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'[!@#$%^&*(),.?":…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}[-…How to Escape HTML in Python
This code demonstrates how to use Python's `html.escape` function to safely encode user input for display in HTML, preventing XSS attacks.
import html
def escape_user_input(user_input: str) -> str:
"""Escape HTML-sensitive characters for safe display."""
return html.escape(user_input)
if __name__ == "__main__":
sample_user_input = '<script>alert("XSS")</script> & \'quotes\''
safe_output = escape_user_input(sample_user_input)
print("…How to Mask Credit Card Middle Digits in Python
Mask the middle digits of credit card numbers in a string, keeping only the first 8 and last 4 digits, using regular expressions.
import re
def mask_credit_card(text: str) -> str:
pattern = re.compile(r'(\d{4}[-\s]?)(\d{4}[-\s]?)(\d{4}[-\s]?)(\d{4})')
return pattern.sub(lambda m: m.group(1) + m.group(2) + '****' + m.group(4), text)
if __name__ == "__main__":
sample = "Card: 1234-5678-9012-3456 and 1111 2222 3333 4444"
print(mas…Browse by section
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Strings & text — Python code examples
What you will find here
This page collects strings & text snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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.