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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Parse an AWS API Gateway Proxy Event in Python
Extract and parse common fields from a mock API Gateway proxy event, turning the JSON body into a native Python dict.
import json
from typing import Any, Dict, Optional
def parse_proxy_event(event: Dict[str, Any]) -> Dict[str, Any]:
"""Extract and parse common fields from an API Gateway proxy event."""
body = event.get("body", "")
if isinstance(body, str):
body = json.loads(body) if body else {}
elif body is…
How to Validate Data Fields and Types in Python
Validate required fields and type correctness in a Python dictionary with small helper functions, returning a list of clear error messages.
import json
from typing import Any, Dict, List
def validate_data(data: Dict[str, Any], required_fields: List[str]) -> List[str]:
"""Check required fields exist and are non-empty. Return list of errors."""
errors = []
for field in required_fields:
value = data.get(field)
if value is None o…
How to mock boto3 S3 upload in Python
Shows how to mock the boto3 S3 client with unit tests and wrap an upload function to return a dictionary with status details.
import boto3
from unittest.mock import Mock, patch
class S3Uploader:
def __init__(self, bucket_name):
self.bucket_name = bucket_name
self.s3 = boto3.client("s3", region_name="us-east-1")
def upload_file(self, local_path, s3_key):
self.s3.upload_file(local_path, self.bucket_name, s3_ke…
How to plan reserved capacity from a CSV in Python
Read a CSV of workloads with csv.DictReader and compute a mock reserved capacity plan with headroom per service.
import csv
import io
def plan_reserved_capacity(workloads_csv: str) -> list[dict]:
"""Read a CSV of workloads and return a plan for reserved capacity per service."""
reader = csv.DictReader(io.StringIO(workloads_csv))
plan = []
for row in reader:
service = row["service"]
avg_load = fl…
Mock ECS Task Run Stop Status Dict in Python
Build a mock ECS task status dictionary with RUNNING/STOPPED states using the standard library.
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…
Mock Lambda handler event context dict in Python
Simulates an AWS Lambda invocation by passing a mock event dict and context object to a handler, then prints the response.
import json
def lambda_handler(event, context):
"""
A mock AWS Lambda handler that processes an event dict and context object.
Demonstrates the typical Lambda function signature and basic event/context usage.
"""
print("Received event:", json.dumps(event, indent=2))
print("Function name:", co…
Mock SNS publish subscribe fanout in Python
Simulates AWS SNS publish/subscribe with an in-memory topic-to-endpoints dict that fans out messages to all subscribers.
class SNSMock:
def __init__(self):
self.topics = {}
def create_topic(self, name):
if name not in self.topics:
self.topics[name] = []
return f"arn:aws:sns:us-east-1:123456789012:{name}"
def subscribe(self, topic_name, endpoint):
self.topics.setdefault(topic_name…
How to Generate a Mock devcontainer.json Config in Python
Build a reproducible devcontainer.json file with Python, composing name, image, extensions, forwarded ports, and a post-create command as a dict.
import json
from pathlib import Path
def create_devcontainer_config(
image: str = "mcr.microsoft.com/devcontainers/python:3.11",
name: str = "python-dev-container",
ports: list[int] | None = None,
post_create: str | None = None,
) -> dict:
config = {
"name": name,
"image": image,
…
How to Load and Inspect CSV Data with a Dataclass Helper in Python
This code defines a DataHelper dataclass that reads a CSV file into a list of dictionaries and prints basic dataset information.
from pathlib import Path
from dataclasses import dataclass
from typing import Any
@dataclass
class DataHelper:
"""Simple helper for loading and inspecting CSV data."""
filepath: Path
def load_csv(self, *, delimiter: str = ",") -> list[dict[str, Any]]:
"""Read CSV into a list of dictionaries."""
…
How to Save and Load JSON Files in Python
Create a simple data helper to save Python dictionaries as pretty-printed JSON files and load them back reliably using pathlib and the stdlib json module.
import json
from pathlib import Path
from typing import Any
def save_json(data: Any, filename: str) -> None:
"""Save data as pretty-printed JSON to the current directory."""
path = Path(filename)
with path.open("w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
def lo…
How to Type Check a Mock with pyright in Python
Shows how pyright validates a mock function against a TypedDict and Callable signature before runtime.
from typing import TypedDict, Callable
class User(TypedDict):
id: int
name: str
def get_user_name(user_id: int, get_user: Callable[[int], User]) -> str:
user = get_user(user_id)
return user["name"]
def mock_get_user(user_id: int) -> User:
return {"id": user_id, "name": f"User {user_id}"}
if…
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.
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…
How to Reduce Instance Memory with __slots__ in Python
Demonstrates that classes with __slots__ use less memory per instance than regular classes because they skip the instance __dict__.
class SlottedPoint:
__slots__ = ('x', 'y', 'z')
def __init__(self, x, y, z):
self.x = x
self.y = y
self.z = z
class RegularPoint:
def __init__(self, x, y, z):
self.x = x
self.y = y
self.z = z
if __name__ == "__main__":
regular = RegularPoint(1, 2, 3)…
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.
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()
…
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.
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):
…
Design Data Helpers with Python TypedDict and Literal
Use TypedDict, Literal, and Union to define typed data shapes and parse values in Python.
from typing import TypedDict, Literal, Optional, Union, List
class User(TypedDict):
name: str
age: int
role: Literal["admin", "user", "guest"]
def describeUser(data: User) -> str:
return f"{data['name']} ({data['age']}) — {data['role']}"
def parse_value(item: Union[int, str, None]) -> str:
if it…
Format Data with Type Hints in Python
Build a validated person dict with modern type hints and optional list handling.
from typing import Any, Dict, List, Optional, Union
JsonValue = Union[str, int, float, bool, None, List["JsonValue"], Dict[str, "JsonValue"]]
def format_person(name: str, age: int, hobbies: Optional[List[str]] = None) -> Dict[str, Any]:
"""Build a person dict with validated typing."""
if not name or age < 0:…
How to Group Data by Key in Python with Type Hints
Group a list of dictionaries by a specified key using a typed helper function and print a summary of each group.
from typing import Any, Dict, List, TypeVar, Union
T = TypeVar("T")
def group_by(data: List[Dict[str, Any]], key: str) -> Dict[Any, List[Dict[str, Any]]]:
"""Group a list of dictionaries by a given key."""
grouped: Dict[Any, List[Dict[str, Any]]] = {}
for item in data:
value = item.get(key)
…
How to Merge TypedDicts in Python
Merge two TypedDict dictionaries with type-aware logic using NotRequired, **kwargs unpacking, and safe key updates.
from typing import TypedDict, NotRequired, merge # hypothetical
class User(TypedDict):
name: str
email: NotRequired[str]
age: NotRequired[int]
def merge_users(base: User, **overrides: User) -> User:
"""Merge two user dicts with typing-aware logic."""
result: User = dict(base)
for key, value …
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.
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("}"):
…
How to Use Python Type Hints for Beginners
Build a data helper module with basic type hints — Union, Optional, List, Dict, Any, and TypeVar — to make your code clearer and safer.
from typing import Any, Union, Optional, List, Dict, Tuple, Callable, TypeVar
T = TypeVar("T")
def describe(value: Any) -> str:
"""Return a human-readable description of the value's type."""
if isinstance(value, list):
return f"list of {len(value)} items"
elif isinstance(value, dict):
ret…
How to Use TypedDict and Dataclasses in Python
Create typed data structures with TypedDict and dataclasses, then use them as helper functions for describing objects in a type-safe way.
from typing import TypedDict, NotRequired, Optional
from dataclasses import dataclass
class User(TypedDict):
name: str
age: NotRequired[int]
email: Optional[str]
@dataclass
class Product:
id: int
title: str
price: float = 0.0
def describe_user(user: User) -> str:
age = user.get("age",…
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.
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…
How to Use TypedDict for Structured Dict Typing in Python
Define and use TypedDict to add type hints to dictionaries, improving code clarity and enabling static type checking in your Python projects.
from typing import TypedDict
class User(TypedDict):
name: str
age: int
email: str
def greet(user: User) -> str:
return f"Hello {user['name']}, age {user['age']}, contact {user['email']}"
if __name__ == "__main__":
alice: User = {"name": "Alice", "age": 30, "email": "alice@example.com"}
pr…
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