Reference library

Python Code Samples

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

36 matches
Errors & debugging easy

How to Use Optional Return in Python Instead of Raising Exceptions

A Python function returns None for missing dictionary keys instead of raising KeyError, enabling graceful lookup handling with type hints.

optional typing dict-get
Python
from typing import Optional


def find_user(users: dict, user_id: int) -> Optional[dict]:
    """
    Look up a user by ID. Returns the user dict if found,
    otherwise returns None instead of raising KeyError.
    """
    return users.get(user_id)


def main() -> None:
    users = {
        1: {"name": "Alice", "ema…
14 0 Open
Errors & debugging easy

Map Exception Type to HTTP Status Code in Python

Maps Python exception types to appropriate HTTP status codes using a dictionary lookup for consistent API error handling.

exceptions http-status error-handling
Python
EXCEPTION_STATUS_MAP = {
    ValueError: 400,
    KeyError: 400,
    TypeError: 400,
    PermissionError: 403,
    FileNotFoundError: 404,
    AttributeError: 404,
    TimeoutError: 408,
    NotImplementedError: 501,
    ConnectionError: 503,
}


def status_code_for(exception_type):
    try:
        return EXCEPTION_S…
13 0 Open
Dictionaries & sets easy

Check Invertible Mapping for Duplicate Values in Python

Detect duplicate values among (key, value) pairs to ensure the mapping is invertible, using a dictionary for O(1) lookups.

dictionary mapping duplicate-check
Python
def invertible_after_dedup(pairs):
    """
    Check whether a set of (key, value) pairs is invertible,
    i.e., no duplicate values exist for different keys.
    """
    seen = {}
    for key, value in pairs:
        if value in seen and seen[value] != key:
            return False, f"Duplicate value '{value}' for k…
16 0 Open
Dictionaries & sets medium

Get Nested Dict Value with Default in Python

Access values deep inside a nested dictionary using a dotted path string, returning a default when any key is missing.

dictionaries nested default-value
Python
def get_nested(d, path, default=None):
    """Walk a nested dict along a dotted path, returning default if missing."""
    current = d
    for key in path.split("."):
        if isinstance(current, dict) and key in current:
            current = current[key]
        else:
            return default
    return current
…
16 0 Open
Dictionaries & sets medium

How to Build a Two-Way Dictionary in Python

Implement a BiDict class that supports both forward key-to-value and reverse value-to-key lookups with a simple add, delete, and update API.

dictionary bidirectional class
Python
class BiDict:
    def __init__(self, data=None):
        self.forward = {}
        self.backward = {}
        if data:
            self.update(data)

    def update(self, data):
        for key, value in data.items():
            self[key] = value

    def __setitem__(self, key, value):
        self.forward[key] = val…
11 0 Open
Dictionaries & sets easy

How to Index a List of Records by Unique ID in Python

Build a dictionary that maps each record's unique id to the record itself from a list of dictionaries.

dictionary index records
Python
from typing import List, Dict, Any

def index_by_id(records: List[Dict[str, Any]], id_field: str = "id") -> Dict[Any, Dict[str, Any]]:
    """Build a dictionary mapping each record's unique id to the record itself."""
    return {record[id_field]: record for record in records}

if __name__ == "__main__":
    sample_re…
15 0 Open
Dictionaries & sets easy

How to Invert a Dictionary in Python Safely

Swap dictionary keys and values while detecting duplicate values to prevent silent data loss.

dictionary inversion data-safety
Python
def invert_dict_safely(d):
    inverted = {}
    for key, value in d.items():
        if value not in inverted:
            inverted[value] = key
        else:
            raise ValueError(f"Duplicate value '{value}' would cause data loss")
    return inverted


if __name__ == "__main__":
    sample = {"a": 1, "b": 2,…
15 0 Open
Dictionaries & sets easy

How to Use ChainMap for Layered Config Lookup in Python

This code demonstrates using collections.ChainMap to combine multiple dictionaries into a single layered lookup, where earlier maps override later ones.

chainmap configuration collections
Python
from collections import ChainMap

defaults = {"theme": "light", "lang": "en", "debug": False}
user = {"lang": "de", "auto_save": True}
runtime = {"debug": True}

config = ChainMap(runtime, user, defaults)

if __name__ == "__main__":
    print("theme:", config["theme"])
    print("lang:", config["lang"])
    print("deb…
14 0 Open
Dictionaries & sets easy

How to Use a Frozenset as a Dict Key in Python

Demonstrates using an immutable frozenset as a hashable dictionary key, including equality and lookup with differently-ordered elements.

frozenset dictionary hashable
Python
frozen = frozenset({"a", "b", "c"})
mapping = {frozen: "set as hashable key"}
other_frozen = frozenset(["c", "b", "a"])
print(f"Are keys equal? {frozen == other_frozen}")
print(f"Lookup with different order: {mapping[other_frozen]}")
print(f"Hash matches: {hash(frozen) == hash(other_frozen)}")
13 0 Open
Algorithms & data structures medium

Find Longest Consecutive Sequence in Python

Find the length of the longest consecutive elements sequence in an unsorted array using a set for O(n) lookups.

set longest-sequence hash-table
Python
def longest_consecutive_length(nums):
    num_set = set(nums)
    longest = 0
    
    for num in num_set:
        if num - 1 not in num_set:
            current = num
            current_streak = 1
            
            while current + 1 in num_set:
                current += 1
                current_streak += 1
…
13 0 Open
Algorithms & data structures medium

Implement Insert Delete GetRandom O(1) in Python

Build a RandomizedSet class that supports insert, delete, and get_random in average O(1) time using a list and a dictionary mapping values to indices.

randomized-set o1-lookup hash-map
Python
import random

class RandomizedSet:
    def __init__(self):
        self.values = []
        self.index_map = {}

    def insert(self, val):
        if val in self.index_map:
            return False
        self.index_map[val] = len(self.values)
        self.values.append(val)
        return True

    def delete(self…
12 0 Open
Comprehensions & generators easy

Merge Data with Comprehension and Generator in Python

Merge user and order data using a dictionary comprehension for lookups and a generator expression to filter and transform orders.

dictionary-comprehension generator-expression data-merging
Python
def merge_data(users, orders):
    """
    Merge user and order data using a dictionary comprehension
    and a generator expression for filtering.
    """
    # Build a lookup: user_id -> user name
    user_map = {user["id"]: user["name"] for user in users}

    # Generator: yield orders with user names attached
    …
14 0 Open
AI & LLM integration patterns easy

Route Tool Call Name to Python Handler Dict

Routes a tool call name to the correct Python handler function using a dictionary lookup, returning an error for unknown tools.

tool-calls llm-integration dictionary-mapping
Python
def get_name():
    return {"name": "Alice"}

def get_age():
    return {"age": 30}

def get_email():
    return {"email": "alice@example.com"}

handlers = {
    "get_name": get_name,
    "get_age": get_age,
    "get_email": get_email,
}

def route(tool_call):
    handler = handlers.get(tool_call["name"])
    if handl…
12 0 Open
Automation & scripting medium

How to Build a Mock Route53 DNS API in Python

Create a mock DNS API server in Python that simulates Route53 record lookups and updates using the standard library.

mock-server dns http-server
Python
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse, parse_qs


class DNSUpdateHandler(BaseHTTPRequestHandler):
    records = {"example.com": "1.2.3.4"}

    def do_GET(self):
        domain = parse_qs(urlparse(self.path).query).get("domain", [""])[0]
        if dom…
13 0 Open
Automation & scripting easy

How to Perform a DNS Lookup for A Records in Python

Resolve a hostname to IPv4 A records using Python's built-in socket.getaddrinfo and return a sorted list of addresses.

dns socket network
Python
import socket

def get_a_records(hostname):
    """Fetch A records (IPv4 addresses) for a given hostname."""
    try:
        # getaddrinfo with family AF_INET restricts to IPv4 (A records)
        infos = socket.getaddrinfo(hostname, None, socket.AF_INET)
        # Each info tuple: (family, type, proto, canonname, so…
13 0 Open
Data pipelines & processing easy

Enrich Events with Geo IP Data in Python

Returns a copy of each event dictionary, enriched with a geo-location dict from a mock IP-to-geo lookup table, with a fallback for unknown IPs.

data-enrichment dictionaries pipelines
Python
import ipaddress


GEO_IP_DB = {
    "192.168.1.10": {"country": "US", "city": "New York", "lat": 40.7128, "lon": -74.0060},
    "10.0.0.5": {"country": "DE", "city": "Berlin", "lat": 52.5200, "lon": 13.4050},
    "172.16.0.8": {"country": "JP", "city": "Tokyo", "lat": 35.6762, "lon": 139.6503},
}

EVENTS = [
    {"id…
14 0 Open
Data pipelines & processing medium

Enrich a stream with reference data by key lookup in Python

Uses streamz to join each incoming record to a reference dictionary by name, adding department and level fields or defaults.

streamz streaming join
Python
from streamz import Stream

reference = {"alice": {"dept": "eng", "level": 3}, "bob": {"dept": "sales", "level": 5}}

def enrich(record):
    name = record.get("name")
    ref = reference.get(name)
    joined = dict(record)
    if ref:
        joined.update(ref)
    else:
        joined["dept"] = "unknown"
        joi…
13 0 Open
Data pipelines & processing medium

How to perform a star schema join in Python

Denormalize mock fact and dimension tables by building lookup dicts and enriching each sales fact with customer, product, and date attributes.

star-schema data-joins dimensional-modeling
Python
from datetime import date

# Mock dimension tables
customers = [
    {"customer_id": 1, "name": "Alice", "city": "New York"},
    {"customer_id": 2, "name": "Bob", "city": "Los Angeles"},
    {"customer_id": 3, "name": "Carol", "city": "Chicago"},
]

products = [
    {"product_id": 101, "name": "Laptop", "category": "…
12 0 Open
API design & gRPC easy

How to Mock a GraphQL Query Type in Python

Create a lightweight mock of a GraphQL Query type to simulate repository lookups without a server.

graphql mock resolver
Python
import json

class Query:
    def __init__(self):
        self.starred_repos = [
            {"id": 1, "name": "graphql", "owner": "graphql"}
        ]

    def repository(self, name):
        if name == "graphql":
            return {"id": 1, "name": "graphql", "stargazerCount": 85000}
        return None


if __name…
14 0 Open
Streaming & messaging easy

Dedupe processed message IDs in Python

Filters an inbox of messages by removing items whose IDs have already been processed, using a set for fast lookups.

deduplication streaming json
Python
from pathlib import Path
import json


def dedupe_processed_ids(inbox_file: Path, processed_file: Path) -> list:
    processed = set(json.loads(processed_file.read_text()))
    inbox = json.loads(inbox_file.read_text())
    deduped = [item for item in inbox if item["id"] not in processed]
    return deduped


if __nam…
12 0 Open
Caching & Redis medium

How to Build a Bloom Filter to Reduce Cache Misses in Python

Implement a probabilistic Bloom filter in Python that lets a cache quickly determine which keys are definitely not present, reducing expensive source lookups on cache misses.

bloom-filter caching probabilistic
Python
import hashlib
import random

class BloomFilter:
    def __init__(self, size=100, num_hashes=3):
        self.size = size
        self.num_hashes = num_hashes
        self.bit_array = [0] * size

    def _hashes(self, item):
        result = []
        for i in range(self.num_hashes):
            hash_value = int(hash…
14 0 Open
Caching & Redis medium

How to Implement a Negative Cache with TTL in Python

This code provides a TTL mock cache that stores negative results (cache misses) for a short time to reduce repeated lookups of missing keys.

cache ttl negative-cache
Python
from time import time, sleep

class TTLMockCache:
    def __init__(self, ttl_seconds=5):
        self.ttl = ttl_seconds
        self.store = {}
        self.negative_cache = {}

    def get(self, key):
        now = time()
        if key in self.store:
            value, expires_at = self.store[key]
            if exp…
12 0 Open
Caching & Redis easy

Simple Redis Cache Helper in Python

Build a minimal Redis-backed cache with TTL, JSON serialization, and automated fetching to speed up repeated expensive lookups.

redis caching cache-aside
Python
import time
import redis
import json


class SimpleCache:
    def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
        self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
        self.default_ttl = default_ttl

    def get(self, key):
        value = self.client.get(key)…
10 0 Open
Microservices patterns easy

How to Mock a Service Registry in Python with an In-Memory Dict

A lightweight ServiceRegistry class backed by a dict, exposing register, unregister, lookup, list, and health-check methods.

microservices service-registry dictionary
Python
class ServiceRegistry:
    def __init__(self):
        self._services = {}

    def register(self, name, endpoint, version="1.0"):
        self._services[name] = {
            "endpoint": endpoint,
            "version": version,
            "status": "healthy"
        }

    def unregister(self, name):
        return…
13 0 Open

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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.