Python Code
Samples
Easy snippets you can copy, study, and run in the browser editor.
How to Group Rows by Key into Nested Arrays in Python
This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.
from collections import defaultdict
def implode_rows(rows, key, value_key):
grouped = defaultdict(list)
for row in rows:
grouped[row[key]].append(row[value_key])
return dict(grouped)
if __name__ == "__main__":
data = [
{"category": "fruit", "item": "apple"},
{"category": "fr…How to Reduce Aggregate Counts from Mapped Chunks in Python
Combine a list of mapped chunk dictionaries into a single aggregated count dictionary using functools.reduce.
from functools import reduce
from collections import defaultdict
def aggregate_chunks(mapped_chunks):
"""Combine mapped chunk counts into a single aggregate dict."""
return reduce(
lambda acc, chunk: {
**acc,
**{k: acc.get(k, 0) + v for k, v in chunk.items()}
},
…Build a Recipe Runner Mock in Python
A Python script that mocks a command runner recipe system: maps recipe names to shell commands, executes them with subprocess, and prints the output and exit code.
import subprocess
import sys
def run_recipe(recipe: str) -> None:
"""Simulate a command runner recipe by printing the command and exit code."""
print(f"Running recipe: {recipe}")
result = subprocess.run(recipe, shell=True, capture_output=True, text=True)
print(f"Exit code: {result.returncode}")
i…How to Use ThreadPoolExecutor in Python for Parallel Processing
Use ThreadPoolExecutor with executor.map to run a function over many inputs concurrently and collect ordered results.
def worker(item):
return item * item
if __name__ == "__main__":
from concurrent.futures import ThreadPoolExecutor
numbers = list(range(1, 11))
with ThreadPoolExecutor(max_workers=4) as executor:
results = list(executor.map(worker, numbers))
print("Input: ", numbers)
print("Results:", …How to Use pool.map for CPU-Bound Tasks in Python
Distribute CPU-intensive functions across processes with multiprocessing.Pool.map and measure the performance gain.
from multiprocessing import Pool
import time
def cpu_bound_task(n):
"""Mock CPU-bound work: compute sum of squares."""
total = 0
for i in range(n):
total += i * i
return total
if __name__ == "__main__":
numbers = [10_000_000, 12_000_000, 8_000_000, 15_000_000]
start = time.perf_count…How to Implement a Data Helper Class in Python
Build a beginner-friendly DataHelper class using dataclasses and key system design patterns like Command, Strategy, and Map.
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
@dataclass
class DataHelper:
"""A beginner-friendly data utility with common system design patterns."""
data: List[Dict[str, Any]] = field(default_factory=list)
def add_record(self, r…How to Implement a Factory Method by Type String in Python
A factory method maps a type string to a class, creating and returning the appropriate object instance while handling unknown types gracefully.
class Animal:
def speak(self):
raise NotImplementedError
class Dog(Animal):
def speak(self):
return "Woof!"
class Cat(Animal):
def speak(self):
return "Meow!"
class AnimalFactory:
@staticmethod
def create(animal_type: str) -> Animal:
animal_types = {
…Route Messages to Handlers with a Python Dict
This code demonstrates a simple message routing pattern using a dictionary to map topic keys to handler functions, with a default handler for unmatched topics.
def route_message(message, routing_table):
"""Route a message to the correct handler based on the topic key."""
topic = message.get("topic", "default")
handler = routing_table.get(topic, routing_table.get("default"))
return handler(message)
def handle_orders(message):
return f"Orders handler proc…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.
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()
…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.
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…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.
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…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.
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…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.
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…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.
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 …Geo shard by region in Python
Maps users to database shards based on geographic region with a deterministic hash fallback.
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…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.
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…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
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- 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.