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Monitor Disk Usage and Alert in Python
A Python script that checks disk usage percentage against a threshold and returns an ALERT or OK message with free space details.
import shutil
import os
def check_disk_usage(path="/", threshold=85.0):
usage = shutil.disk_usage(path)
percent_used = (usage.used / usage.total) * 100
if percent_used > threshold:
return (f"ALERT: Disk usage at {percent_used:.1f}% on {path} "
f"(exceeds {threshold}% threshold…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…Parse WHOIS Data with Python Regex
Extract domain registration fields from a mock WHOIS record using regex and compute days until expiration.
import re
from datetime import datetime
def parse_whois(whois_text: str) -> dict:
"""Extract key registration fields from a mock WHOIS record."""
patterns = {
"domain": r"Domain Name:\s*(.+)",
"registrar": r"Registrar:\s*(.+)",
"creation_date": r"Creation Date:\s*(.+)",
"expir…Parse cron expression and compute next run datetime in Python
Parse a 5-field cron expression and compute the next matching datetime starting from a given base time.
from datetime import datetime, timedelta
import re
def parse_cron_and_next_run(cron_expr, base_time=None):
"""Parse a cron expression and compute the next run time."""
if base_time is None:
base_time = datetime.now().replace(second=0, microsecond=0)
fields = cron_expr.split()
if len(fields) !…Parse nginx access log top IPs in Python
Reads an nginx access log line by line, extracts the client IP, and returns the most frequent IPs using a regex and Counter.
import re
from collections import Counter
def top_ips(log_file, n=10):
ip_pattern = re.compile(r'^(\S+)')
ip_counts = Counter()
with open(log_file, 'r') as f:
for line in f:
match = ip_pattern.match(line)
if match:
ip_counts[match.group(1)] += 1
return…Pin Python package versions in requirements.txt
Pin package versions in requirements.txt-style text by adding ==version when no specifier is present, while preserving existing version constraints and comments.
import re
from pathlib import Path
def pin_versions(requirements_text: str) -> str:
"""
Pin package versions in requirements.txt-style text.
Adds ==version if no version specifier is present.
Keeps existing specifiers (>=, <=, ~=, etc.) unchanged.
"""
lines = requirements_text.strip().splitli…Port Scan Localhost Common Ports in Python
Scan common localhost ports (HTTP, HTTPS, SSH, FTP, and more) with a fast socket-based Python script that prints an open/closed status table.
import socket
from datetime import datetime
COMMON_PORTS = {
80: "HTTP",
443: "HTTPS",
22: "SSH",
21: "FTP",
25: "SMTP",
3306: "MySQL",
5432: "PostgreSQL"
}
def scan_port(port):
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.settimeout(0.1)
try:
resu…Post a message to a Slack webhook in Python
Send a message to a Slack webhook endpoint using the standard library's urllib.request, handling the POST request and response cleanly.
import json
from urllib import request
def post_to_slack(webhook_url: str, message: str) -> dict:
payload = json.dumps({"text": message}).encode("utf-8")
req = request.Request(
webhook_url,
data=payload,
headers={"Content-Type": "application/json"},
method="POST",
)
wit…Rename Files in Folder with Numeric Prefix in Python
Renames all files in a folder by adding a sequential numeric prefix (e.g., 01_, 02_) to each filename using pathlib.
from pathlib import Path
def rename_with_numeric_prefix(folder_path):
folder = Path(folder_path)
for index, file_path in enumerate(folder.iterdir(), start=1):
if file_path.is_file():
new_name = f"{index:02d}_{file_path.name}"
new_path = file_path.with_name(new_name)
…Resize Disk Partitions in Python (Mock Script)
A mock disk partition resize script that uses dataclasses to model partitions, validate new sizes, and output the updated layout as JSON.
#!/usr/bin/env python3
"""Mock script to demonstrate disk partition resize logic."""
import json
from dataclasses import dataclass
from typing import Dict
@dataclass
class Partition:
name: str
size_gb: int
mount_point: str
def to_dict(self) -> Dict[str, object]:
return {
"name": …Restore sqlite from latest backup file in Python
This script finds the most recently modified backup file in a directory and restores it to the main database path, then verifies the restored data.
import sqlite3
import glob
import os
import shutil
def restore_latest_backup(db_path, backup_dir):
backups = sorted(glob.glob(os.path.join(backup_dir, "*.db")), key=os.path.getmtime)
if not backups:
raise FileNotFoundError("No backup files found")
latest = backups[-1]
shutil.copy2(latest, db_p…Restrict Secrets File Permissions with the chmod Script in Python
This script restricts a secrets file to 0600 permissions, rotates it to a dated backup, and creates a fresh protected file for secure automation workflows.
import os
import sys
import stat
from pathlib import Path
def restrict_secrets_file(filepath: str) -> None:
"""Set restrictive permissions (0600) on a secrets file."""
path = Path(filepath).expanduser()
if not path.is_file():
raise FileNotFoundError(f"Secrets file not found: {path}")
…Rotate API keys in Python by updating an .env template
Replace an old API key with a new one inside an .env template file, with a guard for missing keys.
import json
from pathlib import Path
def rotate_api_keys(env_template_path: Path, old_key: str, new_key: str) -> None:
"""Replace an old API key with a new one in an .env template file."""
content = env_template_path.read_text()
if old_key not in content:
print(f"Error: '{old_key}' not found in {e…Stress CPU Threads with a Mock Compute in Python
Simulates CPU-intensive work across multiple threads to test how Python schedules parallel compute.
import threading
import time
def stress_cpu(iterations: int):
result = 0
for i in range(iterations):
result += i * i % 1000
return result
def run_mock_stress(thread_count: int, iterations: int):
threads = []
for tid in range(thread_count):
t = threading.Thread(target=lambda: str…Attach Source File Metadata to Records in Python
Add a source filename field to each record in a list by merging a new key into every dictionary using a dict unpacking comprehension.
from pathlib import Path
import json
def attach_source_metadata(records, source_file):
"""Attach source filename metadata to each record."""
return [
{**record, "source": Path(source_file).name}
for record in records
]
if __name__ == "__main__":
source = "/data/raw/customers.csv"
…Count Records Processed per Category in Python
Use a Counter dictionary to track how many records of each type (ok, error, retry) were processed in a data pipeline.
from collections import Counter
import random
processed_counter = Counter()
def process_records(records):
for record in records:
processed_counter[record] += 1
return len(records)
if __name__ == "__main__":
sample_records = [random.choice(["ok", "error", "retry"]) for _ in range(10)]
print(f…Create Data Helper Functions in Python for Beginners
Build reusable Python helper functions to load, filter, sort, summarize, and save JSON data — a beginner-friendly starting point for small data pipelines.
import json
from pathlib import Path
from typing import Any, Dict, List
def load_json_file(filepath: str) -> Dict[str, Any]:
"""Load JSON data from a file."""
with Path(filepath).open("r", encoding="utf-8") as file:
return json.load(file)
def filter_by_key(
data: List[Dict[str, Any]], key: str,…ETL in Python: Extract CSV, Transform Dict, Load JSON
Build a simple ETL pipeline in Python that reads a CSV file, transforms each row (stripping whitespace and converting numeric fields), and writes the result to JSON.
import csv
import json
from pathlib import Path
def extract_csv(file_path):
"""Read CSV file and return list of row dictionaries."""
with Path(file_path).open('r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
return list(reader)
def transform_dicts(rows):
"""Transform ro…ETL in Python: Extract CSV, Transform Dicts, Load JSON
Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.
import csv
import json
from pathlib import Path
def etl_csv_to_json(csv_path: str, json_path: str) -> None:
"""Extract CSV, transform rows to dicts, load to JSON."""
with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
records = list(reader)
# Trans…Enrich Events with Geo IP Data in Python
Returns a copy of each event dictionary, enriched with a geo-location dict from a mock IP-to-geo lookup table, with a fallback for unknown IPs.
import ipaddress
GEO_IP_DB = {
"192.168.1.10": {"country": "US", "city": "New York", "lat": 40.7128, "lon": -74.0060},
"10.0.0.5": {"country": "DE", "city": "Berlin", "lat": 52.5200, "lon": 13.4050},
"172.16.0.8": {"country": "JP", "city": "Tokyo", "lat": 35.6762, "lon": 139.6503},
}
EVENTS = [
{"id…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_…Filter Records by Required Fields in Python
Filter a list of dictionaries, keeping only records where every required field is present and not None.
def filter_records(records, required_fields):
"""Return only records that have all required fields non-null."""
return [
record for record in records
if all(record.get(field) is not None for field in required_fields)
]
if __name__ == "__main__":
sample_records = [
{"name": "Al…Generate a Deterministic Hash for Deduplication in Python
Create a stable SHA-256 fingerprint from nested data and file contents to deduplicate records in a data pipeline.
import hashlib
import json
from pathlib import Path
def natural_key_hash(data, salt=""):
"""
Generate a deterministic fingerprint from raw data (dict/list/str).
Uses JSON canonical-ish serialization with sorted keys and SHA-256.
"""
canonical = json.dumps(data, sort_keys=True, separators=(",", ":"…Generate a Mock CDC Changelog in Python
Simulate a CDC changelog with INSERT, UPDATE, and DELETE operations, timestamps, and record snapshots for testing data pipelines.
import json
from datetime import datetime, timedelta
def generate_mock_changelog(records, operations=("INSERT", "UPDATE", "DELETE")):
"""Simulate a CDC changelog from a list of record snapshots."""
base_time = datetime(2025, 1, 1, 8, 0, 0)
changelog = []
for idx, record in enumerate(records):
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