Python Type Safety

作者 wshobson46891e7e60da無授權條款收錄於 2026年10月8日更新於 2026年10月8日

Python type safety with type hints, generics, protocols, and strict type checking. Use when adding type annotations, implementing generic classes, defining structural interfaces, or configuring mypy/pyright.

僅含說明Software Development

AI 產生的概覽

指導 Python 型別註解、泛型、協定以及 mypy/pyright 嚴格型別檢查。

功能: 此技能提供使用 Python 型別系統的指引，涵蓋型別註解、泛型、協定與型別收窄。它說明為公開簽章加上註解、使用現代聯集型別語法、撰寫泛型類別，以及設定 mypy 或 pyright 嚴格檢查等模式。產出的是程式碼範例與建議，本身不會執行任何工具。
適用情境: 適用於為現有 Python 程式碼加上型別提示、建立泛型或可重複使用的類別、以協定定義結構化介面，或設定 mypy/pyright 嚴格檢查時。也適合在理解型別收窄與型別守衛，或建構型別安全的 API 與函式庫時使用。
執行需求: 不需要指令碼或執行階段相依項目，僅為說明性內容。套用這些指引需要 Python 專案，並可選用 mypy 或 pyright 進行嚴格檢查。

Python Type Safety

Leverage Python's type system to catch errors at static analysis time. Type annotations serve as enforced documentation that tooling validates automatically.

When to Use This Skill

Adding type hints to existing code
Creating generic, reusable classes
Defining structural interfaces with protocols
Configuring mypy or pyright for strict checking
Understanding type narrowing and guards
Building type-safe APIs and libraries

Core Concepts

1. Type Annotations

Declare expected types for function parameters, return values, and variables.

2. Generics

Write reusable code that preserves type information across different types.

3. Protocols

Define structural interfaces without inheritance (duck typing with type safety).

4. Type Narrowing

Use guards and conditionals to narrow types within code blocks.

Quick Start

python

def get_user(user_id: str) -> User | None:    """Return type makes 'might not exist' explicit."""    ...
# Type checker enforces handling None caseuser = get_user("123")if user is None:    raise UserNotFoundError("123")print(user.name)  # Type checker knows user is User here

def get_user(user_id: str) -> User | None:    """Return type makes 'might not exist' explicit."""    ...
# Type checker enforces handling None caseuser = get_user("123")if user is None:    raise UserNotFoundError("123")print(user.name)  # Type checker knows user is User here

Fundamental Patterns

Pattern 1: Annotate All Public Signatures

Every public function, method, and class should have type annotations.

python

def get_user(user_id: str) -> User:    """Retrieve user by ID."""    ...
def process_batch(    items: list[Item],    max_workers: int = 4,) -> BatchResult[ProcessedItem]:    """Process items concurrently."""    ...
class UserRepository:    def __init__(self, db: Database) -> None:        self._db = db
    async def find_by_id(self, user_id: str) -> User | None:        """Return User if found, None otherwise."""        ...
    async def find_by_email(self, email: str) -> User | None:        ...
    async def save(self, user: User) -> User:        """Save and return user with generated ID."""        ...

def get_user(user_id: str) -> User:    """Retrieve user by ID."""    ...
def process_batch(    items: list[Item],    max_workers: int = 4,) -> BatchResult[ProcessedItem]:    """Process items concurrently."""    ...
class UserRepository:    def __init__(self, db: Database) -> None:        self._db = db
    async def find_by_id(self, user_id: str) -> User | None:        """Return User if found, None otherwise."""        ...
    async def find_by_email(self, email: str) -> User | None:        ...
    async def save(self, user: User) -> User:        """Save and return user with generated ID."""        ...

Use mypy --strict or pyright in CI to catch type errors early. For existing projects, enable strict mode incrementally using per-module overrides.

Pattern 2: Use Modern Union Syntax

Python 3.10+ provides cleaner union syntax.

python

# Preferred (3.10+)def find_user(user_id: str) -> User | None:    ...
def parse_value(v: str) -> int | float | str:    ...
# Older style (still valid, needed for 3.9)from typing import Optional, Union
def find_user(user_id: str) -> Optional[User]:    ...

# Preferred (3.10+)def find_user(user_id: str) -> User | None:    ...
def parse_value(v: str) -> int | float | str:    ...
# Older style (still valid, needed for 3.9)from typing import Optional, Union
def find_user(user_id: str) -> Optional[User]:    ...

Pattern 3: Type Narrowing with Guards

Use conditionals to narrow types for the type checker.

python

def process_user(user_id: str) -> UserData:    user = find_user(user_id)
    if user is None:        raise UserNotFoundError(f"User {user_id} not found")
    # Type checker knows user is User here, not User | None    return UserData(        name=user.name,        email=user.email,    )
def process_items(items: list[Item | None]) -> list[ProcessedItem]:    # Filter and narrow types    valid_items = [item for item in items if item is not None]    # valid_items is now list[Item]    return [process(item) for item in valid_items]

def process_user(user_id: str) -> UserData:    user = find_user(user_id)
    if user is None:        raise UserNotFoundError(f"User {user_id} not found")
    # Type checker knows user is User here, not User | None    return UserData(        name=user.name,        email=user.email,    )
def process_items(items: list[Item | None]) -> list[ProcessedItem]:    # Filter and narrow types    valid_items = [item for item in items if item is not None]    # valid_items is now list[Item]    return [process(item) for item in valid_items]

Pattern 4: Generic Classes

Create type-safe reusable containers.

python

from typing import TypeVar, Generic
T = TypeVar("T")E = TypeVar("E", bound=Exception)
class Result(Generic[T, E]):    """Represents either a success value or an error."""
    def __init__(        self,        value: T | None = None,        error: E | None = None,    ) -> None:        if (value is None) == (error is None):            raise ValueError("Exactly one of value or error must be set")        self._value = value        self._error = error
    @property    def is_success(self) -> bool:        return self._error is None
    @property    def is_failure(self) -> bool:        return self._error is not None
    def unwrap(self) -> T:        """Get value or raise the error."""        if self._error is not None:            raise self._error        return self._value  # type: ignore[return-value]
    def unwrap_or(self, default: T) -> T:        """Get value or return default."""        if self._error is not None:            return default        return self._value  # type: ignore[return-value]
# Usage preserves typesdef parse_config(path: str) -> Result[Config, ConfigError]:    try:        return Result(value=Config.from_file(path))    except ConfigError as e:        return Result(error=e)
result = parse_config("config.yaml")if result.is_success:    config = result.unwrap()  # Type: Config

from typing import TypeVar, Generic
T = TypeVar("T")E = TypeVar("E", bound=Exception)
class Result(Generic[T, E]):    """Represents either a success value or an error."""
    def __init__(        self,        value: T | None = None,        error: E | None = None,    ) -> None:        if (value is None) == (error is None):            raise ValueError("Exactly one of value or error must be set")        self._value = value        self._error = error
    @property    def is_success(self) -> bool:        return self._error is None
    @property    def is_failure(self) -> bool:        return self._error is not None
    def unwrap(self) -> T:        """Get value or raise the error."""        if self._error is not None:            raise self._error        return self._value  # type: ignore[return-value]
    def unwrap_or(self, default: T) -> T:        """Get value or return default."""        if self._error is not None:            return default        return self._value  # type: ignore[return-value]
# Usage preserves typesdef parse_config(path: str) -> Result[Config, ConfigError]:    try:        return Result(value=Config.from_file(path))    except ConfigError as e:        return Result(error=e)
result = parse_config("config.yaml")if result.is_success:    config = result.unwrap()  # Type: Config

Detailed worked examples and patterns

Detailed sections (starting with ## Advanced Patterns) live in references/details.md. Read that file when the navigation summary above is insufficient.

Best Practices Summary

Annotate all public APIs - Functions, methods, class attributes
Use T | None - Modern union syntax over Optional[T]
Run strict type checking - mypy --strict in CI
Use generics - Preserve type info in reusable code
Define protocols - Structural typing for interfaces
Narrow types - Use guards to help the type checker
Bound type vars - Restrict generics to meaningful types
Create type aliases - Meaningful names for complex types
Minimize Any - Use specific types or generics. Any is acceptable for truly dynamic data or when interfacing with untyped third-party code
Document with types - Types are enforceable documentation

來源與署名

來源：wshobson/agents位於plugins/python-development/skills/python-type-safety提交46891e7

授權條款：無授權條款

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架

Python Type Safety

Python Type Safety

When to Use This Skill

Core Concepts

1. Type Annotations

2. Generics

3. Protocols

4. Type Narrowing

Quick Start

Fundamental Patterns

Pattern 1: Annotate All Public Signatures

Pattern 2: Use Modern Union Syntax

Pattern 3: Type Narrowing with Guards

Pattern 4: Generic Classes

Detailed worked examples and patterns

Best Practices Summary

來源與署名

更多來自 wshobson/agents 的技能

Uv Package Manager

Web Component Design

Visual Design Foundations

Responsive Design

Python Resource Management

React Native Design

更多Software Development技能

Playground

M5 Onboard

Cardputer Buddy

Dpop Adoption

Gemini Live Api

Gemini Api