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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…
Find Most Active Contributors in a Repository with Python
Filter recent commits by date and count the most active contributors using Counter and datetime.
from collections import Counter
from datetime import datetime, timedelta
# Simulated commit data
commits = [
{"author": "Alice", "timestamp": datetime.now() - timedelta(days=1)},
{"author": "Bob", "timestamp": datetime.now() - timedelta(days=2)},
{"author": "Alice", "timestamp": datetime.now() - timedelta…
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…
Generate Timesheet Reports from Daily Logs in Python
Aggregate daily log entries by project and produce a formatted timesheet report using Python's standard library.
import json
from pathlib import Path
from collections import defaultdict
def generate_timesheet_report(daily_logs: list[dict]) -> str:
"""
Generate a timesheet report from daily log entries.
Args:
daily_logs: List of dicts with 'date', 'project', 'hours', 'task' keys
Returns:
…
How to Archive Old Files by Age in Python
Move files older than a specified number of days from a source directory to an archive directory using Python's pathlib and shutil modules.
import os
import shutil
import time
from pathlib import Path
def archive_old_files(source_dir: str, archive_dir: str, days_old: int) -> None:
cutoff_time = time.time() - (days_old * 86400) # 86400 seconds in a day
archive_path = Path(archive_dir)
archive_path.mkdir(parents=True, exist_ok=True)
for i…
Build a Live Countdown Timer for Events in Python
A Python script that displays a real-time countdown to a target date and time, updating every second in the console.
import datetime
import time
def countdown(event_name, target_datetime):
"""Displays a live countdown to a target datetime."""
while True:
now = datetime.datetime.now()
remaining = target_datetime - now
if remaining.total_seconds() <= 0:
print(f"\n🚀 {event_name} is happening…
Generate Random Fake User Data for Testing in Python
This code generates a list of fake user dictionaries with random names, emails, ages, and timestamps using the Python standard library for testing purposes.
import json
import random
import string
from datetime import datetime, timedelta
def generate_user_data(num_users=1):
first_names = ["Alice", "Bob", "Charlie", "Diana", "Eve"]
last_names = ["Smith", "Johnson", "Brown", "Taylor", "Wilson"]
domains = ["example.com", "test.org", "demo.net"]
users = …
How to Find Stale GitHub Issues in Python
Filter a list of GitHub issues to find those not updated within a configurable number of days using Python datetime arithmetic.
import os
from datetime import datetime, timezone, timedelta
import re
# Simulated GitHub issue data structure
SAMPLE_ISSUES = [
{"number": 101, "title": "Login button not working", "updated_at": "2025-06-01T12:00:00Z", "assignee": "alice"},
{"number": 102, "title": "Fix database migration error", "updated_at…
How to generate website performance reports from HTTP requests in Python
Measure and report website load time, status code, and content size using Python's standard library.
import urllib.request
import time
def measure_website_load_time(url):
"""Measures total loading time of a website."""
start_time = time.time()
try:
with urllib.request.urlopen(url, timeout=10) as response:
content = response.read()
status_code = response.status
…
Monitor Website Uptime with Python
Periodically check if a website is reachable and its HTTP status is 200, logging the status with timestamps.
import requests
import time
def check_website(url):
try:
response = requests.get(url, timeout=5)
if response.status_code == 200:
return True
else:
return False
except requests.ConnectionError:
return False
except requests.Timeout:
return Fals…
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