Python

Modern Python development with type hints, async/await, and best practices.

When to Use

• Working with .py files

• Building APIs with FastAPI/Django

• Data analysis with pandas/numpy

• Scripting and automation

Quick Start

from typing import Optional, List

def process_items( items: list[str], transform: Optional[callable] = None, ) -> list[str]: if transform: return [transform(item) for item in items] return items

Core Concepts

Type Hints

from typing import TypeVar, Generic from collections.abc import Callable, Iterator

def process_items( items: list[str], transform: Callable[[str], str] | None = None, ) -> list[str]: if transform: return [transform(item) for item in items] return items

Use TypeVar for generics

T = TypeVar('T')

def first(items: list[T]) -> T | None: return items[0] if items else None

Dataclasses & Pydantic

from dataclasses import dataclass, field from pydantic import BaseModel, Field

Dataclass for simple data containers

@dataclass class User: name: str email: str tags: list[str] = field(default_factory=list)

Pydantic for validation

class UserCreate(BaseModel): name: str = Field(..., min_length=1, max_length=100) email: str = Field(..., pattern=r'^[\w.-]+@[\w.-]+.\w+$')

Common Patterns

Async Patterns

import asyncio

async def fetch_all(urls: list[str]) -> list[Response]: async with aiohttp.ClientSession() as session: tasks = [fetch_one(session, url) for url in urls] return await asyncio.gather(*tasks)

Use TaskGroup for structured concurrency (3.11+)

async def process_batch(items: list[Item]) -> list[Result]: results = [] async with asyncio.TaskGroup() as tg: for item in items: tg.create_task(process_item(item, results)) return results

Context Managers

from contextlib import contextmanager, asynccontextmanager

@contextmanager def managed_resource() -> Iterator[Resource]: resource = Resource() try: yield resource finally: resource.cleanup()

Best Practices

Do:

• Use type hints for function signatures

• Use pyproject.toml for project configuration

• Use virtual environments (venv , poetry )

• Use generators for large datasets

Don't:

• Use mutable default arguments (def f(x=[] )

• Use import * (pollutes namespace)

• Catch bare except: (catch specific exceptions)

• Use assert for input validation

Troubleshooting

Error Cause Solution

ModuleNotFoundError

Package not installed Run pip install package

IndentationError

Mixed tabs/spaces Use consistent 4-space indentation

TypeError: unhashable type

Using list as dict key Use tuple instead

References

• Python Official Docs

• Real Python