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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 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 Chainable Filter Helper in Python
A beginner-friendly dataclass helper that chains filters, uniqueness, and slicing on any sequence, returning a plain list at the end.
from dataclasses import dataclass
from typing import Callable, Iterator, Sequence, TypeVar
T = TypeVar("T")
@dataclass
class FilterAssistant:
"""Beginner-friendly helper to filter any collection."""
data: Sequence[T]
def where(self, predicate: Callable[[T], bool]) -> "FilterAssistant":
return …How to Build an MVP Presenter View Mock in Python
A minimal MVP (Model-View-Presenter) mock showing a Presenter controlling a SlideDeck model with slide navigation and typed state via dataclasses.
from dataclasses import dataclass, field
from typing import List
@dataclass
class SlideDeck:
title: str
slides: List[str] = field(default_factory=list)
current_index: int = 0
def next_slide(self) -> str:
if self.current_index < len(self.slides) - 1:
self.current_index += 1
…How to Implement Pagination with Offset and Limit in Python
A mock API pagination pattern that parses page and per_page query parameters, computes offset and limit, and slices a list of items for a specific page.
def paginate(items, page, per_page):
offset = (page - 1) * per_page
return items[offset:offset + per_page]
def parse_query_params(query_string):
params = {}
if query_string:
for pair in query_string.split("&"):
key, value = pair.split("=")
params[key] = value
page …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(
…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…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:
now…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):
…Rate Limit per User ID in Python with a Dict Mock
Implements a simple sliding window rate limiter using a defaultdict of timestamps per user ID, blocking requests that exceed a max count within a time window.
import time
from collections import defaultdict
class RateLimiter:
def __init__(self, max_requests, window_seconds):
self.max_requests = max_requests
self.window_seconds = window_seconds
self.user_timestamps = defaultdict(list)
def allow_request(self, user_id):
now = time.tim…Rate Limiting in Python with a Sliding Window
A beginner-friendly dataclass-based sliding window rate limiter that controls how many calls are allowed per time window.
import time
from dataclasses import dataclass
@dataclass
class RateLimiter:
max_calls: int
window_seconds: float = 1.0
def __post_init__(self):
self.calls = []
self._start = time.monotonic()
def _update(self, now):
self.calls = [t for t in self.calls if now - t < self.window…How to Build a Burn Rate Alert with Multiple Time Windows in Python
Track token consumption and trigger alerts when the burn rate exceeds a threshold across multiple time windows using deque and time-based sliding windows.
import time
from collections import deque
class BurnRateAlert:
def __init__(self, windows_seconds=(60, 300, 900), threshold_rate=0.8):
self.windows = {w: deque() for w in windows_seconds}
self.threshold_rate = threshold_rate
self.previous_tokens = None
def record_sample(self, current_…How to Compute SRE Metrics Like Error Rate and Availability in Python
Tracks log events in a sliding time window and calculates error rate per second and availability percentage using an easy-to-follow class.
from collections import deque
from datetime import datetime, timedelta
from typing import Dict, Deque
class LogMetrics:
"""Simple observability helper to track log events and calculate SRE metrics."""
def __init__(self, window_seconds: int = 60):
self.window_seconds = window_seconds
self.eve…How to Group Alerts by Time Window in Python
Group alert occurrences that fall within a sliding time window per alert key, reducing noise and summarizing bursts into single events.
from collections import defaultdict
from datetime import datetime, timedelta
def group_alerts(alerts, window_minutes=10):
"""Group alerts that occur within the same time window."""
alerts_by_key = defaultdict(list)
for alert in alerts:
key = alert["key"]
timestamp = alert["timestamp"]…How to mock SLI availability success ratio in Python
Simulate request outcomes with deterministic randomness and compute the SLI availability success ratio to check if a target is met.
import random
from collections import defaultdict
def mock_availability(num_requests=1000, target_ratio=0.995):
"""
Simulate request outcomes and compute the SLI availability success ratio.
Args:
num_requests: Total number of requests to simulate
target_ratio: Target availability rati…How to Mock and Test a Rate-Limited Source Stream in Python
Build a class that rate-limits emitted items using a sliding window and test it with a simulated stream in Python.
import time
from collections import deque
class RateLimitedSource:
def __init__(self, max_rate, window=1.0):
self.max_rate = max_rate
self.window = window
self._timestamps = deque()
def emit(self, item):
now = time.monotonic()
while self._timestamps and self._timestam…Browse by section
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