Python Code
Samples
Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Strings & text
Format, split, join, parse, and clean text — everyday Python string patterns.
Automatically Detect Weak Passwords from Large Password Lists in Python
This Python script identifies weak passwords from a list by checking length, common patterns, sequential characters, and uniform characters, returning those that fail the security checks.
import re
COMMON_PASSWORDS_FILE = "common_passwords.txt"
def is_weak(password):
# Check length
if len(password) < 8:
return True
# Check for common patterns
if password.lower() in {"password", "123456", "qwerty", "letmein", "admin", "welcome"}:
return True
# Check for sequential c…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'[!@#$%^&*(),.?":…Convert Natural Language Dates to Datetime in Python
Parse common natural language date phrases like 'tomorrow' or 'in 3 days' into Python datetime objects using regex and timedelta.
from datetime import datetime, timedelta
import re
def parse_natural_date(text: str) -> datetime:
"""Convert common natural language date expressions to datetime objects."""
now = datetime.now()
text = text.lower().strip()
# Handle relative dates
patterns = {
r"today": now,
r"…How to Detect Expired Domains Using Python
Parse a list of domain registration data and compare expiry dates to today to find expired domains.
import datetime
# List of test domains with fake registration and expiry dates
# Format: (domain, registration_date, expiry_date)
test_domains = [
('example.com', '2020-01-15', '2024-01-15'), # Expired
('google.com', '1997-09-15', '2026-09-15'), # Still active
('test-site.org', '2019-06-01', '2023-06-0…How to Detect PII in Documents Using Python
Use regex patterns to automatically detect emails, phone numbers, SSNs, and credit card numbers in text documents.
import re
from typing import List, Dict
def detect_pii(text: str) -> Dict[str, List[str]]:
patterns = {
"email": r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}",
"phone": r"\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}",
"ssn": r"\b\d{3}-\d{2}-\d{4}\b",
"credit_card": r"\b\d{4}[- ]?\d{4}[-…Lists & loops
Iterate, transform, and combine sequences with readable loop patterns.
Functions & basics
Reusable building blocks — parameters, returns, scope, and clear function design.
Calculate Time Difference Across Time Zones in Python
Compute the current time difference in hours between two time zones given their UTC offsets using Python's datetime and timezone modules.
from datetime import datetime, timezone, timedelta
def time_difference(from_tz_offset, to_tz_offset):
"""
Calculate time difference in hours between two time zones given their offsets from UTC.
Offsets are in hours (e.g., -5 for EST, +5.5 for IST).
"""
tz1 = timezone(timedelta(hours=from_tz_offset…Compound interest calculator in Python
Compute future investment value with the compound interest formula and a readable year-by-year loop.
def future_value(
principal: float,
annual_rate: float,
years: int,
compounds_per_year: int = 12,
) -> float:
"""Return balance after compound interest (rounded to cents)."""
rate_per_period = annual_rate / compounds_per_year
periods = compounds_per_year * years
amount = principal * (1 …Files & data
Read and write files safely; parse JSON, CSV, and common text formats.
Audit File Permissions Across a Project in Python
Walks through every file and directory in a project tree and prints POSIX permissions plus owner UID.
import os
import stat
from pathlib import Path
def audit_file_permissions(project_root):
"""Walk through project_root and print path, owner, and permissions for every file."""
results = []
for root, dirs, files in os.walk(project_root):
for name in files + dirs:
full_path = os.path.joi…Automatically Detect Corrupted Files Using SHA-256 Checksums in Python
Compute SHA-256 checksums of files and compare them to detect corruption in Python.
import hashlib
import os
def compute_sha256(filepath: str) -> str:
"""Compute SHA-256 checksum of a file."""
sha256 = hashlib.sha256()
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
sha256.update(chunk)
return sha256.hexdigest()
def validate_file_int…Automatically Highlight Data Validation Errors Inside Excel Files in Python
Load an Excel file with openpyxl, iterate over cells, and highlight invalid data (empty, negative) with a red fill and error message.
import openpyxl
from openpyxl.styles import PatternFill
from pathlib import Path
def highlight_validation_errors(filepath: str, output_path: str = None):
wb = openpyxl.load_workbook(filepath)
red_fill = PatternFill(start_color="FF0000", end_color="FF0000", fill_type="solid")
for sheet in wb.worksheet…Build a Command-Line To-Do List Application with Data Persistence in Python
A persistent command-line to-do list that saves tasks as JSON, supporting add, show, toggle done, and quit commands.
import json
import os
TODO_FILE = "todos.json"
def load_todos():
if not os.path.exists(TODO_FILE):
return []
with open(TODO_FILE, "r") as f:
return json.load(f)
def save_todos(todos):
with open(TODO_FILE, "w") as f:
json.dump(todos, f, indent=2)
def show_todos(todos):
if not…Build a Personal Work Hours Tracker in Python
A Python class that logs daily work hours to a CSV file and produces a weekly summary of total hours worked.
import csv
from pathlib import Path
from datetime import datetime, date
class WorkHoursTracker:
def __init__(self, file_path="work_hours.csv"):
self.file_path = Path(file_path)
if not self.file_path.exists():
with open(self.file_path, "w", newline="") as f:
writer = csv…Build a Python Script That Detects and Deletes Empty Files Across Folders
A Python script that recursively finds and removes all zero-byte files across nested directories, returning a list of deleted paths.
import os
from pathlib import Path
def find_and_delete_empty_files(root_dir: str) -> list:
"""Find and delete all empty files under root_dir. Returns list of deleted paths."""
deleted = []
for file_path in Path(root_dir).rglob('*'):
if file_path.is_file() and file_path.stat().st_size == 0:
…Algorithms & data structures
Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.
AI & LLM integration patterns
Call LLM APIs, structure prompts, parse responses, and ship AI features safely.
Automation & scripting
CLI tools, scheduled jobs, filesystem tasks, and glue scripts that save time.
Automatically Clean Temporary Files from Applications Using Python
A Python script that safely deletes temporary files from common application temp directories across Windows, Linux, and macOS, tracking cleaned count and disk space.
import os
import shutil
import tempfile
import platform
def clean_application_temp_files():
"""Delete common temporary file locations safely."""
system = platform.system()
temp_dirs = []
if system == "Windows":
temp_dirs.extend([
os.path.join(os.getenv("LOCALAPPDATA"), "Temp"),
…Automatically Download the Latest Software Release from GitHub with Python
Use the GitHub API to fetch the latest release metadata and download the first asset (binary or archive) to a local directory.
import requests
import sys
from pathlib import Path
def download_latest_release(owner: str, repo: str, output_dir: str = ".") -> None:
"""Download the latest release asset from a GitHub repository."""
url = f"https://api.github.com/repos/{owner}/{repo}/releases/latest"
response = requests.get(url)
res…Automatically Generate Charts from CSV Files with One Command
Read a CSV file with headers, extract the first two numeric columns, and save a matplotlib line chart as a PNG image.
import csv
import sys
from pathlib import Path
import matplotlib.pyplot as plt
def generate_chart(csv_path: str) -> None:
"""Read a CSV file with headers and plot the first two numeric columns."""
data = []
with open(csv_path, 'r', newline='') as f:
reader = csv.reader(f)
headers = next(re…Automatically Generate Hardware Inventory Reports in Python
Generate a system hardware report including OS version, CPU cores, RAM, and disk usage using platform and psutil.
import platform
import psutil # requires: pip install psutil
from datetime import datetime
def generate_hardware_report():
report_lines = []
report_lines.append(f"Report Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
report_lines.append(f"System: {platform.system()} {platform.release()} ({pl…Automatically Log CPU, RAM, and Disk Usage Every Minute in Python
This script logs CPU, RAM, and disk usage to a CSV file every 60 seconds using psutil and Python's standard library.
import psutil
import time
import csv
from pathlib import Path
LOG_FILE = Path("system_usage_log.csv")
INTERVAL_SECONDS = 60
def log_system_usage():
"""Write CPU, RAM, and disk usage to CSV every minute."""
file_exists = LOG_FILE.exists()
with open(LOG_FILE, mode="a", newline="") as f:
writer = cs…Batch Rename Hundreds of Files in Python
Rename all files with a given extension inside a folder using a sequential counter and a custom prefix.
import os
from pathlib import Path
def batch_rename_files(directory: str, prefix: str, extension: str = ".txt") -> None:
"""Rename all files with given extension in directory to prefix_{counter}.ext."""
path = Path(directory)
if not path.is_dir():
print(f"Directory '{directory}' does not exist.")
…Data pipelines & processing
ETL-style flows, batch transforms, validation, and moving data between formats.
Build a Python Utility That Detects Duplicate Records Across Multiple Excel Sheets
A Python utility that uses pandas to find overlapping records across different Excel sheets based on specified key columns.
import pandas as pd
from pathlib import Path
def find_duplicate_records_across_sheets(file_path: str, key_columns: list, sheet_names: list) -> dict:
"""
Detect duplicate records across multiple Excel sheets based on specified key columns.
Args:
file_path: Path to the Excel file
key_co…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".
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…How to Find Missing Values in Large Datasets in Python
Analyze missing values across multiple large pandas DataFrames with counts and percentages.
import pandas as pd
import numpy as np
def find_missing_values_summary(datasets):
"""Analyze missing values across multiple datasets (dict of name: DataFrame)."""
summary = {}
for name, df in datasets.items():
missing_count = df.isnull().sum()
total_rows = len(df)
missing_pct = (mi…Git + Python
Automate Git from Python — diffs, hooks, release tags, and repo housekeeping.
Cloud + Python
Cloud SDK patterns — storage, serverless handlers, secrets, and deployment helpers.
Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
Testing & modern typing
pytest basics, mocks, type hints, TypedDict, Protocol, and static-checking patterns.
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
- Pick a topic section — strings, lists, files, functions, and more
- 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.