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How to Compute Sliding Window Sum of Size k in Python
Compute the sum of every contiguous subarray of a fixed size k using an efficient O(n) sliding window technique.
def sliding_window_sum(nums, k):
"""Return a list of sums for each contiguous subarray of size k."""
if not nums or k <= 0 or k > len(nums):
return []
result = []
window_sum = sum(nums[:k])
result.append(window_sum)
for i in range(k, len(nums)):
window_sum += nums[i] -…How to Compute a Moving Average in Python
This code computes the moving average over a numeric list using an efficient sliding window sum, avoiding recomputation of each window.
def moving_average(data, window_size):
"""
Compute the moving average over a numeric list.
Args:
data: List of numeric values
window_size: Size of the sliding window (positive integer)
Returns:
List of moving averages, each representing the mean of a window
"""
…How to Apply a Function to Sliding Window Slices in Python
This Python code applies a given function to every contiguous window of a specified size in a list, returning a list of results.
def apply_to_sliding_windows(data, window_size, func):
return [func(data[i:i + window_size]) for i in range(len(data) - window_size + 1)]
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5, 6]
window_size = 3
results = apply_to_sliding_windows(numbers, window_size, sum)
print(results)
results…How to Implement a Moving Average from a Data Stream in Python
Implement a MovingAverage class using a deque and running sum to compute the average of the last k values from a continuous data stream.
from collections import deque
class MovingAverage:
def __init__(self, size):
self.size = size
self.queue = deque()
self.window_sum = 0
def next(self, val):
self.queue.append(val)
self.window_sum += val
if len(self.queue) > self.size:
self.window_su…How to Implement a Recent Counter with a Deque in Python
Implements a RecentCounter class that uses a deque to count ping requests within the last 3000 milliseconds.
from collections import deque
import time
class RecentCounter:
def __init__(self):
self.hits = deque()
def ping(self, t: int) -> int:
self.hits.append(t)
while self.hits and self.hits[0] < t - 3000:
self.hits.popleft()
return len(self.hits)
if __name__ == "__mai…How to Build a Sliding Window Generator in Python
Create a generator that yields fixed-size overlapping slices of a sequence, useful for efficient windowed iteration.
def sliding_window(sequence, size):
for i in range(len(sequence) - size + 1):
yield sequence[i:i + size]
if __name__ == "__main__":
data = [1, 2, 3, 4, 5]
n = 3
for window in sliding_window(data, n):
print(window)Automatically Clean Temporary Files from Applications Using Python
A Python script that safely deletes temporary files from common application temp directories across Windows, Linux, and macOS, tracking cleaned count and disk space.
import os
import shutil
import tempfile
import platform
def clean_application_temp_files():
"""Delete common temporary file locations safely."""
system = platform.system()
temp_dirs = []
if system == "Windows":
temp_dirs.extend([
os.path.join(os.getenv("LOCALAPPDATA"), "Temp"),
…Deduplicate events by ID within a window in Python
Deduplicate event streams by ID within sliding time windows, keeping the newest occurrence per window using heaps and sets.
import heapq
from collections import defaultdict
def deduplicate_events(events, window_size):
"""Return events deduplicated by id, keeping newest within each sliding window."""
# Index events by (timestamp, id) for deterministic ordering
events_by_id = defaultdict(list)
for ts, eid, *payload in events…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 Implement a Sliding Window Average in Python
Compute the average of the most recent N values in a stream using a bounded deque, efficiently updating the total as new values arrive.
from collections import deque
class SlidingWindowAverage:
def __init__(self, window_size):
self.window_size = window_size
self.window = deque(maxlen=window_size)
self.total = 0
def add(self, value):
if len(self.window) == self.window_size:
self.total -= self.windo…Implement an Out-of-Order Sort Buffer with a Heap in Python
Buffers out-of-order indices from a stream and emits them in sorted order using a min-heap with a sliding window.
import heapq
from collections import deque
class OutOfOrderSorter:
def __init__(self, buffer_size):
self.buffer_size = buffer_size
self.buffer = deque(maxlen=buffer_size)
self.heap = []
self.next_expected_index = 0
self.result = []
def push(self, item):
heapq.…How to Build a Flow Control Credit Window in Python
A Python class that reserves, confirms, releases, and settles credit to limit message flow and prevent overload in streaming pipelines.
class CreditWindow:
def __init__(self, max_credit=1000):
self.max_credit = max_credit
self.used_credit = 0
self.pending_credit = 0
def try_reserve(self, amount):
available = self.max_credit - self.used_credit - self.pending_credit
if available >= amount:
…How to Implement a Tumbling Window Counter in Python
Count events that fall within a fixed-size sliding time window using a deque and pruning logic.
from collections import deque
import time
class TumblingWindowCounter:
def __init__(self, window_size_seconds):
self.window_size = window_size_seconds
self.window = deque()
def add_event(self, timestamp):
self.window.append(timestamp)
def count(self, current_time):
while…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(
…How to Track Session Windows with Gap Timeout in Python
A Python class that groups events into sessions, closing a session when the gap between events exceeds a timeout threshold.
import time
class SessionWindow:
"""Track sessions with a gap timeout (mock)."""
def __init__(self, timeout_seconds=5):
self.timeout = timeout_seconds
self.session_start = None
self.last_event_time = None
self.event_count = 0
self.events = []
def add_event…Sliding Window Average with Deque in Python
Computes the running average of a sliding window over streaming numbers using a collections.deque for O(1) pop-left operations.
from collections import deque
class SlidingAverage:
def __init__(self, window_size):
self.window_size = window_size
self.window = deque()
self.total = 0
def add(self, value):
self.window.append(value)
self.total += value
if len(self.window) > self.window_size:
…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…Build a Rate Limiter Decorator in Python
This code defines a reusable rate limiter decorator that caps function calls within a sliding time window using a deque and monotonic time.
import time
from collections import deque
def rate_limiter(max_calls: int, period: float):
calls = deque()
def decorator(func):
def wrapper(*args, **kwargs):
now = time.monotonic()
while calls and now - calls[0] >= period:
calls.popleft()
if len(ca…Circuit breaker failure threshold count in Python
Track consecutive or time-windowed failures with a deque to open a circuit breaker and auto-recover to half-open after a cooldown.
from collections import deque
from time import time, sleep
class CircuitBreaker:
def __init__(self, failure_threshold: int = 5, recovery_time: float = 10.0):
self.failure_threshold = failure_threshold
self.recovery_time = recovery_time
self.failures: deque[float] = deque()
self.st…Fixed Window Counter Rate Limiting in Python
A simple fixed window counter rate limiter that allows a maximum number of requests per 60-second window, with a mock time simulation.
from collections import deque
from time import time
class FixedWindowCounter:
def __init__(self, max_requests):
self.max_requests = max_requests
self.window_start = int(time())
self.window_count = 0
def allow_request(self):
current_time = int(time())
if current_time >=…How to Build a Rate Limiter in Python
Implements a simple sliding-window rate limiter that caps the number of calls per period, used to throttle processing of a data list.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.timestamps = []
def allow(self):
now = time.time()
self.timestamps = [t for t in self.timestamps if now - t < self.period]
if len(self.tim…How to Implement a Sliding Window Counter in Python
This code implements an approximate sliding window counter using a deque of time-based buckets to track event counts within a recent time window.
from collections import deque
from time import time
class SlidingWindowCounter:
def __init__(self, window_size, bucket_size=1):
self.window_size = window_size
self.bucket_size = bucket_size
self.buckets = deque()
def _evict_expired(self, now):
while self.buckets and self.buck…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 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.
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:
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