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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Copy a File with shutil.copy2 in Python
Copy a file while preserving metadata like timestamps and permissions using Python's shutil.copy2 and pathlib.
import shutil
from pathlib import Path
source = Path("sample.txt")
destination = Path("sample_copy.txt")
source.write_text("Hello, PythonSkillset!")
if __name__ == "__main__":
shutil.copy2(source, destination)
copied = destination.read_text()
print(f"Copied content: {copied}")
print(f"Source exists:…
How to Build a TTL Cache Dict in Python
Create a dictionary subclass that automatically expires keys after a fixed time-to-live using timestamps.
import time
class TTLDict(dict):
def __init__(self, ttl, *args, **kwargs):
self.ttl = ttl
self._expires = {}
super().__init__(*args, **kwargs)
def __setitem__(self, key, value):
super().__setitem__(key, value)
self._expires[key] = time.time() + self.ttl
def __geti…
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…
Build a Network Ping Monitor in Python
A Python script that continuously pings a remote host using subprocess and reports connectivity status with timestamps and latency.
import subprocess
import time
def ping_host(host, count=4):
"""Ping a host and return the results."""
try:
# Platform-independent ping command
cmd = ["ping", "-c", str(count), host]
result = subprocess.run(cmd, capture_output=True, text=True, timeout=10)
return result.stdout, r…
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 = …
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…
Track Internet Connectivity and Downtime Automatically in Python
Monitors internet connectivity by pinging a remote host and logs any downtime events with timestamps and duration.
import time
import subprocess
from datetime import datetime
def check_internet(host="8.8.8.8", timeout=3):
"""Returns True if internet is reachable via ping."""
try:
subprocess.run(
["ping", "-c", "1", "-W", str(timeout), host],
capture_output=True,
timeout=timeout …
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):
…
How to Count Events by Minute with a Tumbling Window in Python
Group timestamps into fixed 60-second tumbling windows and count events per bucket using a dict.
from collections import defaultdict
from datetime import datetime, timedelta
def tumbling_window_count(events, window_seconds=60):
buckets = defaultdict(int)
for event in events:
ts = datetime.fromisoformat(event["timestamp"])
bucket_start = ts - timedelta(seconds=ts.second % window_seconds,
…
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…
Normalize Timestamps to UTC DateTime in Python
Convert timestamps in multiple formats to UTC-aware datetime objects using datetime.strptime and astimezone.
from datetime import datetime, timezone
raw_timestamps = [
"2024-01-15 14:30:00+02:00",
"17/05/2024 09:15:00 -0500",
"2024-03-01T22:45:00Z",
"2024-06-20 08:00:00+09:30"
]
def parse_and_convert(ts: str) -> datetime:
normalized_ts = ts.strip().replace("Z", "+00:00")
formats = [
"%Y-%m-%…
Generate Mock CloudFormation Stack Events in Python
Generate a list of mock AWS CloudFormation stack events with random resources, statuses, and timestamps, and print them as JSON.
import json
import random
from datetime import datetime, timedelta
def generate_mock_stack_events(stack_name="MyTestStack", num_events=10):
"""Generate a list of mock CloudFormation stack events."""
resources = [
("AWS::S3::Bucket", "MyBucket"),
("AWS::EC2::Instance", "MyInstance"),
("…
How to Create a JSON Data Helper in Python
A beginner-friendly DataHelper class that safely reads and writes JSON files with timestamps to a local data directory.
from datetime import datetime
from pathlib import Path
import json
class DataHelper:
"""Simple helper for reading/writing JSON files safely."""
def __init__(self, base_dir="data"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save(self, filename, data):
…
Mock GCP Secret Manager access version in Python
A minimal mock of GCP Secret Manager that stores secret versions, retrieves payloads by version, and logs access timestamps.
import json
import time
from datetime import datetime, timezone
class MockSecretManager:
"""Minimal mock of GCP Secret Manager access/version behavior."""
def __init__(self):
self._secrets = {}
self._access_log = []
def create_secret(self, secret_id: str, payload: str) -> dict:
…
How to Generate a Mock Rollbar Error Report in Python
Create a realistic fake Rollbar error report with random timestamps, levels, messages, and counts for testing and demos.
import json
import random
import time
from datetime import datetime, timedelta
def mock_rollbar_report(n_errors=5):
messages = [
"TypeError: unsupported operand type(s) for +: 'int' and 'str'",
"KeyError: 'user_id'",
"ValueError: invalid literal for int() with base 10: 'abc'",
"At…
Build a Streaming Messaging Helper in Python
Create a simple message stream class that stores recent messages, sends user messages, and retrieves history or latest messages with timestamps.
from collections import deque
from dataclasses import dataclass
from datetime import datetime
import time
@dataclass
class Message:
user: str
text: str
timestamp: str = ""
def __post_init__(self):
if not self.timestamp:
self.timestamp = datetime.now().strftime("%H:%M:%S")
class…
How to Build a Mock Change Data Capture Event Stream in Python
Generate a deterministic list of mock CDC events with event IDs, stream positions, payloads, and timestamps for testing streaming pipelines.
from itertools import count
from random import choice, randint, seed
from datetime import datetime, timedelta
seed(42) # Make output deterministic
event_types = ["INSERT", "UPDATE", "DELETE"]
table_names = ["users", "orders", "products", "payments"]
counter = count(1)
def mock_cdc_event(stream_index: int) -> dict:
…
How to Stream Join Windowed Mock Topics in Python
Simulates two message topics and joins their events when timestamps fall within a sliding time window using Python generators and deques.
import itertools
import random
import time
from collections import deque
from dataclasses import dataclass, field
@dataclass
class Event:
key: str
value: int
timestamp: float = field(default_factory=time.time)
def generate_topic(prefix, keys, start_time):
while True:
yield Event(
…
Mock Watermark Late Event Side Output in Python
Simulates watermarking in a streaming pipeline by classifying events as on-time or late using timestamps and delays.
from datetime import datetime, timedelta
from typing import List, Tuple
def watermark_mock(
events: List[Tuple[datetime, str]], watermark_delay: timedelta, max_delay: timedelta
) -> Tuple[List[Tuple[datetime, str]], List[Tuple[datetime, str]]]:
"""Simulate watermarking: events arriving on time vs. late by ch…
Redis-inspired sliding window rate limiter in Python
A pure-Python sliding window rate limiter using a deque of timestamps, mock-ready for Redis-backed production limits.
import time
from collections import deque
class SlidingWindowRateLimiter:
def __init__(self, max_requests: int, window_seconds: int) -> None:
self.max_requests = max_requests
self.window_seconds = window_seconds
self.requests: dict[str, deque] = {}
def is_allowed(self, client_id: str…
How to Implement a Rate Limiter in Python
A beginner-friendly Python class that tracks call timestamps with a deque to allow or block calls based on a max rate per time period.
import time
from collections import deque
class RateLimiter:
"""Simple rate limiter for beginners."""
def __init__(self, max_calls: int, period_seconds: float):
self.max_calls = max_calls
self.period = period_seconds
self.calls = deque()
def allow(self) -> bool:
"""Retur…
How to Implement a Sliding Window Log Rate Limiter in Python
Implements a sliding window log rate limiter in Python using a deque of timestamps to enforce a maximum request count within a rolling time window.
from collections import deque
from datetime import datetime, timedelta
from time import sleep
class SlidingWindowLog:
def __init__(self, window_seconds: int, max_requests: int):
self.window_seconds = window_seconds
self.max_requests = max_requests
self.timestamps = deque()
def allow_…
How to implement rate limiting in Python
Build a simple sliding-window rate limiter in Python that enforces a max number of calls per time period and formats data with timestamps.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.calls = []
def allow(self):
now = time.time()
# Remove calls older than the period window
self.calls = [t for t in self.calls if now -…
How to implement rate limiting per API key in Python
A simple sliding-window rate limiter that tracks request timestamps per API key and rejects requests exceeding the configured limit.
import time
API_RATE_LIMITS = {"api_key_1": 5, "api_key_2": 3} # max requests per window
WINDOW_SECONDS = 10
class RateLimiter:
def __init__(self, limits, window):
self.limits = limits
self.window = window
self.requests = {key: [] for key in limits}
def allow(self, api_key):
…
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