Streaming & messaging
Kafka-style pub/sub, event consumers, async pipelines, and message-driven workflows.
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…How to Aggregate Periodic Snapshot Data in Python
Generates mock snapshot data and groups values into periods to compute average aggregates with Python's standard library.
import random
from collections import defaultdict
def snapshot_aggregate(n=10, period=3):
data = defaultdict(list)
for i in range(n):
key = f"item_{i % period}"
data[key].append(random.randint(1, 100))
return dict(data)
def aggregate_periodic(snapshots, period=3):
result = {}
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Streaming & messaging — Python code examples
What you will find here
This page collects streaming & messaging snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.