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Python Code Samples

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

1685 matches
Microservices patterns easy

How to Mock an API Gateway Router in Python

Create a lightweight HTTP server that routes requests to mock microservice responses, simulating an API gateway for local development and testing.

api-gateway mock-server http
Python
from http.server import HTTPServer, BaseHTTPRequestHandler
import json


class SimpleGateway(BaseHTTPRequestHandler):
    def do_GET(self):
        routes = {
            "/users": {"service": "user-service", "status": "ok", "count": 42},
            "/orders": {"service": "order-service", "status": "ok", "count": 17}…
17 0 Open
Microservices patterns easy

How to Mock an Ambassador Edge Proxy in Python

Build a lightweight mock Ambassador edge proxy with Python's http.server that responds to health and user endpoint requests for local development and testing.

ambassador mock http-server
Python
import http.server
import json
import urllib.parse
import threading

class AmbassadorProxyHandler(http.server.BaseHTTPRequestHandler):
    def do_GET(self):
        parsed = urllib.parse.urlparse(self.path)
        if parsed.path == "/health":
            self.send_response(200)
            self.send_header("Content-T…
15 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.
       …
15 0 Open
Microservices patterns medium

How to implement a circuit breaker in Python

A Python CircuitBreaker class that tracks failures, opens after a threshold, and retries after a timeout.

circuit-breaker resilience microservices
Python
class CircuitBreaker:
    def __init__(self, failure_threshold=3, timeout=5):
        self.failure_threshold = failure_threshold
        self.timeout = timeout
        self.failure_count = 0
        self.last_failure_time = None
        self.state = "CLOSED"

    def call(self, mock_downstream):
        if self.state …
16 0 Open
Microservices patterns easy

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.

sticky-routing microservices routing
Python
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…
15 0 Open
Microservices patterns easy

How to implement round-robin load balancing in Python

Implement a client-side round-robin load balancer that distributes requests sequentially across a list of mock servers using itertools.cycle.

load balancing round robin microservices
Python
import itertools
import random


class MockServer:
    def __init__(self, name):
        self.name = name

    def handle_request(self, request_id):
        return f"Server {self.name} handled request #{request_id}"


class RoundRobinLoadBalancer:
    def __init__(self, servers):
        self.servers = servers
       …
17 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"…
16 0 Open
Microservices patterns medium

JWT Service-to-Service Authentication Mock in Python

Create and verify HS256 JWTs for service-to-service authentication without external libraries.

jwt authentication hmac
Python
import hashlib
import hmac
import base64
import json
import time


class JWTMock:
    """Minimal JWT service-to-service mock using HS256."""
    
    def __init__(self, secret):
        self.secret = secret.encode()
    
    @staticmethod
    def _b64url_encode(data):
        return base64.urlsafe_b64encode(data).rstr…
17 0 Open
Microservices patterns easy

Mock a Sidecar Logger with Python Metrics

Simulate a sidecar logger that tracks request counts, error rates, and endpoint hits, producing a metrics snapshot.

microservices monitoring metrics
Python
import random
import time
from collections import defaultdict


class SidecarLogger:
    def __init__(self):
        self.metrics = defaultdict(int)
        self.total_requests = 0
        self.error_count = 0

    def log_request(self, endpoint, status_code):
        """Simulate logging a request and updating metrics…
17 0 Open
Microservices patterns medium

Python Saga Compensating Steps Mock

Mock a distributed transaction saga with forward steps and compensating actions that reverse partial progress on failure.

saga microservices compensation
Python
from datetime import datetime


def make_payment(user_id, amount):
    print(f"[{datetime.now():%H:%M:%S}] Payment of ${amount} processed for user {user_id}")
    return {"step": "payment", "status": "ok", "details": f"${amount} charged"}


def deduct_inventory(order_id, items):
    print(f"[{datetime.now():%H:%M:%S}]…
16 0 Open
Microservices patterns easy

Retry idempotent GET requests in Python

A Python function that retries an idempotent GET request a fixed number of times with a delay between attempts, raising a RuntimeError only after all retries fail.

retry idempotent urllib
Python
import time
import urllib.error
import urllib.request
from http.client import HTTPException

def fetch_with_retry(url, max_retries=3, delay=1.0):
    for attempt in range(1, max_retries + 1):
        try:
            with urllib.request.urlopen(url, timeout=5) as response:
                return response.read().decode…
17 0 Open
Microservices patterns medium

Saga pattern orchestration with rollback in Python

Orchestrate a distributed transaction with Saga steps and automated compensation rollback on failure.

saga microservices transaction
Python
import time
import random


class SagaStep:
    def __init__(self, name):
        self.name = name
        self.executed = False

    def execute(self):
        print(f"Executing {self.name}...")
        time.sleep(0.2)
        if random.random() < 0.3:
            raise RuntimeError(f"{self.name} failed")
        sel…
18 0 Open
Microservices patterns easy

Scatter Gather Aggregate Pattern in Python

Simulates a scatter/gather/aggregate pattern by distributing work across items, gathering results, and aggregating them.

scatter-gather aggregation pattern
Python
import random

def process_items(items, scatter_fn, gather_fn, aggregate_fn):
    """Simple scatter/gather/aggregate pattern simulation."""
    scattered = [scatter_fn(item) for item in items]
    gathered = [gather_fn(item) for item in scattered]
    return aggregate_fn(gathered)

if __name__ == "__main__":
    data …
16 0 Open
Microservices patterns easy

Strangler Fig Migration Pattern in Python

Gradually reroute calls from a legacy service to a modern replacement using a runtime switch and feature detection.

migration facade microservices
Python
from dataclasses import dataclass

@dataclass
class PaymentService:
    def process(self, amount: float) -> str:
        return f"Legacy processed ${amount:.2f}"

class StranglerFig:
    def __init__(self):
        self._new_service = None

    def attach_new(self, service):
        self._new_service = service

    de…
16 0 Open
Big data & Spark medium

Approximate Distinct Count in Python with HyperLogLog

Mock a large data stream and estimate the number of distinct items with a HyperLogLog-style probabilistic counter to save memory.

hyperloglog distinct-count probabilistic
Python
import random
import string
from collections import Counter
import math

class ApproxCountDistinct:
    def __init__(self, num_buckets=16):
        self.num_buckets = num_buckets
        self.max_zeros = [0] * num_buckets
        
    def _hash(self, item):
        # Simple string hash to a 32-bit integer
        h = …
20 0 Open
Big data & Spark medium

Bloom Filter Join Mock in Python

A mock hash join that uses a Bloom filter to pre-filter one table before performing an exact match, reducing the number of comparisons in large dataset joins.

bloom filter join hashing
Python
import hashlib
import random
import string


class BloomFilter:
    def __init__(self, size: int = 200, num_hashes: int = 3):
        self.bits = [False] * size
        self.size = size
        self.num_hashes = num_hashes

    def _hashes(self, item: str):
        result = []
        for seed in range(self.num_hashes…
17 0 Open
Big data & Spark easy

Compaction Small Files Mock in Python

Simulates a small-files compaction job by creating small mock files and merging them into a single output file using Python's standard library.

compaction file-io mock
Python
from pathlib import Path
import tempfile
import os


def create_small_files(directory: Path, file_count: int = 5, lines_per_file: int = 3):
    """Create several small mock files with sample content."""
    directory.mkdir(exist_ok=True)
    for i in range(file_count):
        file_path = directory / f"part-{i:04d}.tx…
21 0 Open
Big data & Spark medium

Delta Lake ACID Transaction Log Mock in Python

Simulates Delta Lake's transactional log with JSON files for atomic commits, versioned operations, and crash recovery

delta-lake transaction-log acid
Python
import json
import time
from pathlib import Path

class DeltaLog:
    def __init__(self, path):
        self.log_dir = Path(path)
        self.log_dir.mkdir(parents=True, exist_ok=True)
        self.version = 0

    def _write_txn(self, action, payload):
        txn = {
            "version": self.version,
           …
22 0 Open
Big data & Spark medium

How to Build a DAG Execution Stage Calculator in Python

Computes the execution stages of a directed acyclic graph (DAG) by grouping nodes that become ready simultaneously using topological sorting with Kahn's algorithm.

dag topological-sort kahn-algorithm
Python
from collections import defaultdict, deque


def get_stages(edges):
    """Return list of stages, where each stage is a list of nodes
    that become ready at the same time in a DAG."""
    graph = defaultdict(list)
    in_degree = defaultdict(int)
    nodes = set()

    for src, dst in edges:
        graph[src].appen…
19 0 Open
Big data & Spark medium

How to Create a Mock Iceberg Snapshot Manifest in Python

Build a mock Iceberg snapshot manifest structure with metadata and data entries using Python dictionaries and JSON.

iceberg manifest snapshot
Python
import json
from datetime import datetime, timezone


def create_mock_manifest(snapshot_id: int, file_paths: list[str]) -> dict:
    """Create a mock Iceberg snapshot manifest structure."""
    manifest_file = {
        "manifest_path": f"/warehouse/table/metadata/snap-{snapshot_id}-m0.avro",
        "manifest_length"…
16 0 Open
Big data & Spark easy

How to Create a Mock Kafka Producer in Python

Build a Kafka producer that generates mock streaming records with JSON serialization and error handling for local testing.

kafka streaming producer
Python
import json
import time
from kafka import KafkaProducer
from kafka.errors import KafkaError

def create_mock_producer(bootstrap_servers="localhost:9092", topic="input-topic"):
    """Create a Kafka producer that generates mock streaming data."""
    producer = KafkaProducer(
        bootstrap_servers=bootstrap_servers…
19 0 Open
Big data & Spark easy

How to Filter and Project Spark DataFrames with PySpark SQL

Simulate a SQL SELECT with WHERE using PySpark DataFrame select and filter to project columns and apply conditions.

pyspark dataframe filter
Python
from pyspark.sql import SparkSession
from pyspark.sql.functions import col

spark = SparkSession.builder.appName("QueryFilterMock").master("local[2]").getOrCreate()

data = [
    ("Alice", 28, "Engineering"),
    ("Bob", 35, "Sales"),
    ("Carol", 32, "Engineering"),
    ("David", 25, "Marketing"),
    ("Eve", 29, "E…
18 0 Open
Big data & Spark easy

How to Implement MapReduce Word Count in Python Using a Dict

Simulate a MapReduce word count pipeline in Python with a mock dict, splitting text into words, shuffling, and reducing to frequency counts.

mapreduce word-count dictionary
Python
def map_reduce_word_count(text: str) -> dict:
    """Simulate a MapReduce pipeline to count word frequencies."""
    # MAP phase: split into words and emit (word, 1) pairs
    mapped = []
    for word in text.lower().split():
        # Clean word of punctuation
        clean_word = ''.join(char for char in word if cha…
16 0 Open
Big data & Spark medium

How to Implement a Mock MapReduce for Word Count in Python

Simulates a MapReduce word count pipeline with mapper, shuffle, and reducer phases using Python dicts and standard library modules.

mapreduce word-count big-data
Python
from collections import defaultdict
import re

def mapper(text):
    """Split text into words and emit (word, 1) pairs."""
    words = re.findall(r'\b\w+\b', text.lower())
    return [(word, 1) for word in words]

def reducer(pairs):
    """Group word-count pairs and sum counts."""
    counts = defaultdict(int)
    fo…
19 0 Open

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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

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  3. Run it in the IDE, tweak values, then take a related quiz or tutorial lesson

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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.