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Python Code Samples

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

148 matches
Cloud + Python easy

Mock ECS Task Run Stop Status Dict in Python

Build a mock ECS task status dictionary with RUNNING/STOPPED states using the standard library.

aws ecs mocking
Python
from datetime import datetime, timezone


def mock_ecs_task_status(task_id: str, state: str = "RUNNING") -> dict:
    """Return a mock ECS task status dictionary."""
    return {
        "taskArn": f"arn:aws:ecs:us-east-1:123456789012:task/cluster/{task_id}",
        "taskDefinition": "arn:aws:ecs:us-east-1:1234567890…
15 0 Open
Modern tooling easy

How to Validate Data with a Simple Dict-Based Rules Helper in Python

Validates a dictionary against a set of callable rules, printing pass/fail per field and returning an overall boolean.

validation dictionary helper
Python
import json
from pathlib import Path
from typing import Any, Callable


def validate_data(
    data: dict[str, Any],
    rules: dict[str, Callable[[Any], bool]],
    path: Path | None = None,
) -> bool:
    """Validate a dict against a set of simple rules."""
    all_valid = True
    for field, validator in rules.item…
15 0 Open
Concurrency & performance medium

How to Share a Dict and List Between Processes with multiprocessing Manager in Python

This code demonstrates how to share a dictionary and a list between multiple processes using multiprocessing.Manager, enabling safe concurrent updates.

multiprocessing manager shared-state
Python
import multiprocessing as mp


def worker(shared_dict, shared_list, name):
    shared_dict[name] = name.upper()
    shared_list.append(name)
    print(f"{name} added to shared structures")


def main():
    with mp.Manager() as manager:
        shared_dict = manager.dict()
        shared_list = manager.list()

       …
14 0 Open
Concurrency & performance medium

How to Use a Weakref Cache to Avoid Memory Leaks in Python

This code demonstrates building a value cache with weakref.WeakValueDictionary so objects can be garbage collected when no longer referenced, preventing memory leaks.

weakref caching memory
Python
import weakref
import gc


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

    def __repr__(self):
        return f"ExpensiveObject('{self.name}')"


class ObjectCache:
    def __init__(self):
        self._cache = weakref.WeakValueDictionary()

    def get_or_create(self, name):
       …
13 0 Open
Testing & modern typing easy

How to Parse Data with Type Hints in Python

A beginner-friendly helper that parses simple dictionary- or list-like strings into typed Python structures using modern typing annotations.

type-hints parsing typing
Python
from typing import Any, Dict, List, Union


def parse_data(raw: str) -> Union[Dict[str, Any], List[Any], str]:
    """Parse a simple string into structured data using type hints."""
    cleaned = raw.strip()
    
    if not cleaned:
        return {}
    
    if cleaned.startswith("{") and cleaned.endswith("}"):
     …
11 0 Open
Testing & modern typing medium

How to Use TypedDict for Data Validation in Python

Define a TypedDict schema and validate raw dictionary input with type hints for safer, more readable data handling.

typeddict typing validation
Python
from typing import Any, Dict, List, Optional, Union, TypedDict, Literal

class Product(TypedDict):
    product_id: int
    name: str
    price: Union[int, float]
    in_stock: bool
    tags: Optional[List[str]]

def validate_product(data: Dict[str, Any]) -> Product:
    product_id: int = int(data["product_id"])
    na…
15 0 Open
System design patterns easy

How to Aggregate Mock API Routes by Method in Python

Groups mock API routes by path and method, collecting response bodies and counts into a nested dictionary structure.

defaultdict api-gateway aggregation
Python
from collections import defaultdict


def aggregate_mock_routes(routes):
    """Aggregate mock API routes by method and aggregate their response bodies."""
    aggregated = defaultdict(lambda: defaultdict(list))

    for route in routes:
        method = route["method"]
        path = route["path"]
        response = …
13 0 Open
System design patterns easy

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.

routing dictionary message-broker
Python
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…
12 0 Open
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()
            …
17 0 Open
API design & gRPC easy

How to Build a Simple Data Helper in Python for API Design

Create a beginner-friendly DataHelper class that demonstrates basic CRUD operations (add, get, list, remove) using an in-memory dictionary, ideal for learning API design concepts.

api-design data-structures crud
Python
class DataHelper:
    """Simple data helper for beginners learning API design concepts."""
    
    def __init__(self):
        self._data = {}
    
    def add_record(self, key, value):
        """Add a record to the store."""
        self._data[key] = value
        return f"Added: {key} -> {value}"
    
    def get_…
12 0 Open
API design & gRPC easy

How to Implement a PATCH Partial Update Merge Dict in Python

Implements a recursive merge function that applies HTTP PATCH-like partial updates to a nested dictionary while preserving untouched fields.

http rest dict-merge
Python
import json

def patch_merge(target: dict, patch: dict) -> dict:
    """Simulate HTTP PATCH semantic: shallow-merge patch into a copy of target."""
    merged = target.copy()
    for key, value in patch.items():
        if isinstance(value, dict) and isinstance(merged.get(key), dict):
            merged[key] = patch_m…
13 0 Open
Caching & Redis medium

How to Implement a Redis-Like Cache Dictionary in Python

Build a RedisMockDict class that mimics basic Redis key-value operations with TTL support, expiry cleanup, and standard dict-like methods.

redis cache ttl
Python
from collections import OrderedDict
import time

class RedisMockDict:
    def __init__(self, ttl=None):
        self._data = OrderedDict()
        self._ttl = ttl  # default TTL in seconds, None = no expiry
        self._expiry = {}

    def set(self, key, value, ttl=None):
        """Set a key-value pair with optiona…
12 0 Open
Reliability & rate limiting medium

How to Implement a Token Bucket Rate Limiter per Client IP in Python

Implements a simple sliding-window rate limiter using a dictionary of timestamp lists per client IP to limit requests per window.

rate-limiting sliding-window ip
Python
from time import time
from collections import defaultdict

class RateLimiter:
    def __init__(self, max_requests: int, window_seconds: int):
        self.max_requests = max_requests
        self.window_seconds = window_seconds
        self.clients = defaultdict(list)

    def allow(self, ip: str) -> bool:
        now…
13 0 Open
Reliability & rate limiting medium

How to implement rate limiting per API key in Python

A simple sliding-window rate limiter that tracks request timestamps per API key and rejects requests exceeding the configured limit.

rate-limiting api time-window
Python
import time

API_RATE_LIMITS = {"api_key_1": 5, "api_key_2": 3}  # max requests per window
WINDOW_SECONDS = 10

class RateLimiter:
    def __init__(self, limits, window):
        self.limits = limits
        self.window = window
        self.requests = {key: [] for key in limits}

    def allow(self, api_key):
       …
13 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
Big data & Spark easy

How to Broadcast a Small Lookup Table in Python

Simulates broadcasting a small lookup table by iterating key-value pairs and emitting packed rows to subscribers with deterministic output.

broadcast lookup-table dictionary
Python
import random

# Generate a deterministic mock broadcast of a small lookup table
# with 5 keys and random integer values (seeded for reproducibility)

data = {
    "sensor_a": 22,
    "sensor_b": 87,
    "sensor_c": 43,
    "sensor_d": 65,
    "sensor_e": 31,
}

# Simulate a broadcast to subscribers by iterating and p…
15 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 easy

How to Mock a Hash Join on Large and Small Tables in Python

This code efficiently joins a large dataset (1000 rows) with a small lookup table (20 rows) by building a dictionary hash lookup, mimicking a hash join strategy used in big data systems.

hash-join dictionaries data-join
Python
import random
from pprint import pprint

# Large table: 1000 rows (id, group_id, value)
large = [{"id": i, "group_id": random.randint(1, 20), "value": random.random() * 100} for i in range(1000)]

# Small table: 20 rows (group_id, label)
small = [{"group_id": g, "label": f"Group-{g}"} for g in range(1, 21)]

# Mock a …
13 0 Open
Big data & Spark easy

How to Pivot and Group Aggregate in Python

Group records by a key, collect values, and apply an aggregate function (like sum) to build a pivot-style summary dictionary.

pivot group-by aggregation
Python
from collections import defaultdict

def pivot_group_aggregate(records, group_key, value_key, agg_func):
    groups = defaultdict(list)
    for record in records:
        groups[record[group_key]].append(record[value_key])
    return {key: agg_func(values) for key, values in groups.items()}

if __name__ == "__main__":…
13 0 Open
ML engineering pipelines easy

How to Build a Data Validation Schema in Python

Create a lightweight validation schema using dataclasses and lambda validators to check fields in a dictionary.

validation dataclasses ml-pipelines
Python
import re
from dataclasses import dataclass, field
from typing import Any, Callable


@dataclass
class Field:
    name: str
    validator: Callable[[Any], bool]
    required: bool = True

    def validate(self, value: Any) -> bool:
        if not self.required and value is None:
            return True
        return …
12 0 Open
ML engineering pipelines easy

How to Load, Save, and Split JSON Data in Python

Provides helper functions to load, save, and split JSON dictionary data for simple ML pipeline preprocessing.

json data-splitting ml-pipeline
Python
import json
from pathlib import Path


def load_json_data(file_path):
    """Load JSON data from a file, returning an empty dict if missing."""
    path = Path(file_path)
    if path.exists():
        with path.open("r", encoding="utf-8") as f:
            return json.load(f)
    return {}


def save_json_data(data, f…
13 0 Open
A/B testing & experimentation easy

How to Define a Mock Primary Metric in Python

Define a mock primary metric object with a name, value, and unit, and serialize it to a dictionary for experimentation and testing.

metrics mock ab-testing
Python
class Metric:
    def __init__(self, name, value, unit=None):
        self.name = name
        self.value = value
        self.unit = unit

    def to_dict(self):
        result = {"name": self.name, "value": self.value}
        if self.unit:
            result["unit"] = self.unit
        return result

    def __repr…
15 0 Open
Database scaling & optimization easy

Build a Partial Index Mock in Python for Database Filtering

Simulate a partial database index by filtering keys with a predicate, then return a limited mock lookup dictionary.

partial-index database mock
Python
data = [
    "alpha", "beta", "gamma", "delta", "epsilon",
    "zeta", "eta", "theta", "iota", "kappa"
]

filtered_keys = [item for item in data if len(item) >= 5]

def mock_partial_index(keys, filter_func, limit=3):
    result = {}
    for key in keys:
        if not filter_func(key):
            continue
        res…
14 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

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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

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.