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Take While Predicate True From Start in Python
Create a custom take_while function that collects elements from an iterable until a predicate returns False, then stops.
def take_while(predicate, iterable):
"""Return elements from iterable until the predicate becomes False."""
result = []
for item in iterable:
if predicate(item):
result.append(item)
else:
break
return result
if __name__ == "__main__":
numbers = [2, 4, 6, 7,…Dict Comprehension to Map Keys to Lengths in Python
Build a dictionary that maps each word to its character count using a dictionary comprehension.
words = ["apple", "banana", "cherry", "date", "elderberry"]
word_lengths = {word: len(word) for word in words}
print(word_lengths)Drop n items then yield rest generator
A generator that skips the first n items of an iterable and then yields the remaining items one by one.
def drop(n, items):
"""Yield every item except the first n from items."""
it = iter(items)
for _ in range(n):
next(it, None) # skip first n items
yield from it
if __name__ == "__main__":
numbers = [10, 20, 30, 40, 50]
result = list(drop(2, numbers))
print(result)How to Generate a Collatz Sequence in Python
Generate the Collatz sequence for a given positive integer by repeatedly applying the 3n+1 rule until reaching 1.
def collatz_sequence(n):
if n <= 0:
raise ValueError("n must be a positive integer")
sequence = [n]
while n != 1:
if n % 2 == 0:
n = n // 2
else:
n = 3 * n + 1
sequence.append(n)
return sequence
if __name__ == "__main__":
start = 7
result…How to Repeat a Generator Cycle Single Value in Python
Build a generator that repeats a single value across multiple cycles, each cycle adding an extra repetition to mark its completion.
def repeat_with_cycle(value, cycle_limit, repetitions):
"""
Repeats a single value until reaching a cycle limit,
then yields the value one more time to demonstrate a full cycle.
Args:
value: The single value to repeat.
cycle_limit: Number of repetitions per cycle.
repetitio…Merge Data with Comprehension and Generator in Python
Merge user and order data using a dictionary comprehension for lookups and a generator expression to filter and transform orders.
def merge_data(users, orders):
"""
Merge user and order data using a dictionary comprehension
and a generator expression for filtering.
"""
# Build a lookup: user_id -> user name
user_map = {user["id"]: user["name"] for user in users}
# Generator: yield orders with user names attached
…How to Batch Embed a List of Strings in Python
Batch embed a list of strings into deterministic pseudo-random vectors using a mock encoder class.
class MockEncoder:
def __init__(self, dim=8, seed=42):
self.dim = dim
self.seed = seed
def embed(self, text):
# Deterministic pseudo-random embedding based on text content
hash_val = hash(text)
import random
rng = random.Random(hash_val + self.seed)
retu…How to Log Prompts and Completions as JSONL Audit Files in Python
Read a JSONL file of LLM prompt–completion pairs, compute totals and averages, then write an audit summary with timestamps.
import json
from pathlib import Path
from datetime import datetime
def audit_jsonl(filepath):
logs = []
with open(filepath, encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
entry = json.loads(line)
logs.ap…Automatically Generate Hardware Inventory Reports in Python
Generate a system hardware report including OS version, CPU cores, RAM, and disk usage using platform and psutil.
import platform
import psutil # requires: pip install psutil
from datetime import datetime
def generate_hardware_report():
report_lines = []
report_lines.append(f"Report Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
report_lines.append(f"System: {platform.system()} {platform.release()} ({pl…Automatically Log CPU, RAM, and Disk Usage Every Minute in Python
This script logs CPU, RAM, and disk usage to a CSV file every 60 seconds using psutil and Python's standard library.
import psutil
import time
import csv
from pathlib import Path
LOG_FILE = Path("system_usage_log.csv")
INTERVAL_SECONDS = 60
def log_system_usage():
"""Write CPU, RAM, and disk usage to CSV every minute."""
file_exists = LOG_FILE.exists()
with open(LOG_FILE, mode="a", newline="") as f:
writer = cs…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 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
…How to Mock an Ansible Inventory in Python
Load an Ansible-style inventory JSON file into Python and simulate a playbook run across hosts and groups.
import json
from pathlib import Path
class InventoryMock:
def __init__(self, inventory_file: str):
self.inventory_file = Path(inventory_file)
self.hosts = {}
def load(self):
if not self.inventory_file.exists():
raise FileNotFoundError(f"Inventory file {self.inventory_file…How to Mock subprocess Calls in Python with unittest.mock
A Python script that wraps Vagrant up/destroy commands using subprocess, with tests that mock the subprocess call to simulate outputs and errors.
import subprocess
from unittest.mock import patch, Mock
def run_vagrant(action: str) -> str:
result = subprocess.run(
["vagrant", action],
capture_output=True,
text=True,
check=False,
)
return result.stdout.strip()
def vagrant_wrapper(action: str) -> str:
if action n…How to Save a VM Snapshot State to a JSON File in Python
Define a dataclass for a VM snapshot and serialize it to a JSON file, then reload it to verify the state.
import json
from dataclasses import dataclass, asdict
from pathlib import Path
@dataclass
class VMSnapshot:
name: str
memory_mb: int
disk_gb: int
state: str = "saved"
def snapshot_to_file(self, path: Path) -> str:
"""Write snapshot state to a JSON file and return the filename."""
…How to Simulate a Traceroute in Python
This Python script simulates a network traceroute by generating mock hop IPs, random delays, and a destination reach condition, useful for testing network scripts.
import random
import time
def simulate_traceroute(destination, max_hops=30):
"""Simulate a traceroute to a destination with mock hop delays."""
print(f"Traceroute to {destination} ({max_hops} hops max):")
for hop in range(1, max_hops + 1):
# Mock IP address for the hop
mock_ip = f"10.0.{ra…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 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…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…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…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):
…Group Python Events into Sessions with a Gap Timeout
Groups timestamped events into sessions, starting a new session when the time gap exceeds a specified timeout.
from itertools import groupby
from datetime import datetime, timedelta
def session_window_group(events, gap_seconds=300):
"""Group events into sessions where gap > gap_seconds starts a new session."""
if not events:
return []
events = sorted(events, key=lambda x: x[0])
sessions = []
c…How to Group Rows by Key into Nested Arrays in Python
This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.
from collections import defaultdict
def implode_rows(rows, key, value_key):
grouped = defaultdict(list)
for row in rows:
grouped[row[key]].append(row[value_key])
return dict(grouped)
if __name__ == "__main__":
data = [
{"category": "fruit", "item": "apple"},
{"category": "fr…How to List Failed Records in a Dead Letter Queue Mock in Python
A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.
import json
from datetime import datetime, timedelta
import random
class DeadLetterQueue:
def __init__(self):
self.failed_records = []
def add_failed_record(self, record_id, payload, error_message):
self.failed_records.append({
"record_id": record_id,
"payload": paylo…Browse by section
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