Reference library

Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

48 matches
Streaming & messaging medium

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.

kafka mock streaming
Python
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"…
13 0 Open
Streaming & messaging easy

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.

json serialization datetime
Python
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({
          …
12 0 Open
Streaming & messaging medium

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.

streaming join generator
Python
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(
            …
14 0 Open
Streaming & messaging medium

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.

session-window streaming timeout
Python
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…
13 0 Open
Streaming & messaging easy

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.

cloudevents messaging dataclasses
Python
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…
13 0 Open
Streaming & messaging medium

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.

cqrs projector read-model
Python
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…
11 0 Open
Streaming & messaging medium

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.

outbox-pattern sqlite transactions
Python
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…
17 0 Open
Streaming & messaging medium

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.

pubsub mock events
Python
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, []):
    …
16 0 Open
Streaming & messaging hard

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.

protobuf binary-encoding varint
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)
  …
11 0 Open
Streaming & messaging medium

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.

watermark streaming side output
Python
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…
11 0 Open
Observability & SRE easy

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.

observability sre metrics
Python
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…
14 0 Open
Observability & SRE medium

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.

alerts grouping monitoring
Python
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"]…
12 0 Open
Observability & SRE easy

How to Model Span Events in Python

Define a Span class with timestamped milestone events and a completion marker to track operation lifecycle.

observability dataclasses tracing
Python
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…
14 0 Open
Observability & SRE easy

Python Observability Data Helper for Beginners

A beginner-friendly Python helper to log events, record metrics, summarize observability data, and export it as JSON.

observability logging metrics
Python
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):
…
14 0 Open
Microservices patterns easy

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.

event-sourcing microservices mock
Python
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…
14 0 Open
Microservices patterns easy

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.

deduplication event-processing hashing
Python
```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…
12 0 Open
Microservices patterns easy

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.

outbox domain-events microservices
Python
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 =…
13 0 Open
Microservices patterns medium

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.

saga microservices events
Python
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…
13 0 Open
Microservices patterns easy

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.

partition events sorting
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.
       …
11 0 Open
Microservices patterns easy

Idempotent Consumer Event Processing in Python

Track processed event IDs to skip duplicates and count event types for a reliable, idempotent consumer.

idempotency events microservices
Python
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"…
13 0 Open
Big data & Spark medium

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.

spark streaming micro-batch
Python
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…
13 0 Open
Big data & Spark medium

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.

tumbling-window streaming aggregation
Python
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:
         …
13 0 Open
Big data & Spark easy

Session window gap mock in Python

Group sorted timestamps into sessions where any gap between consecutive events exceeds a threshold starts a new session.

timestamps sessions windowing
Python
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…
14 0 Open
A/B testing & experimentation easy

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.

mocking events testing
Python
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…
16 0 Open

Browse by section

Each section groups closely related Python snippets.

Guide: free Python code samples library

Copy-ready Python snippets for learners and developers

PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.

How to use this library

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. Run it in the IDE, tweak values, then take a related quiz or tutorial lesson

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.