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asyncio sleep cooperative scheduling demo in Python
This demo shows how asyncio.sleep yields control between concurrent tasks, letting multiple workers interleave their ticks.
import asyncio
async def worker(name, delay):
for i in range(3):
print(f"{name}: tick {i}")
await asyncio.sleep(delay)
return f"{name} done"
async def main():
tasks = [
asyncio.create_task(worker("A", 0.1)),
asyncio.create_task(worker("B", 0.2)),
asyncio.create_tas…How to Build an Append-Only Event Store in Python
Implement a simple append-only event store class that stores events in a list and supports retrieval by index range.
class EventStore:
def __init__(self):
self._events = []
def append(self, event):
"""Append an event to the store."""
self._events.append(event)
def get_events(self, start=0, end=None):
"""Return events from start index to end (exclusive)."""
return self._events[sta…How to Implement a Simple Event Bus in Python
Create a publish-subscribe event bus using dataclasses and defaultdict to decouple event producers from consumers.
from collections import defaultdict
from dataclasses import dataclass, field
from typing import Callable, Dict, List, Set
@dataclass
class EventBus:
_subscribers: Dict[str, List[Callable]] = field(
default_factory=lambda: defaultdict(list)
)
def subscribe(self, event_type: str, handler: Callable…Event Envelope with Schema Version Field in Python
Build a typed event envelope dataclass with an explicit schema version field for mock streaming scenarios.
from dataclasses import dataclass, field
from datetime import datetime
import uuid
@dataclass
class Event:
event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
event_type: str = "user.created"
version: str = "1.0.0"
created_at: str = field(default_factory=lambda: datetime.utcnow().isoform…Event sourcing append store replay in Python
A simple in-memory event store that appends events per aggregate and replays them on demand.
import json
from collections import defaultdict
class EventStore:
def __init__(self):
self._events = defaultdict(list)
def append(self, aggregate_id, event_type, data):
event = {"type": event_type, "data": data}
self._events[aggregate_id].append(event)
def replay(self, aggregate…Exactly Once Idempotent Consumer Store in Python
A mock key-value store that guarantees exactly-once processing by rejecting duplicate message keys in a message or event stream.
from collections import defaultdict
class ExactlyOnceStore:
def __init__(self):
self.processed = defaultdict(set)
self.data = {}
def consume(self, key, value):
if key in self.data:
return False
self.data[key] = value
return True
def get_processed_count…How to Build a Materialized View Updater Consumer Mock in Python
A mock consumer that queues change events and triggers refresh callbacks to simulate materialized view updates.
import time
from collections import deque
from dataclasses import dataclass, field
from typing import Callable, Deque, Optional
@dataclass
class MaterializedViewUpdater:
"""Mock updater that consumes change events and refreshes a view."""
refresh: Optional[Callable[[str], None]] = None
queue: Deque[tuple…How to Build a Mock Change Data Capture Event Stream in Python
Generate a deterministic list of mock CDC events with event IDs, stream positions, payloads, and timestamps for testing streaming pipelines.
from itertools import count
from random import choice, randint, seed
from datetime import datetime, timedelta
seed(42) # Make output deterministic
event_types = ["INSERT", "UPDATE", "DELETE"]
table_names = ["users", "orders", "products", "payments"]
counter = count(1)
def mock_cdc_event(stream_index: int) -> dict:
…How to Implement Publish-Subscribe Fanout with Multiple Subscribers in Python
Create a simple publish-subscribe system in Python that broadcasts messages to multiple subscriber callbacks for a given topic.
import time
class PubSub:
def __init__(self):
self.subscribers = {}
def subscribe(self, topic, callback):
if topic not in self.subscribers:
self.subscribers[topic] = []
self.subscribers[topic].append(callback)
def publish(self, topic, message):
if topic in sel…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 Implement an In-Memory Pub/Sub System in Python
This code implements a simple in-memory publish/subscribe system in Python, allowing topics, callbacks, and message broadcasting.
class PubSub:
def __init__(self):
self.topics = {}
def subscribe(self, topic, callback):
if topic not in self.topics:
self.topics[topic] = []
self.topics[topic].append(callback)
return lambda: self.unsubscribe(topic, callback)
def unsubscribe(self, topic, callb…How to Serialize and Deserialize JSON Event Payloads in Python
Define an EventPayload class with custom to_json and from_json methods to convert event objects to JSON strings and back, using datetime parsing.
import json
from datetime import datetime
class EventPayload:
def __init__(self, event_id, event_type, timestamp, data):
self.event_id = event_id
self.event_type = event_type
self.timestamp = timestamp
self.data = data
def to_json(self):
return json.dumps({
…How to Wrap Message Attributes in a CloudEvent with Python
Create a minimal CloudEvent dataclass that wraps arbitrary message attributes into a JSON envelope, matching CloudEvents 1.0 spec.
import json
from dataclasses import dataclass, field, asdict
from typing import Any, Dict
from datetime import datetime, timezone
@dataclass
class CloudEvent:
message_attributes: Dict[str, Any] = field(default_factory=dict)
def wrap(self, event_id: str, source: str, event_type: str, data: Any):
self…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 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 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 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…Python Observability Data Helper for Beginners
A beginner-friendly Python helper to log events, record metrics, summarize observability data, and export it as JSON.
import json
from datetime import datetime
from collections import defaultdict
class ObservabilityDataHelper:
"""Helper for exploring basic observability data patterns."""
def __init__(self):
self.events = []
self.metrics = defaultdict(list)
def log_event(self, service, level, message):
…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 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 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 Eventual Consistency UI Notes in Python
Simulates a UI note that shows local state until a pending server update is confirmed, mocking eventual consistency behavior in distributed systems.
class EventualConsistencyNote:
def __init__(self, entity_id, note):
self.entity_id = entity_id
self.note = note
self.confirmed = False
self.pending_updates = []
def add_pending_update(self, update):
self.pending_updates.append(update)
def confirm_update(self):
…How to Order Partition Key Events in Python (Mock Stream)
Generate a mock event stream grouped by partition key and sort it deterministically by key then sequence in Python.
import itertools
import random
def partition_key_events(keys, events_per_key=3, seed=None):
"""Produce a realistic-looking, but mock, event stream grouped by partition key.
Args:
keys: iterable of partition keys (e.g. strings or ints).
events_per_key: how many events we want per key.
…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"…Browse by section
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