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Python Code Samples

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

68 matches
API design & gRPC easy

Generate an OpenAPI Spec from Mock Routes in Python

This Python script generates an OpenAPI 3.0 specification from a simple mock routes dictionary, mapping each HTTP method to response examples.

openapi api-docs api-design
Python
import json
from pathlib import Path


def generate_openapi_spec(routes: dict, title: str = "Mock API", version: str = "1.0.0") -> dict:
    paths = {}
    for route, methods in routes.items():
        path_item = {}
        for method, response_data in methods.items():
            method = method.lower()
            …
15 0 Open
API design & gRPC medium

How to Build a Mock REST GET Endpoint Handler in Python

Create a lightweight mock REST GET server in Python using the standard library, with a dict-based route registry that maps paths to handler functions and returns JSON responses with proper HTTP status codes.

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

# Mock API handler registry
def handle_users():
    return {"status": "ok", "data": [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]}

def handle_products():
    return {"status": "ok", "data": [{"id": 101, "name": "Laptop", "price": 999.99}…
14 0 Open
Streaming & messaging easy

How to Partition and Order Kafka-Style Messages by Key in Python

Group messages with the same key into ordered buckets using hashing and a defaultdict, mimicking Kafka partition ordering.

streaming partitioning kafka-pattern
Python
from dataclasses import dataclass
from collections import defaultdict

@dataclass
class Message:
    key: str
    content: str

def partition_and_order(messages, num_partitions=3):
    partitions = defaultdict(list)
    for msg in messages:
        partition_id = hash(msg.key) % num_partitions
        partitions[parti…
14 0 Open
Caching & Redis medium

Consistent Hashing Cache Shard in Python

A minimal consistent hashing ring with virtual nodes that distributes cache keys across shards and minimizes re-mapping when a node is removed.

caching sharding consistent-hashing
Python
import hashlib
import bisect


class ConsistentHashRing:
    def __init__(self, nodes=None, replicas=3):
        self.replicas = replicas
        self.ring = {}
        self.sorted_keys = []
        if nodes:
            for node in nodes:
                self.add_node(node)

    def _hash(self, key):
        return i…
16 0 Open
Reliability & rate limiting medium

How to Implement a Bulkhead Pattern with Threading in Python

Implement a bulkhead pattern in Python that isolates concurrent tasks with a bounded semaphore, limiting active workers to prevent resource exhaustion.

bulkhead threading semaphore
Python
import threading
import time
import random


class Bulkhead:
    def __init__(self, workers: int):
        self._semaphore = threading.BoundedSemaphore(workers)
        self._lock = threading.Lock()
        self._active = 0

    def run(self, task):
        with self._semaphore:
            with self._lock:
          …
13 0 Open
Observability & SRE easy

How to Route Alerts by Severity in Python

Map alert severity levels to routing targets and simulate dispatching alerts to on-call pages, email, Slack, or logs.

observability alerts routing
Python
def main():
    # Severity levels with corresponding alert routing targets
    routing_map = {
        "critical": "call_page",
        "high": "call_page",
        "medium": "email_team",
        "low": "slack_channel",
        "info": "log_only"
    }

    # Simulated alerts with severity
    alerts = [
        {"na…
12 0 Open
Microservices patterns medium

Bulkhead Thread Pool per Service Mock in Python

Simulates a bulkhead pattern with per-service thread pools and semaphore-based rejection to isolate failures between dependent services.

bulkhead threadpool semaphore
Python
import threading
import time
import random
from concurrent.futures import ThreadPoolExecutor

class ServiceBulkhead:
    def __init__(self, name, max_threads, max_queue):
        self.name = name
        self.executor = ThreadPoolExecutor(max_workers=max_threads)
        self.semaphore = threading.Semaphore(max_thread…
12 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…
15 0 Open
Big data & Spark medium

How to Simulate a MapReduce Mock with Combine Phase in Python

Simulates a MapReduce pipeline with a combiner that aggregates local counts per reducer to reduce network and compute overhead.

mapreduce combiner hadoop
Python
from collections import defaultdict

def map_phase(lines):
    intermediate = defaultdict(list)
    for line in lines:
        for word in line.strip().lower().split():
            intermediate[word].append(1)
    return dict(intermediate)

def combine_phase(intermediate, num_reducers=3):
    combined = defaultdict(li…
14 0 Open
Big data & Spark medium

Mock RDD in Python: Simulate Spark RDD Lazy Transformations

Simulate Apache Spark RDD behavior in Python with lazy maps, filters, partitions, and a collect action.

spark rdd big-data
Python
import random

def mock_rdd(data, num_slices=2):
    """
    A simple simulation of Spark RDD behavior with lazy evaluation,
    transformations, and an action.
    """
    class SimpleRDD:
        def __init__(self, data, num_slices=2):
            self.data = data
            self.num_slices = num_slices
           …
13 0 Open
ML engineering pipelines medium

How to Mock Kedro Pipeline Nodes in Python

Create a modular Kedro pipeline with node functions, namespacing, and input/output mapping to mock pipeline execution locally.

kedro pipeline modular
Python
from kedro.pipeline import Pipeline, node
from kedro.pipeline.modular_pipeline import pipeline as modular_pipeline


def preprocess(data: list) -> list:
    """Clean data by removing None values."""
    return [item for item in data if item is not None]


def transform(data: list) -> list:
    """Add 1 to each numeric…
15 0 Open
A/B testing & experimentation easy

How to Hash a User ID to an Experiment Bucket in Python

Deterministically map a user ID to one of N experiment buckets using MD5 hashing and modulo arithmetic.

hashing ab-testing bucketing
Python
import hashlib

def hash_to_bucket(user_id: str, num_buckets: int = 10) -> int:
    """Deterministically map a user_id to a bucket (0 to num_buckets-1)."""
    digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
    return int(digest[:8], 16) % num_buckets

if __name__ == "__main__":
    # Mock experiment: split…
14 0 Open
A/B testing & experimentation easy

How to hash user IDs to experiment buckets in Python

Deterministically map a user ID to an experiment bucket using MD5 hashing, ensuring stable and consistent assignment for A/B testing.

hashing ab-testing experiments
Python
import hashlib


def hash_user_to_bucket(user_id: str, num_buckets: int = 10) -> int:
    """Deterministically map a user ID to an experiment bucket (0..num_buckets-1)."""
    digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
    return int(digest, 16) % num_buckets


if __name__ == "__main__":
    mock_users …
12 0 Open
Database scaling & optimization medium

Consistent Hashing with Virtual Buckets in Python

This code maps many virtual buckets onto a few physical buckets using a consistent hashing ring, ensuring balanced distribution with minimal remapping when physical buckets change.

consistent-hashing virtual-buckets sharding
Python
import random

class VirtualBuckets:
    """Maps many virtual buckets onto few physical buckets using consistent hashing."""
    
    def __init__(self, physical_buckets, virtual_factor=100):
        self.physical = list(physical_buckets)
        self.virtual_factor = virtual_factor
        self.ring = []
        self…
13 0 Open
Database scaling & optimization easy

Geo shard by region in Python

Maps users to database shards based on geographic region with a deterministic hash fallback.

sharding geolocation database
Python
import json
from collections import defaultdict

REGION_SHARD_MAP = {
    "na": ["shard-01", "shard-02"],
    "eu": ["shard-03", "shard-04", "shard-05"],
    "ap": ["shard-06"],
    "sa": ["shard-07", "shard-08"],
}

# user_id -> region (mock lookup)
USER_REGIONS = {
    "u_1001": "na",
    "u_1002": "eu",
    "u_1003…
13 0 Open
Database scaling & optimization medium

How to Build a Shard Map Mock Dict in Python

Implement a dictionary-like class that distributes keys across multiple shards using Python's hash() for realistic data partitioning.

dict sharding hash
Python
class ShardMap:
    def __init__(self, shard_count):
        self.shards = {i: {} for i in range(shard_count)}
        self.shard_count = shard_count

    def _shard_for(self, key):
        return hash(key) % self.shard_count

    def __getitem__(self, key):
        return self.shards[self._shard_for(key)][key]

    d…
14 0 Open
Database scaling & optimization medium

How to Implement Consistent Hashing in Python

Build a consistent hash ring in Python that distributes keys across nodes and minimizes remapping when nodes are added or removed.

consistent-hashing distributed-systems sharding
Python
import hashlib
from bisect import bisect_right


class ConsistentHashRing:
    def __init__(self, nodes, replicas=3):
        self.replicas = replicas
        self.ring = {}
        self.sorted_keys = []
        for node in nodes:
            self.add_node(node)

    def _hash(self, key):
        return int(hashlib.md…
15 0 Open
Database scaling & optimization easy

How to Shard Data by User ID Hash in Python

Deterministically map user IDs to shard indexes using an MD5 hash modulo the shard count in Python.

sharding hashing md5
Python
import hashlib

def shard_id(user_id: str, num_shards: int = 4) -> int:
    """Deterministically map a user_id to a shard index using MD5."""
    digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
    return int(digest[:8], 16) % num_shards

if __name__ == "__main__":
    user_ids = ["alice", "bob", "carol", "d…
12 0 Open
Production deployment patterns medium

Mock ConfigMap Mount Environment Variables in Python

Simulate reading environment variables from a Kubernetes ConfigMap-mounted directory and test it with mocks.

kubernetes configmap mocking
Python
import os
import tempfile
from unittest.mock import patch

def load_config_from_mount(mount_path):
    """Simulate reading environment variables from a ConfigMap-mounted directory."""
    config = {}
    for filename in os.listdir(mount_path):
        file_path = os.path.join(mount_path, filename)
        if os.path.i…
14 0 Open

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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

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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.