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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 Mock Kafka Topic Partitions with a Python dict of lists
Mocks a Kafka topic and its partitions using a defaultdict of lists to simulate message production, consumption, and per-partition counts.
from collections import defaultdict
class KafkaTopicPartitionMock:
"""A simple mock for Kafka topic-partition assignment using dict of lists."""
def __init__(self, topic):
self.topic = topic
self.partitions = defaultdict(list) # partition_id -> list of messages
def produce(self, message…Simulate RabbitMQ QoS Prefetch Count in Python
Mocks RabbitMQ QoS prefetch semantics using threading and a queue to cap concurrent unacked message processing per worker.
import threading
import time
import queue
class RabbitMQMock:
def __init__(self, prefetch_count=1):
self.prefetch_count = prefetch_count
self.channel_queue = queue.Queue()
self.currently_processing = 0
self.lock = threading.Lock()
def start_consuming(self, messages, worker_co…Redis INCR DECR Counter Mock in Python
Simulate Redis INCR and DECR commands with a Python class to test counter logic without a live Redis server.
class RedisCounter:
def __init__(self):
self._store = {}
def incr(self, key: str, amount: int = 1) -> int:
if key not in self._store:
self._store[key] = 0
self._store[key] += amount
return self._store[key]
def decr(self, key: str, amount: int = 1) -> int:
…Refresh Proactive TTL Renewal in Python
This snippet implements a proactive TTL renewal pattern that refreshes a cache expiration before it lapses, using a mock counter to track renewals.
import time
from datetime import datetime, timezone
class TTLRenewer:
def __init__(self, ttl_seconds=10, renew_at=0.5):
self.ttl = ttl_seconds
self.last_renewed = time.time()
self.renew_threshold = ttl_seconds * renew_at
self.renewals = 0
def check_and_renew(self):
if …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 Implement a Dead Letter Queue Replay in Python
A mock Dead Letter Queue that stores failed messages with retry attempts and replays them with a simple retry counter.
import json
from collections import deque
class DeadLetterQueue:
def __init__(self):
self.messages = deque()
def add_message(self, message_id, payload, attempts=3):
"""Add a message to the DLQ with retry metadata."""
self.messages.append({
"id": message_id,
…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 Mock Daily and Monthly Quota Counters in Python
Track daily and monthly API call usage with automatic resets, quota checks, and limits using a Python class.
import random
from datetime import datetime, timedelta
class QuotaCounter:
def __init__(self, daily_limit=1000, monthly_limit=20000):
self.daily_limit = daily_limit
self.monthly_limit = monthly_limit
self.daily_usage = 0
self.monthly_usage = 0
self.current_day = datetime.n…How to implement a rate-limited shared counter in Python
Implements a thread-safe global counter that allows a maximum number of increments per second using a lock and time-based refill.
import threading
import time
import random
counter = 0
lock = threading.Lock()
MAX_CALLS_PER_SECOND = 3
last_refill = time.time()
def rate_limited_increment():
global counter, last_refill
with lock:
now = time.time()
if now - last_refill >= 1.0:
last_refill = now
count…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…Calculate Error Rate from Log Stream in Python
Parses a mock log stream to count errors and compute the error percentage using a rolling window of recent entries.
import re
from collections import deque
def error_rate_from_log_stream(message):
log_pattern = r'^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] (ERROR|INFO|DEBUG): (.*)$'
recent_entries = deque(maxlen=100)
error_count = 0
total_count = 0
for line in message.strip().split('\n'):
match = re.mat…Generate Synthetic SRE Metrics and Calculate Availability in Python
Create realistic service metrics with random latency, error rate, and request counts, then compute availability and summarize the stream for SLO checks.
from datetime import datetime, timedelta
import random
def generate_service_metrics(service_name: str, minutes: int = 30) -> list[dict]:
"""Generate synthetic SRE metrics for a service across recent minutes."""
metrics = []
now = datetime.now()
for i in range(minutes):
timestamp = now - t…How to Build a Metrics Counter with Increment and Snapshot in Python
A simple dict-backed MetricsCounter class that increments named counters and returns a snapshot of the current values.
class MetricsCounter:
def __init__(self):
self._metrics = {}
def increment(self, key, delta=1):
self._metrics[key] = self._metrics.get(key, 0) + delta
def snapshot(self):
return dict(self._metrics)
if __name__ == "__main__":
counter = MetricsCounter()
counter.increment("…How to Build a Python Latency Histogram with Mock Buckets
This code implements a mock latency histogram that records request durations into configurable buckets and outputs counts, total, and average latency.
import time
import random
from collections import Counter
class LatencyHistogram:
def __init__(self, buckets):
self.buckets = sorted(buckets)
self.counts = Counter()
self.total = 0
self.sum_latency = 0
def record(self, latency_ms):
for i, boundary in enumerate(self.bu…How to Deduplicate Events in Python with SHA256 Hashing
Build an event deduplicator that identifies duplicate inbox messages using SHA256 hashes and tracks duplicate counts per event type.
```python
import hashlib
import json
from collections import defaultdict
class EventDeduplicator:
def __init__(self):
self.seen_hashes = set()
self.duplicate_counts = defaultdict(int)
def process_event(self, event):
event_key = f"{event['event_id']}:{event['timestamp']}"
even…How to Implement an Exactly-Once Deduplication Store in Python
Implement a Python class that deduplicates keys exactly once, tracking first-seen timestamps and duplicate counts.
from datetime import datetime
from typing import Any, Hashable
class ExactlyOnceStore:
def __init__(self) -> None:
self._seen: set[Hashable] = set()
self._first_seen: dict[Hashable, datetime] = {}
self._counts: dict[Hashable, int] = {}
def add(self, key: Hashable, value: Any = None) …How to mock a SPIFFE workload identity in Python
Generate a mock SPIFFE ID and token for a workload using a trust domain, namespace, and service account.
import hashlib
import json
from dataclasses import dataclass, asdict
@dataclass
class SPIFFEIdentity:
trust_domain: str
namespace: str
service_account: str
@property
def id(self) -> str:
return f"spiffe://{self.trust_domain}/ns/{self.namespace}/sa/{self.service_account}"
def mock_workl…Idempotent Consumer Event Processing in Python
Track processed event IDs to skip duplicates and count event types for a reliable, idempotent consumer.
import json
from collections import defaultdict
class EventProcessor:
def __init__(self):
self.processed_ids = set()
self.counts = defaultdict(int)
def process_event(self, event):
event_id = event["id"]
if event_id in self.processed_ids:
return {"status": "skipped"…Mock a Sidecar Logger with Python Metrics
Simulate a sidecar logger that tracks request counts, error rates, and endpoint hits, producing a metrics snapshot.
import random
import time
from collections import defaultdict
class SidecarLogger:
def __init__(self):
self.metrics = defaultdict(int)
self.total_requests = 0
self.error_count = 0
def log_request(self, endpoint, status_code):
"""Simulate logging a request and updating metrics…Accumulators Global Counter Mock in Python
Shows an accumulator-style global counter with a mock patch to control its value in tests.
import unittest
from unittest.mock import patch
# Module-level global counter accumulator
counter = 0
def increment(by=1):
"""Increment the global counter in place (accumulator pattern)."""
global counter
counter += by
return counter
def reset():
"""Reset the counter to zero."""
global count…Approximate Distinct Count in Python with HyperLogLog
Mock a large data stream and estimate the number of distinct items with a HyperLogLog-style probabilistic counter to save memory.
import random
import string
from collections import Counter
import math
class ApproxCountDistinct:
def __init__(self, num_buckets=16):
self.num_buckets = num_buckets
self.max_zeros = [0] * num_buckets
def _hash(self, item):
# Simple string hash to a 32-bit integer
h = …Browse by section
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