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How to Mock a Kafka Producer Batch Send in Python
Simulate a Kafka producer in Python that sends batched JSON events with mock partitions and latency for testing streaming pipelines without a real broker.
import json
import random
import time
from datetime import datetime
class MockKafkaProducer:
def __init__(self, topic):
self.topic = topic
self.sent_messages = []
def send(self, value, key=None):
message = {
"topic": self.topic,
"key": key,
"value"…
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 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(
…
How to Track Session Windows with Gap Timeout in Python
A Python class that groups events into sessions, closing a session when the gap between events exceeds a timeout threshold.
import time
class SessionWindow:
"""Track sessions with a gap timeout (mock)."""
def __init__(self, timeout_seconds=5):
self.timeout = timeout_seconds
self.session_start = None
self.last_event_time = None
self.event_count = 0
self.events = []
def add_event…
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 mock a CQRS projector read model update in Python
Build a CQRS projector class that maintains denormalized read models by applying domain events in a mock order-processing service.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class OrderReadModel:
order_id: str
customer_name: str
total: float
status: str = "pending"
items: List[Dict] = field(default_factory=list)
def apply_event(self, event_type: str, payload: Dict) -> Non…
Implement the Transactional Outbox Pattern with SQLite in Python
A Python implementation of the transactional outbox pattern using SQLite, ensuring atomic writes of order data and outbox events in a single transaction while supporting reliable message publishing and consumption.
import sqlite3
from dataclasses import dataclass
from datetime import datetime, timezone
import json
@dataclass
class Order:
order_id: str
amount: float
status: str
class TransactionalOutbox:
def __init__(self, db_path=":memory:"):
self.conn = sqlite3.connect(db_path)
self._create_tab…
In-Memory PubSub Topic Subscribe Mock in Python
Build a thread-safe in-memory publish/subscribe mock where handlers subscribe to named topics and receive every message published to them.
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)
def publish(self, topic, message):
for callback in self.topics.get(topic, []):
…
Mock Protobuf Binary Encoding in Python
Demonstrates a minimal protobuf-like binary encoding and decoding of an event dataclass using varints and length-delimited fields in pure Python.
import struct
from dataclasses import dataclass
@dataclass
class Event:
id: int
user_id: int
action: str
def encode(self) -> bytes:
# Mock protobuf-like binary encoding using varint and length-delimited fields
buf = bytearray()
# field 1: varint id (tag = (1 << 3) | 0 = 8)
…
Mock Watermark Late Event Side Output in Python
Simulates watermarking in a streaming pipeline by classifying events as on-time or late using timestamps and delays.
from datetime import datetime, timedelta
from typing import List, Tuple
def watermark_mock(
events: List[Tuple[datetime, str]], watermark_delay: timedelta, max_delay: timedelta
) -> Tuple[List[Tuple[datetime, str]], List[Tuple[datetime, str]]]:
"""Simulate watermarking: events arriving on time vs. late by ch…
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 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 a Choreography Saga in Python
Simulate a choreography-based saga with event envelopes, status tracking, and compensating actions to model distributed transactions.
import json
from dataclasses import dataclass, asdict
from typing import List, Optional
from enum import Enum
class SagaStatus(Enum):
PENDING = "PENDING"
COMPLETING = "COMPLETING"
COMPLETED = "COMPLETED"
FAILED = "FAILED"
@dataclass
class EventEnvelope:
event_type: str
order_id: str
sta…
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"…
How to Mock Spark Streaming Micro-Batches in Python
Simulate Spark's micro-batch streaming with a simple deque-based class that collects events over time and processes them in timed batches.
import time
from collections import deque
from datetime import datetime
class MicroBatchStream:
def __init__(self, batch_interval_sec=2):
self.batch_interval = batch_interval_sec
self.source = deque()
self.processed = []
def add_events(self, events):
self.source.extend(events…
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:
…
Session window gap mock in Python
Group sorted timestamps into sessions where any gap between consecutive events exceeds a threshold starts a new session.
from datetime import datetime, timedelta
def session_windows(timestamps, gap_seconds=300):
"""Group timestamps into sessions where gaps > gap_seconds start new sessions."""
if not timestamps:
return []
# Sort timestamps chronologically to ensure correct windowing
timestamps = sorted(timestam…
How to Mock an Exposure Event Log Record in Python
Generate a realistic exposure event record with UUID, UTC timestamp, and risk level for testing or experimentation.
import uuid
from datetime import datetime, timezone
def mock_exposure_event(person_id: str, location: str, duration_minutes: int) -> dict:
return {
"event_id": str(uuid.uuid4()),
"person_id": person_id,
"location": location,
"duration_minutes": duration_minutes,
"timestamp…
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