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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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…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…Detect Outliers in CSV Data Using Z-Score in Python
Read a CSV file and detect outliers in a numeric column by computing z-scores, flagging those exceeding a given threshold — no machine learning required.
import csv
import statistics
from math import sqrt
def detect_outliers(csv_path, column_name, threshold=2.0):
"""Detect outliers in a numeric column using z-score method."""
values = []
with open(csv_path, 'r', newline='') as f:
reader = csv.DictReader(f)
if column_name not in reader.field…Find Duplicate Web Pages by Content Similarity in Python
Compute SHA-256 hashes of file contents to detect and report duplicate HTML pages or any files in a directory.
import hashlib
import os
from collections import defaultdict
def get_file_hash(filepath):
"""Compute SHA-256 hash of file contents."""
sha256 = hashlib.sha256()
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
sha256.update(chunk)
return sha256.hexdiges…How to Detect Hardcoded Secrets in Python Source Code
A Python utility that scans source code for common hardcoded secrets like API keys, passwords, tokens, and AWS credentials using regex patterns.
import re
def detect_secrets(text):
"""Detect potential hardcoded secrets in source code."""
patterns = {
'api_key': r'(?i)(api[_-]?key|apikey)\s*[=:]\s*["\']([^"\']+)["\']',
'password': r'(?i)(password|passwd)\s*[=:]\s*["\']([^"\']+)["\']',
'token': r'(?i)(\b(token|secret)\b)\s*[=:]\s…Create a Python Script That Detects Website Technology Stack Automatically
This script sends an HTTP request to a URL and inspects headers and HTML content to identify technologies like servers, frameworks, and JavaScript libraries.
import requests
from re import search
def detect_tech_stack(url):
tech_stack = []
try:
response = requests.get(url, timeout=5, headers={'User-Agent': 'Mozilla/5.0'})
headers = response.headers
html = response.text.lower() if response.text else ''
# Check server header
…Detect and Remove Blurry Images in Python with OpenCV
Automatically scan a directory of images, detect blur using Laplacian variance, and remove blurry images with a dry-run option for safety.
from pathlib import Path
import cv2
import numpy as np
def is_blurry(image_path, threshold=100.0):
"""
Detect if an image is blurry using Laplacian variance.
Returns True if blurry, False otherwise.
"""
img = cv2.imread(str(image_path), cv2.IMREAD_GRAYSCALE)
if img is None:
return True…Browse by section
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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.
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- 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.