Reference library

Python Code Samples

Medium snippets you can copy, study, and run in the browser editor.

73 matches
Automation & scripting medium

How to Download a GitHub Repository as a ZIP File in Python

Download any public GitHub repository as a ZIP file using the GitHub API and Python's requests and zipfile modules.

github download zip
Python
import requests
import zipfile
import io
import os

def download_github_repo_as_zip(repo_url, output_path='.'):
    """
    Download a GitHub repository as a ZIP file.
    
    Args:
        repo_url (str): Full GitHub repository URL (e.g., 'https://github.com/username/repo')
        output_path (str): Directory to sa…
35 0 Open
Automation & scripting medium

How to Monitor Website Content Changes in Python

This script fetches a webpage's content, computes its SHA-256 hash, and compares it with the last stored hash to detect and alert on changes.

web scraping monitoring requests
Python
import time
import hashlib
import requests
from pathlib import Path

def fetch_content_hash(url: str) -> str:
    response = requests.get(url, timeout=10)
    response.raise_for_status()
    return hashlib.sha256(response.text.encode()).hexdigest()

def monitor_website(url: str, check_interval: int = 60):
    hash_fil…
50 0 Open
Automation & scripting medium

How to Track GitHub Stars, Forks, and Watchers in Python

Automatically fetch and track stars, forks, and watchers for multiple GitHub repositories, saving snapshots locally as JSON files for historical analysis.

github api automation
Python
import os
import time
import json
import requests
from pathlib import Path
from datetime import datetime

REPOS = [
    "psf/requests",
    "python/cpython",
    "pallets/flask",
]
DATA_DIR = Path("github_metrics")

def fetch_repo_stats(repo):
    url = f"https://api.github.com/repos/{repo}"
    resp = requests.get(ur…
39 0 Open
Data pipelines & processing medium

Extract Schema.org Structured Data from Any Website in Python

A Python tool that fetches a webpage and extracts all JSON-LD structured data (Schema.org) embedded in <script> tags with type="application/ld+json".

web-scraping structured-data schema-org
Python
import requests
from bs4 import BeautifulSoup
import json

def extract_schema_org(url):
    """Extract structured data (Schema.org) from a website."""
    try:
        response = requests.get(url, timeout=10)
        response.raise_for_status()
    except requests.exceptions.RequestException as e:
        return {"err…
51 0 Open
Git + Python medium

Generate Release Notes Markdown from PR Titles in Python

Generate structured Markdown release notes from a list of pull request titles using conventional commit types.

release-notes git pr-titles
Python
import json
from datetime import datetime, timezone

PRS = [
    {"title": "feat: add user login", "number": 12, "merged_at": "2025-01-10"},
    {"title": "fix: resolve payment timeout", "number": 13, "merged_at": "2025-01-11"},
    {"title": "chore: bump dependencies", "number": 14, "merged_at": "2025-01-12"},
    {"…
15 0 Open
Cloud + Python medium

Build a URL Shortener Client with Python

A Python class that shortens long URLs and resolves short codes using a REST API built with requests.

url shortener api
Python
import json
import sys
import requests

class URLShortenerClient:
    def __init__(self, base_url="http://tinyurl.com"):
        self.base_url = base_url

    def shorten_url(self, long_url):
        payload = {"url": long_url}
        headers = {"Content-Type": "application/json"}
        response = requests.post(f"{…
58 0 Open
Concurrency & performance medium

Benchmark list.append vs deque.append in Python

Measures and compares the performance of appending to a Python list versus a collections.deque using timeit.repeat, showing best and average timings.

benchmark performance list
Python
"""Benchmark list.append vs collections.deque.append."""

import timeit

def bench(stmt, setup, repeat=5, number=1_000_000):
    times = timeit.repeat(stmt, setup=setup, repeat=repeat, number=number)
    return min(times), sum(times) / len(times)

if __name__ == "__main__":
    number = 1_000_000
    list_best, list_a…
14 0 Open
Concurrency & performance medium

How to Implement a Batch Requests Flush Interval in Python

A simple async batcher that accumulates items and flushes them either when a max batch size is reached or after a time-based flush interval.

asyncio batching concurrency
Python
import asyncio
from collections import deque

class Batcher:
    def __init__(self, flush_interval=0.5, max_batch=5):
        self.flush_interval = flush_interval
        self.max_batch = max_batch
        self.queue = deque()
        self.lock = asyncio.Lock()

    async def add(self, item):
        async with self.l…
14 0 Open
Concurrency & performance medium

How to Speed Up Data Filtering with Python ThreadPoolExecutor

This code compares sequential filtering of even numbers with a threaded version using ThreadPoolExecutor, showing a measurable speedup for I/O-bound work.

threadpoolexecutor concurrency filtering
Python
import time
from concurrent.futures import ThreadPoolExecutor
import random


def is_even(number):
    time.sleep(0.001)  # simulate work
    return number % 2 == 0


def filter_even_sequential(numbers):
    return [n for n in numbers if is_even(n)]


def filter_even_threaded(numbers):
    with ThreadPoolExecutor(max_…
14 0 Open
Concurrency & performance medium

How to Speed Up Downloads with ThreadPoolExecutor in Python

Compare sequential and thread-pool download loops to measure real speedup when I/O s bound.

threads concurrency performance
Python
import time
import threading
from concurrent.futures import ThreadPoolExecutor

def download_file(file_id):
    """Simulate fetching a file by sleeping briefly."""
    time.sleep(0.2)  # pretend network latency
    return f"file_{file_id}"

def sequential_downloads(num_files):
    """Process files one at a time."""
  …
13 0 Open
Concurrency & performance medium

How to Use ProcessPoolExecutor for CPU Parallel Map in Python

Run a function over a sequence of inputs in parallel across multiple CPU cores with ProcessPoolExecutor.map.

concurrency processpoolexecutor parallelism
Python
from concurrent.futures import ProcessPoolExecutor
import math

def compute_square(num):
    return num * num

def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(math.sqrt(n)) + 1):
        if n % i == 0:
            return False
    return True

if __name__ == "__main__":
    numbers = rang…
12 0 Open
Concurrency & performance medium

How to Use ThreadPoolExecutor for Concurrent Tasks in Python

Compare sequential execution with ThreadPoolExecutor for I/O-bound tasks, measuring speedup and timing with perf_counter.

concurrency threadpool performance
Python
import time
import threading
from concurrent.futures import ThreadPoolExecutor


def fetch_data(index):
    """Simulate a synchronous data fetch."""
    time.sleep(0.1)
    return f"data-{index}"


def run_sequential(total=10):
    """Run tasks one after another."""
    start = time.perf_counter()
    results = [fetch…
14 0 Open
Testing & modern typing medium

How to Mock and Stub API Calls in Playwright E2E Tests with Python

This code demonstrates how to mock and stub API responses in Playwright end-to-end tests using Python's unittest.mock patch and Playwright's APIRequestContext.

playwright e2e-testing mocking
Python
import re
from unittest.mock import patch
from playwright.sync_api import sync_playwright

def verify_api_mock(page, mock_url, mock_response):
    with patch("playwright.sync_api.APIRequestContext.get") as mock_get:
        mock_get.return_value.json.return_value = mock_response
        mock_get.return_value.status_co…
14 0 Open
System design patterns medium

How to Build an Immutable Money Value Object in Python

Implement an immutable Money class with rounded decimal amounts, currency, safe equality, and hashing for use as a value object.

value-object immutability money
Python
class Money:
    def __init__(self, amount: float, currency: str):
        object.__setattr__(self, "_amount", round(amount, 2))
        object.__setattr__(self, "_currency", currency)

    def __setattr__(self, name, value):
        raise AttributeError(f"Money is immutable: cannot set '{name}'")

    def __delattr__…
13 0 Open
System design patterns medium

How to Limit Concurrent Requests with a Semaphore in Python

Use threading.Semaphore with a ThreadPoolExecutor to cap how many worker threads run simultaneously, preventing resource overload.

concurrency semaphore threading
Python
import threading
import time
from concurrent.futures import ThreadPoolExecutor

def worker(name, semaphore, results):
    with semaphore:
        results.append(f"start {name}")
        time.sleep(0.5)  # simulate async work
        results.append(f"done {name}")

def main():
    sem = threading.Semaphore(2)  # max 2 …
14 0 Open
System design patterns medium

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.

architecture layered design-pattern
Python
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}")
     …
12 0 Open
System design patterns medium

Inbox pattern consumer dedupe mock in Python

Implements a mock inbox consumer that deduplicates incoming messages by ID, with automatic eviction of old seen IDs to prevent unbounded memory growth.

deduplication inbox-pattern dataclasses
Python
import json
from collections import deque
from dataclasses import dataclass, field
from hashlib import sha256
from typing import Any


@dataclass
class InboxConsumer:
    max_seen: int = 1000
    seen_ids: set = field(default_factory=set)
    seen_history: deque = field(default_factory=deque)

    def _mark_seen(self,…
13 0 Open
System design patterns medium

Simulate a Leaky Bucket Rate Limiter in Python

This code implements a leaky bucket rate limiter that drains at a fixed rate and accepts or rejects incoming requests based on capacity.

rate limiting leaky bucket simulation
Python
import time
from collections import deque


class LeakyBucket:
    """Simulates a leaky bucket rate limiter with a fixed drain rate."""
    def __init__(self, capacity, drain_rate_per_sec):
        self.capacity = capacity
        self.drain_rate = drain_rate_per_sec
        self.water = 0.0
        self.last_refill =…
13 0 Open
API design & gRPC medium

Build a Bulk Array POST Mock Server in Python

Creates an HTTP mock server that accepts POST requests with a JSON array and returns incremental IDs for each item.

http-server mock-api rest
Python
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse

class MockHandler(BaseHTTPRequestHandler):
    def do_POST(self):
        if urlparse(self.path).path != "/bulk":
            self.send_response(404)
            self.end_headers()
            return

        cont…
17 0 Open
API design & gRPC medium

How to Build an Idempotency-Key POST Handler in Python

Python HTTP server mock that accepts POST requests and deduplicates them using an Idempotency-Key header, returning the same response for repeated calls.

http-server idempotency api-mock
Python
import hashlib
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse


class MockAPI(BaseHTTPRequestHandler):
    responses = {}

    def do_POST(self):
        length = int(self.headers.get("Content-Length", 0))
        body = self.rfile.read(length).decode("utf-8")
…
14 0 Open
API design & gRPC medium

How to Filter Query Parameters by Operator in Python

Parse a URL query string and keep only parameters with allowed comparison operators like eq, gt, and lt.

query-parsing url api
Python
from urllib.parse import urlparse, parse_qs

def filter_operators(query_string, allowed=("eq", "gt", "lt")):
    parsed = urlparse(query_string)
    params = parse_qs(parsed.query)
    filtered = {}
    for key, values in params.items():
        if "__" in key:
            field, op = key.rsplit("__", 1)
            i…
12 0 Open
API design & gRPC medium

How to Implement Content Negotiation with JSON and XML in Python

Build an HTTP server that returns JSON or XML responses based on the client's Accept header, with a 406 response for unsupported formats.

http-server content-negotiation json
Python
import json
import xml.etree.ElementTree as ET
from http.server import BaseHTTPRequestHandler, HTTPServer


class RequestHandler(BaseHTTPRequestHandler):
    def do_GET(self):
        data = {"message": "Hello, world!"}
        accept_header = self.headers.get("Accept", "")

        if "application/json" in accept_hea…
11 0 Open
API design & gRPC medium

How to Mock a Webhook Subscribe Callback URL in Python

Mock a webhook subscribe callback URL using Python's http.server to receive and parse POST requests sent by webhook providers.

webhook http-server mock
Python
import json
from http.server import BaseHTTPRequestHandler, HTTPServer

class WebhookHandler(BaseHTTPRequestHandler):
    def do_POST(self):
        content_length = int(self.headers.get('Content-Length', 0))
        payload = json.loads(self.rfile.read(content_length)) if content_length else {}
        
        print…
15 0 Open
API design & gRPC medium

How to Validate Request Body JSON Against a Schema in Python

Build a lightweight schema validator to check required fields, types, string lengths, allowed values, and nested objects in a JSON request body.

api-validation json schema-validation
Python
import json


def validate_against_schema(data, schema, path=""):
    errors = []

    if not isinstance(data, dict):
        errors.append(f"{path}: expected object, got {type(data).__name__}")
        return errors

    for field, rules in schema.items():
        field_path = f"{path}.{field}" if path else field

  …
15 0 Open

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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.