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Rate Limiting with a Simple Python RateLimiter Class
A beginner-friendly Python rate limiter that tracks call timestamps and enforces a maximum number of calls within a rolling time window, with a helper to validate positive integers.
import time
class RateLimiter:
def __init__(self, max_calls, period_seconds):
self.max_calls = max_calls
self.period_seconds = period_seconds
self.calls = []
def is_allowed(self):
now = time.time()
while self.calls and now - self.calls[0] >= self.period_seconds:
…How to Add Metadata Attributes to a Span in Python
Create a lightweight dataclass-based Span mock that stores key-value metadata attributes for tracing or event logging.
from dataclasses import dataclass, field
from typing import Dict, Any
@dataclass
class Span:
name: str
attributes: Dict[str, Any] = field(default_factory=dict)
def set_attribute(self, key: str, value: Any) -> None:
self.attributes[key] = value
def get_attribute(self, key: str) -> Any…How to Build a Consumer Lag Gauge in Python
Simulate Kafka consumer lag with a Python class that tracks lag over time and reports health and averages.
import time
import random
from collections import deque
class ConsumerLagGauge:
"""Mock consumer lag gauge measuring how far behind a consumer is."""
def __init__(self, producer_rate=10, consumer_rate=7, initial_lag=0):
self.producer_rate = producer_rate
self.consumer_rate = consumer_rate
…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 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 Link Parent and Child Span Elements in Python
This code defines a lightweight mock element class and a function that links child elements to a parent when their ranges are nested within the parent's range.
class MockElement:
def __init__(self, name, start, end, children=None):
self.name = name
self.start = start
self.end = end
self.children = children or []
def __repr__(self):
return f"MockElement({self.name}, {self.start}-{self.end})"
def link_parent_child(parent, chil…How to Model Span Events in Python
Define a Span class with timestamped milestone events and a completion marker to track operation lifecycle.
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import List
class SpanStatus(Enum):
STARTED = "started"
COMPLETED = "completed"
@dataclass
class SpanEvent:
name: str
timestamp: float = field(default_factory=time.time)
attributes: dict = field(default_facto…How to Redact Secrets from Log Messages in Python
Build a lightweight RedactingFormatter class that replaces sensitive tokens like passwords and API keys with [REDACTED] before log messages are printed.
class RedactingFormatter:
def __init__(self, secrets):
self.secrets = secrets
def redact(self, message):
for secret in self.secrets:
message = message.replace(secret, "[REDACTED]")
return message
def format(self, record):
message = record["message"]
ret…Track Success Rates and Latency in Python: SRE Metrics Helper
A beginner-friendly Python class to record request outcomes and latencies, then report success rate, average latency, and p99.
import random
import time
from collections import defaultdict
class MetricsTracker:
"""Simple helper to track success rates and latencies for SRE beginners."""
def __init__(self):
self.successes = 0
self.failures = 0
self.latencies = []
def record(self, success, latency_ms):
…BFF aggregation pattern: combine multiple service responses in Python
Mock three backend services and aggregate their responses into one unified payload — the BFF pattern every Python microservice gateway relies on.
from dataclasses import dataclass
from typing import Any
@dataclass
class Service:
name: str
data: dict[str, Any]
def get_user_service() -> Service:
return Service("user", {"id": 1, "name": "Alice"})
def get_orders_service() -> Service:
return Service("orders", {"total": 299.99, "count": 2})
de…Event Sourcing Store in Python: Append-Only Log Mock
Mock an append-only event store in Python — record events, list them, and fetch by ID using a simple list-backed class.
class EventStore:
def __init__(self):
self._events = []
def append(self, event):
event_id = len(self._events) + 1
stored_event = {"id": event_id, "data": event}
self._events.append(stored_event)
return stored_event
def get_events(self):
return list(self._ev…How to Build a Health Check Service Registry in Python
Build a minimal Python service registry that handles registration, deregistration, health checks, and service listing in one simple class.
import random
import time
class ServiceRegistry:
def __init__(self):
self.services = {}
def register(self, name, address):
self.services[name] = {
"address": address,
"status": "healthy",
"registered_at": time.time(),
"checks": 0
}
…How to Build an In-Memory Service Registry Mock in Python
A simple in-memory ServiceRegistry class to register, retrieve, list, and unregister microservice endpoints or configs using a dict, with KeyError guards.
class ServiceRegistry:
def __init__(self):
self._services = {}
def register(self, name, service):
self._services[name] = service
def unregister(self, name):
if name not in self._services:
raise KeyError(f"Service '{name}' not found")
del self._services[name]
…How to Implement a Data Helper for Microservices in Python
Create a reusable helper class to serialize, deserialize, and wrap data for microservice communication using dataclasses and JSON.
import json
from dataclasses import dataclass, asdict
from typing import Any, Dict, List
@dataclass
class ServiceResponse:
status: str
data: Any
message: str = ""
class DataHelper:
"""Simple helper for microservice data handling."""
@staticmethod
def serialize(data: Dict[str, Any]) -> str:…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 Implement an Outbox Pattern Mock in Python
This code demonstrates a simple in-memory outbox pattern mock for publishing domain events and tracking pending events until they are marked as published.
from dataclasses import dataclass, field
from datetime import datetime
from uuid import uuid4
@dataclass
class DomainEvent:
event_id: str = field(default_factory=lambda: str(uuid4()))
occurred_at: datetime = field(default_factory=datetime.utcnow)
class Outbox:
def __init__(self):
self._events =…How to Mock a GraphQL Backend in Python
Create an in-memory GraphQL mock backend using dataclasses and resolver methods returning plain dictionaries.
from dataclasses import dataclass, asdict
from typing import Any, Dict, List
@dataclass
class Product:
id: int
name: str
price: float
@dataclass
class User:
id: int
username: str
class MockGraphQLBackend:
def __init__(self) -> None:
self.products = [
Product(id=1, name…How to Mock a Server-Side Load Balancer in Python
A simple Python class that mimics a server-side load balancer with round-robin, random, and least-connections selection strategies.
import itertools
import random
class LoadBalancer:
def __init__(self, servers=None):
self.servers = servers if servers else ["server1", "server2", "server3"]
self.counter = itertools.count(1)
def round_robin(self):
return next(self.counter) % len(self.servers)
def random_selectio…How to Mock a Service Mesh Sidecar Proxy in Python
Simulate a service mesh sidecar proxy with route registration, service discovery, and request proxying using a simple Python class.
class SidecarProxy:
def __init__(self, name):
self.name = name
self.routes = {}
self.services = {}
self.requests_processed = 0
def register_service(self, service_name, address, port):
self.services[service_name] = f"{address}:{port}"
def add_route(self, path, servi…How to Mock a Service Registry in Python with an In-Memory Dict
A lightweight ServiceRegistry class backed by a dict, exposing register, unregister, lookup, list, and health-check methods.
class ServiceRegistry:
def __init__(self):
self._services = {}
def register(self, name, endpoint, version="1.0"):
self._services[name] = {
"endpoint": endpoint,
"version": version,
"status": "healthy"
}
def unregister(self, name):
return…How to implement read-your-writes sticky routing in Python
A mock StickyRouter class that routes all requests for the same key to the same node, ensuring read-after-write consistency.
import random
class StickyRouter:
def __init__(self, nodes):
self.nodes = nodes
self.routes = {}
def route(self, key):
if key not in self.routes:
self.routes[key] = random.choice(self.nodes)
return self.routes[key]
def read(self, key):
node = self.rout…How to Mock Partition Pruning in Python
A dataclass-based mock that filters partitions by year and month to emulate Spark's partition pruning logic.
from dataclasses import dataclass
from typing import List
@dataclass(frozen=True)
class Partition:
id: int
year: int
month: int
class PartitionPruner:
"""Mock partition pruning: only keep partitions that match the filter."""
def __init__(self, partitions: List[Partition]):
self._partiti…Modeling a Hive Metastore Table Schema in Python
A dataclass that mimics a Hive metastore table schema—columns, partition keys, storage format, and location—with helper methods for description and mutation.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class HiveTable:
"""Simple mock of a Hive metastore table schema."""
name: str
database: str = "default"
columns: List[Dict[str, str]] = field(default_factory=list)
partition_keys: List[Dict[str, str]] = f…Sliding Window Streaming Mock in Python
A simple Python class that maintains a sliding window of recent streaming values and computes the running average.
import time
import random
class StreamingMock:
"""Produces a stream of numbers using a sliding window."""
def __init__(self, window_size=5):
self.window = []
self.window_size = window_size
def push(self, value):
"""Add a value, sliding the window forward."""
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