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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…
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}[-…
Validate email format with regex in Python
A Python function using a regex pattern to validate simple email formats, returning True or False for each input.
import re
def is_valid_email(email):
pattern = r'^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$'
return bool(re.match(pattern, email))
if __name__ == "__main__":
test_emails = [
"user@example.com",
"first.last@sub.domain.org",
"invalid-email",
"user@.com",
"user@…
How to Sort a List of Dictionaries by Key with a Lambda in Python
Sort a list of dictionaries ascending or descending by one of their keys using sorted() with a lambda as the key function — a beginner-friendly pattern.
def get_students():
return [
{"name": "alice", "score": 85},
{"name": "bob", "score": 92},
{"name": "carol", "score": 78},
{"name": "dave", "score": 92},
]
students = get_students()
sorted_by_score = sorted(students, key=lambda s: s["score"])
print("Sorted by score (ascending)…
How to Use a Dispatch Table in Python (Map Strings to Functions)
Maps string command names to callable functions in a dictionary, then dispatches calls safely with error handling.
def add(a, b):
return a + b
def subtract(a, b):
return a - b
def multiply(a, b):
return a * b
def divide(a, b):
if b == 0:
raise ValueError("Division by zero")
return a / b
dispatch = {
"add": add,
"subtract": subtract,
"multiply": multiply,
"divide": divide,
}
def…
How to Handle ValueError with try except in Python
Shows a beginner-friendly try/except pattern that catches ValueError when converting text to an integer, prints a helpful message, and returns None instead of crashing.
def parse_number(text):
try:
return int(text)
except ValueError:
print(f"ValueError: '{text}' is not a valid integer.")
return None
if __name__ == "__main__":
user_input = "abc"
result = parse_number(user_input)
print(f"Parsing '{user_input}' returned: {result}")
vali…
How to Return Success or Error as a Tuple in Python (Result Type Pattern)
Use a (bool, value) tuple as a lightweight Result type to return either a successful result or a descriptive error message from a Python function.
def divide(dividend: float, divisor: float) -> tuple[bool, float | str]:
"""Return (True, result) on success, (False, error_message) on failure."""
if divisor == 0:
return False, "Error: Division by zero"
return True, dividend / divisor
if __name__ == "__main__":
# Success case
success, r…
How to Test Exceptions in Python with pytest.raises
Learn the pytest.raises pattern to assert that specific exceptions are raised and validate their messages.
import pytest
def divide(a: int, b: int) -> float:
if b == 0:
raise ValueError("Cannot divide by zero")
return a / b
def test_divide_by_zero_raises():
with pytest.raises(ValueError, match="Cannot divide by zero"):
divide(10, 0)
def test_divide_by_zero_raises_exact_match():
with py…
How to Use Optional Return in Python Instead of Raising Exceptions
A Python function returns None for missing dictionary keys instead of raising KeyError, enabling graceful lookup handling with type hints.
from typing import Optional
def find_user(users: dict, user_id: int) -> Optional[dict]:
"""
Look up a user by ID. Returns the user dict if found,
otherwise returns None instead of raising KeyError.
"""
return users.get(user_id)
def main() -> None:
users = {
1: {"name": "Alice", "ema…
How to Validate an Email Address and Raise ValueError in Python
This code defines a validate_email function that checks an email address against a regex pattern and several rules, raising ValueError with a specific reason when invalid.
import re
def validate_email(email: str) -> str:
"""Validate an email address and return it if valid, otherwise raise ValueError."""
if not isinstance(email, str):
raise ValueError("Email must be a string")
if len(email) > 254:
raise ValueError("Email length exceeds 254 characters")
#…
How to List Files Matching a Glob Pattern in Python
Uses pathlib.Path.glob to find and sort all files matching a glob pattern like *.py in a directory.
from pathlib import Path
def list_files_matching(pattern: str, directory: str = ".") -> list[str]:
"""Return sorted list of file paths matching the glob pattern in a directory."""
return sorted(Path(directory).glob(pattern))
if __name__ == "__main__":
# Example: list all .py files in current directory
…
Group Data by Key in Python with Dictionaries and Sets
Group items into a dictionary of sets using a key function, a beginner-friendly pattern for organizing data by categories.
def group_data(items, key_func):
"""Group items into a dictionary of sets based on a key function."""
grouped = {}
for item in items:
key = key_func(item)
if key not in grouped:
grouped[key] = set()
grouped[key].add(item)
return grouped
if __name__ == "__main__":
…
Composition over Inheritance: How to Build a Wallet Account in Python
Demonstrates composition by wrapping a WalletAccount class in an AuditedWallet decorator-like class to add behavior without changing the original class.
class WalletAccount:
def __init__(self, owner, balance=0.0):
self.owner = owner
self.balance = balance
def deposit(self, amount):
if amount <= 0:
raise ValueError("Deposit must be positive")
self.balance += amount
return self.balance
def withdraw(self, …
How to Build a Fluent Interface with the Builder Pattern in Python
Learn to implement a fluent builder pattern in Python by chaining methods that return self, enabling readable object construction.
class Pizza:
def __init__(self):
self.size = None
self.toppings = []
self.crust = None
def set_size(self, size):
self.size = size
return self
def add_topping(self, topping):
self.toppings.append(topping)
return self
def set_crust(self, crust):
…
How to Implement a Singleton Class in Python
This code demonstrates a classic Singleton pattern in Python by overriding __new__ to ensure only one instance of the class is created, even when instantiated multiple times.
class Singleton:
_instance = None
def __new__(cls):
if cls._instance is None:
cls._instance = super().__new__(cls)
return cls._instance
def __init__(self):
self.value = 0
if __name__ == "__main__":
s1 = Singleton()
s2 = Singleton()
s1.value = 42
print…
How to Implement the Decorator Pattern in Python to Add Behavior
This Python code demonstrates the decorator pattern by wrapping a function to add logging behavior without modifying the original function.
import functools
def logger(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
print(f"Calling {func.__name__} with {args} {kwargs}")
result = func(*args, **kwargs)
print(f"{func.__name__} returned {result}")
return result
return wrapper
@logger
def add(a, b):
…
Python Adapter Class: Wrap Legacy Interface
Convert a legacy system's interface into a modern one using the Adapter pattern in Python, translating method calls and data formats.
class LegacySystem:
"""Legacy interface - old method names and parameter format."""
def query_employee_info(self, emp_id, emp_name):
return f"Legacy: {emp_id} - {emp_name}"
def update_employee_department(self, emp_id, department_code):
return f"Legacy: Updated {emp_id} to dept {department_…
Python Factory Method: Create Shapes by Type String
A factory method that maps a type string to a concrete shape class and returns an instance, with runtime error handling.
class Shape:
def draw(self):
raise NotImplementedError
class Circle(Shape):
def draw(self):
return "Drawing a circle"
class Square(Shape):
def draw(self):
return "Drawing a square"
class Triangle(Shape):
def draw(self):
return "Drawing a triangle"
class ShapeFact…
How to Generate Cartesian Product Combinations in Python
Use itertools.product to generate every combination across multiple iterables, a pattern common for product variant generation.
from itertools import product
def generate_cartesian_combinations(*iterables):
"""Generate all Cartesian product combinations of given iterables."""
return list(product(*iterables))
if __name__ == "__main__":
colors = ["red", "green", "blue"]
sizes = ["S", "M", "L"]
styles = ["t-shirt", "hoodie"]…
Normalize Data in Python with Comprehensions and Generators
Clean a list by dropping None values with a comprehension, then min-max normalize it using a lazy generator expression — a beginner-friendly data preparation pattern.
import statistics
# Sample raw data including missing and outlier-ish values
raw = [22, 18, None, 25, 30, 19, 22, 17, None, 28, 24]
# Clean the data: drop None values using a list comprehension
clean = [x for x in raw if x is not None]
# Normalize using min-max scaling with a generator expression
min_val = min(clea…
How to Kill Zombie Processes Matching a Name in Python
Scans running processes with ps, finds zombies whose command name matches a pattern, and attempts to kill them with SIGKILL.
import subprocess
import re
import signal
def find_zombies(name_pattern):
"""Find PIDs of zombie processes matching the given pattern."""
result = subprocess.run(["ps", "-eo", "pid,stat,comm"], capture_output=True, text=True)
zombies = []
for line in result.stdout.splitlines()[1:]: # Skip header
…
Fan Out Records to Multiple Sinks in Python
Distribute the same records across multiple target sinks (database, API, queue, etc.) using a defaultdict-based fan-out pattern.
import json
from collections import defaultdict
SINKS = ["database", "api", "message_queue", "data_lake", "monitoring"]
def fan_out(records, *sinks):
dist = defaultdict(list)
for record in records:
for sink in sinks:
dist[sink].append(record)
return dict(dist)
if __name__ == "__main_…
How to Deduplicate Events with At-Least-Once Delivery in Python
Implements an exactly-once processing pattern for at-least-once event delivery by tracking seen event IDs in a set, skipping duplicates.
seen_ids = set()
def process_event(event_id: str, payload: dict) -> dict:
"""Process an event exactly once, ignoring duplicates."""
if event_id in seen_ids:
return {"status": "duplicate", "event_id": event_id}
seen_ids.add(event_id)
return {"status": "processed", "event_id": event_id, **payloa…
How to Generate Git LFS Extension Patterns in Python
This script builds mock Git LFS file patterns for common geospatial extensions and filters them based on compression suffixes.
import itertools
import re
LFS_EXTENSIONS = {".csv", ".geojson", ".tif", ".shp", ".gpkg"}
def build_mock_lfs_pattern(base_name="data_usgs_lidar"):
patterns = []
for ext in sorted(LFS_EXTENSIONS):
for variant in (("", ".lz4"), (".compressed",), (".b", ".a"), ("_v1", ".zip")):
full_pattern …
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