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Python Code Samples

Medium snippets you can copy, study, and run in the browser editor.

12 matches
Dictionaries & sets medium

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.

dictionary cache ttl
Python
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…
16 0 Open
Automation & scripting medium

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.

ping network monitoring
Python
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…
94 0 Open
Automation & scripting medium

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.

internet connectivity monitoring
Python
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 …
39 0 Open
Data pipelines & processing medium

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.

datetime grouping time-window
Python
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,
…
12 0 Open
Data pipelines & processing medium

Normalize Timestamps to UTC DateTime in Python

Convert timestamps in multiple formats to UTC-aware datetime objects using datetime.strptime and astimezone.

datetime timezone utc
Python
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-%…
14 0 Open
Streaming & messaging medium

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.

streaming join generator
Python
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(
            …
14 0 Open
Streaming & messaging medium

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.

watermark streaming side output
Python
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…
11 0 Open
Caching & Redis medium

Implement a TTL cache with a mock clock in Python

This code creates a simple TTL cache that stores values with an expiration timestamp and allows injecting a mock time function to test expiry behavior deterministically.

cache ttl mocking
Python
import time
from functools import wraps

class TTLCache:
    def __init__(self, ttl_seconds):
        self.ttl = ttl_seconds
        self.cache = {}
        self._now = time.time

    def set_mock_time(self, mock_time_fn):
        """Inject a mock time function for testing TTL expiry."""
        self._now = mock_time_…
15 0 Open
Caching & Redis medium

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.

redis rate-limit sliding-window
Python
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…
14 0 Open
Reliability & rate limiting medium

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.

rate-limiting sliding-window deque
Python
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_…
15 0 Open
Reliability & rate limiting medium

How to Implement a Token Bucket Rate Limiter per Client IP in Python

Implements a simple sliding-window rate limiter using a dictionary of timestamp lists per client IP to limit requests per window.

rate-limiting sliding-window ip
Python
from time import time
from collections import defaultdict

class RateLimiter:
    def __init__(self, max_requests: int, window_seconds: int):
        self.max_requests = max_requests
        self.window_seconds = window_seconds
        self.clients = defaultdict(list)

    def allow(self, ip: str) -> bool:
        now…
13 0 Open
Reliability & rate limiting medium

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.

rate-limiting api time-window
Python
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):
       …
13 0 Open

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