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Python Code Samples

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

125 matches
Algorithms & data structures easy

Rearrange array alternately max min in Python

Rearranges a sorted list so its elements alternate between the current maximum and current minimum using two pointers in O(n) time.

two-pointers array sorting
Python
def rearrange_alternately(arr):
    """
    Rearrange sorted array so elements alternate: max, min, next max, next min...
    Returns a new list in O(n) time using O(n) space.
    """
    n = len(arr)
    result = []
    left, right = 0, n - 1
    while left <= right:
        if left == right:
            result.appen…
14 0 Open
Comprehensions & generators easy

Build a lazy generator to read file lines in Python

Create a generator function that yields file lines one at a time, avoiding loading the entire file into memory, and demonstrate its lazy processing.

generator file-io lazy
Python
def lazy_lines(filepath):
    """Yield lines from a file one at a time without loading the whole file into memory."""
    with open(filepath, 'r', encoding='utf-8') as file:
        for line in file:
            yield line.rstrip('\n')


if __name__ == "__main__":
    # Create a sample file to demonstrate
    sample_c…
14 0 Open
Comprehensions & generators easy

Generate UUID4 Values with a Python Generator

This code defines a generator function that yields mock UUID4 values, allowing you to stream unique identifiers one at a time.

uuid generators streaming
Python
import uuid

def generate_uuids(count=5):
    """Generate a stream of mock UUID4 values."""
    for _ in range(count):
        yield uuid.uuid4()

if __name__ == "__main__":
    # Generate and print 5 UUIDs
    for uid in generate_uuids(5):
        print(uid)
15 0 Open
Comprehensions & generators easy

How to Parse CSV Rows as Generator Dicts in Python

Reads a CSV file and yields each row as a dictionary one at a time using a generator, so the file is processed lazily.

csv generator parsing
Python
import csv
from pathlib import Path

def csv_to_dicts(filepath):
    with open(filepath, mode="r", newline="", encoding="utf-8") as file:
        reader = csv.DictReader(file)
        for row in reader:
            yield row

if __name__ == "__main__":
    sample_csv = Path("sample_data.csv")
    sample_csv.write_text…
13 0 Open
AI & LLM integration patterns easy

How to Log Prompts and Completions as JSONL Audit Files in Python

Read a JSONL file of LLM prompt–completion pairs, compute totals and averages, then write an audit summary with timestamps.

jsonl audit llm
Python
import json
from pathlib import Path
from datetime import datetime


def audit_jsonl(filepath):
    logs = []
    with open(filepath, encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            entry = json.loads(line)
            logs.ap…
15 0 Open
AI & LLM integration patterns easy

How to Serialize Chat Messages to a JSON File in Python

Writes a list of chat message dicts to a JSON file with metadata like export time and message count.

json serialization chat
Python
import json
from pathlib import Path
from datetime import datetime

def serialize_messages(messages, output_path):
    data = {
        "exported_at": datetime.now().isoformat(),
        "count": len(messages),
        "messages": messages
    }
    Path(output_path).write_text(
        json.dumps(data, indent=2, ensu…
16 0 Open
AI & LLM integration patterns easy

How to Stream Tokens from a Mock LLM in Python

Simulate real-time LLM streaming by yielding tokens one at a time with a delay, making it easy to test streaming UIs.

generator llm streaming
Python
import time
from typing import Generator


def stream_tokens(text: str, delay: float = 0.05) -> Generator[str, None, None]:
    """Simulate an LLM streaming tokens word by word."""
    for word in text.split():
        yield word
        time.sleep(delay)


if __name__ == "__main__":
    sample = "Hello world! This is…
15 0 Open
Automation & scripting easy

Aggregate Log Errors Count by Hour in Python

Counts ERROR log lines per hour using regex and Counter, returning a sorted dictionary of hourly totals.

logs regex counter
Python
import re
from collections import Counter
from datetime import datetime

def aggregate_errors_by_hour(log_lines):
    pattern = re.compile(r'^(\d{4}-\d{2}-\d{2} \d{2}):\d{2}:\d{2}.*ERROR')
    hourly_counts = Counter()
    
    for line in log_lines:
        match = pattern.match(line)
        if match:
            ho…
21 0 Open
Automation & scripting easy

Build a Live Countdown Timer for Events in Python

A Python script that displays a real-time countdown to a target date and time, updating every second in the console.

datetime countdown timers
Python
import datetime
import time

def countdown(event_name, target_datetime):
    """Displays a live countdown to a target datetime."""
    while True:
        now = datetime.datetime.now()
        remaining = target_datetime - now
        if remaining.total_seconds() <= 0:
            print(f"\n🚀 {event_name} is happening…
46 0 Open
Automation & scripting easy

Generate Random Fake User Data for Testing in Python

This code generates a list of fake user dictionaries with random names, emails, ages, and timestamps using the Python standard library for testing purposes.

testing random data-generation
Python
import json
import random
import string
from datetime import datetime, timedelta

def generate_user_data(num_users=1):
    first_names = ["Alice", "Bob", "Charlie", "Diana", "Eve"]
    last_names = ["Smith", "Johnson", "Brown", "Taylor", "Wilson"]
    domains = ["example.com", "test.org", "demo.net"]
    
    users = …
39 0 Open
Automation & scripting easy

How to Backup an SQLite Database with a Timestamp in Python

Backs up an SQLite database file to a timestamped copy using the sqlite3 backup API.

sqlite backup automation
Python
import sqlite3
import shutil
from datetime import datetime
from pathlib import Path

def backup_database(db_path: str, backup_dir: str = "backups") -> Path:
    db = Path(db_path)
    backup_folder = Path(backup_dir)
    backup_folder.mkdir(exist_ok=True)
    
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
 …
14 0 Open
Automation & scripting easy

How to Filter Docker Containers for Pruning in Python

Simulate Docker's container prune by filtering a JSON list for exited containers older than a cutoff, returning pruned IDs and space freed.

docker json datetime
Python
import json
from datetime import datetime, timedelta


def parse_docker_ps(json_output: str, older_than_hours: int = 24) -> list:
    containers = json.loads(json_output)
    cutoff = datetime.now() - timedelta(hours=older_than_hours)
    return [
        c for c in containers
        if datetime.fromisoformat(c["crea…
13 0 Open
Automation & scripting easy

How to Find Stale GitHub Issues in Python

Filter a list of GitHub issues to find those not updated within a configurable number of days using Python datetime arithmetic.

github issues automation
Python
import os
from datetime import datetime, timezone, timedelta
import re

# Simulated GitHub issue data structure
SAMPLE_ISSUES = [
    {"number": 101, "title": "Login button not working", "updated_at": "2025-06-01T12:00:00Z", "assignee": "alice"},
    {"number": 102, "title": "Fix database migration error", "updated_at…
36 0 Open
Automation & scripting easy

How to generate website performance reports from HTTP requests in Python

Measure and report website load time, status code, and content size using Python's standard library.

http performance urllib
Python
import urllib.request
import time

def measure_website_load_time(url):
    """Measures total loading time of a website."""
    start_time = time.time()
    try:
        with urllib.request.urlopen(url, timeout=10) as response:
            content = response.read()
            status_code = response.status
            …
39 0 Open
Automation & scripting easy

Monitor Website Uptime with Python

Periodically check if a website is reachable and its HTTP status is 200, logging the status with timestamps.

monitoring uptime requests
Python
import requests
import time

def check_website(url):
    try:
        response = requests.get(url, timeout=5)
        if response.status_code == 200:
            return True
        else:
            return False
    except requests.ConnectionError:
        return False
    except requests.Timeout:
        return Fals…
39 0 Open
Automation & scripting easy

Parse WHOIS Data with Python Regex

Extract domain registration fields from a mock WHOIS record using regex and compute days until expiration.

whois regex parsing
Python
import re
from datetime import datetime


def parse_whois(whois_text: str) -> dict:
    """Extract key registration fields from a mock WHOIS record."""
    patterns = {
        "domain": r"Domain Name:\s*(.+)",
        "registrar": r"Registrar:\s*(.+)",
        "creation_date": r"Creation Date:\s*(.+)",
        "expir…
12 0 Open
Automation & scripting easy

Parse cron expression and compute next run datetime in Python

Parse a 5-field cron expression and compute the next matching datetime starting from a given base time.

cron datetime scheduling
Python
from datetime import datetime, timedelta
import re

def parse_cron_and_next_run(cron_expr, base_time=None):
    """Parse a cron expression and compute the next run time."""
    if base_time is None:
        base_time = datetime.now().replace(second=0, microsecond=0)

    fields = cron_expr.split()
    if len(fields) !…
11 0 Open
Automation & scripting easy

Schedule Daily Task in Python

Use the schedule library to queue a daily task at a fixed time, then simulate a loop that checks for pending jobs.

schedule cron timers
Python
import schedule
import time
from datetime import datetime

def daily_task():
    print(f"Task executed at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")

schedule.every().day.at("10:30").do(daily_task)

if __name__ == "__main__":
    for _ in range(3):
        schedule.run_pending()
        time.sleep(1)
12 0 Open
Data pipelines & processing easy

Generate a Mock CDC Changelog in Python

Simulate a CDC changelog with INSERT, UPDATE, and DELETE operations, timestamps, and record snapshots for testing data pipelines.

cdc changelog mock-data
Python
import json
from datetime import datetime, timedelta


def generate_mock_changelog(records, operations=("INSERT", "UPDATE", "DELETE")):
    """Simulate a CDC changelog from a list of record snapshots."""
    base_time = datetime(2025, 1, 1, 8, 0, 0)
    changelog = []
    for idx, record in enumerate(records):
       …
15 0 Open
Data pipelines & processing easy

Group Python Events into Sessions with a Gap Timeout

Groups timestamped events into sessions, starting a new session when the time gap exceeds a specified timeout.

sessions grouping datetime
Python
from itertools import groupby
from datetime import datetime, timedelta

def session_window_group(events, gap_seconds=300):
    """Group events into sessions where gap > gap_seconds starts a new session."""
    if not events:
        return []
    
    events = sorted(events, key=lambda x: x[0])
    sessions = []
    c…
13 0 Open
Data pipelines & processing easy

How to Convert Data Types in a Python Data Pipeline

Demonstrates a simple Python data pipeline that converts string values to proper types (bool, int, float, datetime) and outputs structured JSON.

data-pipeline type-conversion json
Python
import json
from datetime import datetime

def convert_value(value):
    """Convert string values to appropriate Python types."""
    if value.lower() == "true":
        return True
    if value.lower() == "false":
        return False
    if value.isdigit():
        return int(value)
    try:
        return float(val…
11 0 Open
Data pipelines & processing easy

How to Implement Incremental Load with Watermark by updated_at in Python

Load only new or changed rows into SQLite by comparing an updated_at timestamp against a stored watermark, returning counts and the new watermark.

incremental-load watermark sqlite
Python
import sqlite3
from datetime import datetime, timedelta


def watermark_incremental_load(db_path, table_name, last_watermark, source_data):
    """Load only rows with updated_at greater than the last watermark."""
    conn = sqlite3.connect(db_path)
    cursor = conn.cursor()

    # Create table if it doesn't exist
  …
12 0 Open
Data pipelines & processing easy

How to List Failed Records in a Dead Letter Queue Mock in Python

A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.

dead-letter-queue json logging
Python
import json
from datetime import datetime, timedelta
import random


class DeadLetterQueue:
    def __init__(self):
        self.failed_records = []

    def add_failed_record(self, record_id, payload, error_message):
        self.failed_records.append({
            "record_id": record_id,
            "payload": paylo…
13 0 Open
Data pipelines & processing easy

How to Parse Data in Python: A Beginner's Helper

This helper parses a JSON payload, extracts user names, emails, and signup dates, then summarizes the results.

json parsing data-processing
Python
import json
from datetime import datetime
from typing import Dict, List


def parse_data(payload: str) -> Dict[str, List]:
    """Parse a JSON payload and extract useful fields."""
    raw = json.loads(payload)
    users = raw.get("users", [])

    parsed = {
        "names": [],
        "emails": [],
        "signup_…
15 0 Open

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Guide: free Python code samples library

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.

How to use this library

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. 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.