper uses optional predicates and numeric bounds with modern Python type hints.
from typing import Iterable, TypeVar, Callable, Any
T = TypeVar("T")
def filter_data(
items: Iterable[T],
predicate: Callable[[T], bool] | None = None,
*,
min_value: float | None = None,
max_value: float | None = None,
) -> list[T]:
"""Filter items by predicate and/or numeric bounds."""
r…
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…
How to Parse Data with Type Hints in Python
A beginner-friendly helper that parses simple dictionary- or list-like strings into typed Python structures using modern typing annotations.
from typing import Any, Dict, List, Union
def parse_data(raw: str) -> Union[Dict[str, Any], List[Any], str]:
"""Parse a simple string into structured data using type hints."""
cleaned = raw.strip()
if not cleaned:
return {}
if cleaned.startswith("{") and cleaned.endswith("}"):
…
How to mark known bugs with pytest xfail in Python
Use @pytest.mark.xfail to mark tests that are expected to fail due to known bugs, with optional strict mode to control pass/fail behavior.
import pytest
def divide(a: int, b: int) -> float:
if b == 0:
raise ZeroDivisionError("Cannot divide by zero")
return a / b
@pytest.mark.xfail(reason="Known bug: division returns int instead of float", strict=False)
def test_divide_integer_division():
result = divide(10, 4)
assert isinstanc…
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 Anti-Corruption Layer in Python
Wrap a legacy system with a translation layer that converts awkward legacy data into a clean, modern DTO (Data Transfer Object) for use by new code.
class LegacyOrderSystem:
"""Legacy system with awkward, unstructured data."""
def get_order(self):
return {
"order_id": "ORD-123",
"cust": "Acme Corp",
"items": [{"sku": "A1", "qty": 2, "price_each": 10.0}],
"ship_to": "123 Main St, Springfield"
}…
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Copy-ready Python snippets for learners and developers
PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.
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- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.