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How to Invalidate Cache When Arguments Change in Python
A memoization decorator that caches function results keyed by arguments, automatically invalidating when inputs change.
from functools import wraps
def memoize(func):
cache = {}
@wraps(func)
def wrapper(*args, **kwargs):
key = (args, tuple(sorted(kwargs.items())))
if key not in cache:
cache[key] = func(*args, **kwargs)
return cache[key]
return wrapper
@memoize
def expensiv…Collect Multiple Validation Errors in Python Before Raising
A chainable Validator class that accumulates all validation errors and raises them together in a single exception.
class ValidationError(Exception):
pass
class Validator:
def __init__(self):
self.errors = []
def validate_required(self, value, field_name):
if not value:
self.errors.append(f"{field_name} is required")
return self
def validate_email(self, email):
…Redact secrets from log message formatter in Python
Build a custom logging.Formatter that masks passwords, API keys, and credit card numbers in log output.
import re
import logging
class RedactingFormatter(logging.Formatter):
"""Formatter that masks sensitive data in log messages."""
SENSITIVE_PATTERNS = [
(re.compile(r'password[=:]\s*\S+', re.IGNORECASE), 'password=[REDACTED]'),
(re.compile(r'api[_-]?key[=:]\s*\S+', re.IGNORECASE), 'api_key…Calculate Working Hours Between Two Dates in Python
Compute total business hours (Mon-Fri, 09:00-17:00) between two datetime objects, excluding weekends and non-working hours.
from datetime import datetime, timedelta
def work_hours_between(start: datetime, end: datetime) -> float:
"""Calculate total working hours between two datetimes (Mon-Fri, 09:00-17:00)."""
def is_workday(d: datetime) -> bool:
return d.weekday() < 5
total_hours = 0.0
current = start
whi…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 Merge Sorted Chunk Files in Python
Merge multiple sorted text files into one sorted output file using a heap for efficient k-way merging.
import heapq
def merge_sorted_chunks(chunks, output_path):
"""Merge multiple sorted iterables into single sorted output file."""
with open(output_path, "w") as out_f:
# Open all chunk files
handles = [open(chunk, "r") for chunk in chunks]
try:
# Heap of (value, index) tupl…Join two CSV files on shared key column in Python
Merge rows from two CSV files by a common key column, outputting combined records to a new file.
import csv
def join_csv(file1, file2, key, output="joined.csv"):
# Read first CSV into dict keyed by the join column
with open(file1, newline="") as f1:
reader1 = csv.DictReader(f1)
data1 = {row[key]: row for row in reader1}
# Read second CSV and merge matching rows
with open(file2, n…Find Longest Increasing Subsequence Length in Python
Compute the length of the longest increasing subsequence in an array using dynamic programming.
def longest_increasing_subsequence(nums):
if not nums:
return 0
dp = [1] * len(nums)
for i in range(1, len(nums)):
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[i], dp[j] + 1)
return max(dp)
if __name__ == "__main__":
# Demo with…Game of Life Next State Grid in Python
Compute the next generation of Conway's Game of Life from a 2D grid using the standard three rules with neighbor counting.
def next_state(grid):
m, n = len(grid), len(grid[0])
new = [[0] * n for _ in range(m)]
for r in range(m):
for c in range(n):
total = 0
for dr in (-1, 0, 1):
for dc in (-1, 0, 1):
if dr == 0 and dc == 0:
continue
…How to Solve Daily Temperatures Days Until Warmer in Python
Compute the number of days until a warmer temperature for each day using a monotonic stack.
def daily_temperatures(temps):
n = len(temps)
result = [0] * n
stack = []
for i, temp in enumerate(temps):
while stack and temps[stack[-1]] < temp:
prev_idx = stack.pop()
result[prev_idx] = i - prev_idx
stack.append(i)
return result
if __name__ == …How to Solve the Trapping Rain Water Problem in Python
Compute the total water trapped between elevation bars using a two-pointer O(n) algorithm.
def trap(height):
if not height:
return 0
left, right = 0, len(height) - 1
left_max, right_max = 0, 0
water = 0
while left < right:
if height[left] < height[right]:
if height[left] >= left_max:
left_max = height[left]
else:
…Product of Array Except Self in Python Without Division
Compute the product of all array elements except the current one in O(n) time using prefix and suffix products, without using division.
from math import prod
def product_except_self(nums):
n = len(nums)
result = [1] * n
left_product = 1
for i in range(n):
result[i] = left_product
left_product *= nums[i]
right_product = 1
for i in range(n - 1, -1, -1):
result[i] *= right_product
right_product *…How to Detect Prompt Injection in Python
Implements a regex-based heuristic in Python to flag common prompt injection attempts before sending input to an LLM.
import re
def contains_prompt_injection(user_input: str) -> bool:
# Directives to ignore previous instructions or act as system
ignore_patterns = [
r"\bignore\s+(all\s+)?previous\s+instructions\b",
r"\bdisregard\s+(all\s+)?previous\s+instructions\b",
r"\bdon'?t\s+follow\s+(any\s+)?inst…How to cache embeddings with a Python dict to avoid recomputation
Caches embeddings computed from text in a dictionary keyed by SHA-256 hash, returning cached results for repeated calls.
import hashlib
import time
class EmbeddingCache:
def __init__(self):
self.cache = {}
def _hash_text(self, text):
return hashlib.sha256(text.encode()).hexdigest()
def get_embedding(self, text, compute_func):
key = self._hash_text(text)
if key not in self.cache:
…How to parallel map embeddings with a thread pool in Python
Run embedding computations in parallel using ThreadPoolExecutor, collect results into a dict keyed by the original item.
import threading
from concurrent.futures import ThreadPoolExecutor
import time
def compute_embedding(item: int) -> tuple[int, int]:
time.sleep(0.05) # Simulate embedding work
return item, item * 10
def parallel_map_embed(items, max_workers=3):
results = {}
with ThreadPoolExecutor(max_workers=max_w…Benchmark File Read and Write Speed in Python
Measures file write and read throughput in MB/s by writing and reading a temporary file of a given size.
import os
import time
import tempfile
def benchmark_write(file_path, size_mb=100):
data = b'x' * (1024 * 1024) # 1 MB block
start = time.perf_counter()
with open(file_path, 'wb') as f:
for _ in range(size_mb):
f.write(data)
elapsed = time.perf_counter() - start
return size_mb …Build a Python Utility That Verifies Backup Integrity Automatically
Automatically compute and verify SHA-256 checksums of backup files using a JSON manifest to detect missing or corrupted data.
import hashlib
import os
import json
def compute_checksum(filepath, algorithm='sha256'):
"""Compute checksum for the given file."""
hash_func = hashlib.new(algorithm)
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
hash_func.update(chunk)
return hash_f…Create a Local Search Engine to Instantly Find Files on Your Computer in Python
Build a local file search engine in Python that indexes files by name, extension, and glob pattern for instant retrieval.
import os
import sys
import time
from pathlib import Path
import fnmatch
class LocalSearchEngine:
def __init__(self, root_directory="."):
self.root_directory = Path(root_directory)
self.file_index = {}
def build_index(self):
"""Build a complete index of files in the root direc…Find Zombie Processes on Linux with Python
Parse the output of `ps -eo pid,stat,comm` to detect processes in zombie state (Z) on a Linux system and report their PIDs and commands.
#!/usr/bin/env python3
import os
import subprocess
def find_zombie_processes():
"""Find zombie processes (state 'Z') running on Linux."""
try:
result = subprocess.run(['ps', '-eo', 'pid,stat,comm'], capture_output=True, text=True, check=True)
zombies = []
for line in result.stdout.stri…Find and Delete Duplicate Files Using Hashing in Python
Walk a directory tree, compute SHA256 hashes for every file, and delete duplicates that share the same hash.
import hashlib
import os
from pathlib import Path
def file_hash(path, block_size=65536):
"""Return SHA256 hash of file content."""
hasher = hashlib.sha256()
with open(path, 'rb') as f:
while chunk := f.read(block_size):
hasher.update(chunk)
return hasher.hexdigest()
def find_and_d…How to Monitor USB Device Connections in Python
A Python utility that monitors USB device connections and disconnections by comparing output of the lsusb command at regular intervals.
import time
import subprocess
import os
def get_usb_devices():
"""Return list of currently connected USB devices (Linux)."""
try:
result = subprocess.run(['lsusb'], capture_output=True, text=True, check=True)
return result.stdout.strip().split('\n')
except (subprocess.CalledProcessError, F…How to Monitor Website Content Changes in Python
This script fetches a webpage's content, computes its SHA-256 hash, and compares it with the last stored hash to detect and alert on changes.
import time
import hashlib
import requests
from pathlib import Path
def fetch_content_hash(url: str) -> str:
response = requests.get(url, timeout=10)
response.raise_for_status()
return hashlib.sha256(response.text.encode()).hexdigest()
def monitor_website(url: str, check_interval: int = 60):
hash_fil…How to Topologically Sort a DAG in Python
Compute a valid execution order for tasks with dependencies using Kahn's algorithm in Python.
from collections import defaultdict, deque
def topological_order(dependencies):
graph = defaultdict(list)
in_degree = defaultdict(int)
tasks = set(dependencies.keys())
for task, depends_on in dependencies.items():
for d in depends_on:
graph[d].append(task)
in_degree[t…Map Partition Over Chunks in Python with Multiprocessing and Mock
Process data in chunks across multiple CPU cores using multiprocessing Pool.map, and mock the chunk function to test partitioning behavior without heavy computation.
from multiprocessing import Pool
from unittest.mock import patch, Mock
def process_chunk(chunk):
return [x * x for x in chunk]
def map_partition_over_chunks(data, chunk_size, process_func=process_chunk):
chunks = [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]
with Pool() as pool:
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