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At Least Once with Idempotent Consumer in Python
Implements a thread-safe idempotent consumer that processes each unique message exactly once, even when a producer sends duplicates under an at-least-once delivery model.
import threading
import time
import uuid
from collections import Counter
class IdempotentConsumer:
def __init__(self):
self.processed = set()
self._lock = threading.Lock()
def consume(self, message_id, payload):
with self._lock:
if message_id in self.processed:
…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 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"]…Summary Quantile Mock Sketch in Python
Build a memory-efficient sketch that stores sorted bins of data points to answer approximate quantile queries like median without keeping all values in memory.
import random
import statistics
from collections import Counter
class SummaryQuantileSketch:
"""
A simple sketch that stores a fixed-size summary of data (min, max, deciles)
using sorted bins, then answers approximate quantile queries.
"""
def __init__(self, bins=10):
self.bins = bins
…Consumer Driven Contract Pact Mock in Python
Define and verify consumer-driven contracts using Pact's Consumer and Provider classes, mocking the provider to assert expected interactions.
from pact import Consumer, Provider
pact = Consumer('OrderService').has_pact_with(Provider('InventoryService'))
@Pact.verify()
class TestInventoryContract:
def test_get_inventory(self):
expected = {"item": "widget", "quantity": 100}
(pact
.given('inventory exists for widget')
.u…How to implement a tumbling window aggregation in Python
Build a mock tumbling window aggregator in Python that groups streaming events into fixed time intervals and computes count, sum, and average per window.
import time
from collections import deque
class TumblingWindow:
def __init__(self, duration_seconds):
self.duration = duration_seconds
self.buffer = deque()
self.window_start = None
def add(self, item):
current_time = time.time()
if self.window_start is None:
…How to Run a Permutation Test in Python
Run a Monte Carlo permutation test to compute a p-value for comparing two group means without parametric assumptions.
import random
import statistics
def permutation_test(group_a, group_b, n_permutations=10000, seed=42):
random.seed(seed)
combined = group_a + group_b
observed_diff = abs(statistics.mean(group_a) - statistics.mean(group_b))
count = 0
n = len(group_a)
for _ in range(n_permutations):
…How to mock batch commit of transactions in Python
Simulate a transaction batch writer with commit, rollback, and summary logic to test database write patterns without a real database.
import json
from datetime import datetime, timezone
class TransactionBatch:
def __init__(self):
self.pending = []
self.committed = []
self._log = []
def add(self, operation):
self.pending.append(operation)
def commit(self):
if not self.pending:
return …Browse by section
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