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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Unflatten Dot Keys to Nested Dict in Python
Convert a flat dictionary with dot-separated keys into a nested dictionary structure using recursive setdefault loops.
def unflatten_dot_keys(flat_dict):
result = {}
for flat_key, value in flat_dict.items():
parts = flat_key.split(".")
current = result
for part in parts[:-1]:
current = current.setdefault(part, {})
current[parts[-1]] = value
return result
if __name__ == "__main_…Graph Class with Adjacency Dict in Python
Build an undirected graph class using a dictionary of adjacency lists with methods to add vertices, edges, remove edges, and query neighbors.
class Graph:
def __init__(self):
self.adjacency = {}
def add_vertex(self, vertex):
if vertex not in self.adjacency:
self.adjacency[vertex] = []
def add_edge(self, u, v):
self.add_vertex(u)
self.add_vertex(v)
self.adjacency[u].append(v)
self.adja…How to Build a Class Method Alternative Constructor from Dict in Python
Use a classmethod alternative constructor to build a Book instance from a dictionary with sensible defaults.
class Book:
def __init__(self, title, author, pages):
self.title = title
self.author = author
self.pages = pages
@classmethod
def from_dict(cls, data):
"""Alternative constructor that builds a Book from a dictionary."""
return cls(
title=data["title"],
…How to Build a Fluent Interface with the Builder Pattern in Python
Learn to implement a fluent builder pattern in Python by chaining methods that return self, enabling readable object construction.
class Pizza:
def __init__(self):
self.size = None
self.toppings = []
self.crust = None
def set_size(self, size):
self.size = size
return self
def add_topping(self, topping):
self.toppings.append(topping)
return self
def set_crust(self, crust):
…How to Build a Linked List Node Class in Python
Create a Node class and a LinkedList class with insert, remove, and display methods to manage a singly linked list.
class Node:
def __init__(self, data):
self.data = data
self.next = None
class LinkedList:
def __init__(self):
self.head = None
def insert(self, data):
new_node = Node(data)
if not self.head:
self.head = new_node
else:
current = self.…How to Implement a Queue Class in Python Using deque
Build a FIFO queue class in Python backed by the collections.deque container with enqueue, dequeue, peek, and size methods.
from collections import deque
class Queue:
def __init__(self):
self._items = deque()
def enqueue(self, item):
self._items.append(item)
def dequeue(self):
if self.is_empty():
raise IndexError("dequeue from empty queue")
return self._items.popleft()
…How to Implement a Stack Class in Python
A complete Stack class implemented with a Python list, featuring push, pop, peek, is_empty, size, and a readable string representation.
class Stack:
def __init__(self):
self._items = []
def push(self, item):
"""Add an item to the top of the stack."""
self._items.append(item)
def pop(self):
"""Remove and return the top item. Raises IndexError if empty."""
if self.is_empty():
raise IndexE…How to Build a Coordinate Grid with Nested Loops in Python
Generate a 2D list of (row, col) coordinate pairs using nested loops and return the grid structure.
def build_coordinate_grid(rows, cols):
"""Build a 2D grid of (row, col) coordinates using nested loops."""
grid = []
for r in range(rows):
row = []
for c in range(cols):
row.append((r, c))
grid.append(row)
return grid
if __name__ == "__main__":
grid = build_coo…How to Heapify a List into a Min Heap with heapq in Python
Convert any list into a valid min heap in-place using Python's heapq.heapify(), then pop the smallest element to verify heap order.
import heapq
data = [5, 3, 8, 1, 9, 2, 7, 4, 6]
print("Original list:", data)
heapq.heapify(data)
print("Min heap:", data)
popped = heapq.heappop(data)
print("Smallest element popped:", popped)
print("Heap after pop:", data)Implement Insert Delete GetRandom O(1) in Python
Build a RandomizedSet class that supports insert, delete, and get_random in average O(1) time using a list and a dictionary mapping values to indices.
import random
class RandomizedSet:
def __init__(self):
self.values = []
self.index_map = {}
def insert(self, val):
if val in self.index_map:
return False
self.index_map[val] = len(self.values)
self.values.append(val)
return True
def delete(self…Implement Queue Using Two Stacks in Python
Python class that implements a FIFO queue using two stacks, with enqueue, dequeue, peek, and emptiness checks.
class QueueUsingStacks:
def __init__(self):
self.stack_in = []
self.stack_out = []
def enqueue(self, value):
self.stack_in.append(value)
def dequeue(self):
if not self.stack_out:
while self.stack_in:
self.stack_out.append(self.stack_in.pop())
…Implement a Stack Using List Push Pop in Python
A minimal Stack class built on a Python list, with push, pop, peek, is_empty, and size methods, including empty-stack guards.
class Stack:
def __init__(self):
self.items = []
def push(self, item):
self.items.append(item)
def pop(self):
if self.is_empty():
raise IndexError("pop from empty stack")
return self.items.pop()
def peek(self):
if self.is_empty():
raise…Chain of Thought Prompting in Python: Step-by-Step Reasoning Demo
This demo shows how to structure a function that explains its own reasoning step-by-step, mimicking chain-of-thought prompting for AI systems.
def solve_math_step_by_step(expression: str) -> str:
"""Solves a simple expression, showing each reasoning step."""
# Step 1: Parse the expression (assume "a + b" or "a - b")
parts = expression.split()
a = int(parts[0])
op = parts[1]
b = int(parts[2])
steps = []
steps.append(f"Step…Parse ReAct Logs into Thought Action Observation Steps in Python
Parse a ReAct agent's textual log into structured steps with thought, action, and observation using regex and named tuples.
import re
from collections import namedtuple
ReActStep = namedtuple("ReActStep", ["thought", "action", "observation"])
def parse_react_log(log: str) -> list[ReActStep]:
"""Parse a ReAct log into structured thought/action/observation steps."""
pattern = re.compile(
r"Thought:\s*(?P<thought>.+?)\s*"
…Serialize and Format Data for LLM Prompts in Python
Use dataclasses and the json module to convert Python objects to JSON strings, parse them back, and format structured data into prompt-friendly text for LLM calls.
import json
from dataclasses import dataclass, asdict
@dataclass
class Recipe:
"""Simple data model to represent a recipe."""
name: str
cuisine: str
prep_minutes: int
def to_json(recipe: Recipe) -> str:
"""Serialize a Recipe to a JSON string."""
return json.dumps(asdict(recipe), indent=2)
…Build a Complete Website Sitemap Generator Without External Services
Crawl a website recursively using only Python's standard library to generate a structured sitemap of internal links.
import json
from urllib.parse import urlparse, urljoin
from collections import deque
import urllib.request
import urllib.error
import re
from html.parser import HTMLParser
class SitemapParser(HTMLParser):
def __init__(self, base_url):
super().__init__()
self.base_url = base_url
self.links …Create Mock Watermarked Image Bytes in Python Without PIL
Builds a mock image-like byte stream with an embedded watermark using only stdlib modules, for testing pipelines without PIL.
from io import BytesIO
import zlib
import struct
def create_watermarked_bytes(width: int, height: int, watermark: bytes) -> bytes:
"""Create a mock image-like byte stream with a watermark (no PIL)."""
header = struct.pack("<2I", width, height)
payload = watermark * max(1, (width * height // max(1, len(wa…How to Automatically Download Every Favicon from a List of Websites in Python
Download each website's favicon.ico file by constructing its URL, making a GET request, and saving the binary content locally.
import requests
from urllib.parse import urlparse
import os
websites = [
"https://www.google.com",
"https://www.github.com",
"https://www.stackoverflow.com"
]
def download_favicon(url):
parsed = urlparse(url)
favicon_url = f"{parsed.scheme}://{parsed.netloc}/favicon.ico"
response = requests.g…How to Compress a Folder in Python While Preserving Directory Structure
A Python function that uses zipfile to recursively compress a folder, maintaining the original directory hierarchy inside the zip archive.
import os
import zipfile
from pathlib import Path
def compress_folder(source_dir: str, output_zip: str):
"""
Compress a folder into a zip file, preserving the directory structure.
Args:
source_dir: Path to the source directory to compress
output_zip: Path for the output zip file
"…How to Mock FFmpeg subprocess Calls in Python
Compress a video with ffmpeg while mocking subprocess.run to test the command construction without executing the actual encoder.
import subprocess
from unittest.mock import Mock, patch
def compress_video(input_path: str, output_path: str, crf: int = 23) -> None:
"""Compress a video using ffmpeg with a given CRF (quality) value."""
command = [
"ffmpeg",
"-i", input_path,
"-c:v", "libx264",
"-crf", str(cr…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:
…How to Parse Terraform Plan Output in Python
Parse mock Terraform plan output text into structured add, change, and destroy lists using Python.
import json
from typing import Dict, List
def parse_terraform_plan_output(plan_output_text: str) -> Dict[str, List[str]]:
"""
Parses a mock Terraform plan output text into a structured dictionary.
"""
parsed: Dict[str, List[str]] = {"add": [], "change": [], "destroy": []}
for line in plan_output_…How to Split PDF Pages into Ranges in Python
Simulates splitting a PDF into page ranges by validating and returning structured range splits for automation workflows.
import os
def split_pdf_ranges(pdf_name, num_pages, ranges):
"""
Simulates splitting a PDF by returning the page ranges that would be split.
Args:
pdf_name (str): Name of the PDF file.
num_pages (int): Total number of pages in the PDF.
ranges (list of tuple): List of (start, end) …ETL in Python: Extract CSV, Transform Dicts, Load JSON
Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.
import csv
import json
from pathlib import Path
def etl_csv_to_json(csv_path: str, json_path: str) -> None:
"""Extract CSV, transform rows to dicts, load to JSON."""
with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
records = list(reader)
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