skills / wshobson / agents / python-type-safety 
python-type-safety 
$ npx skills add https://github.com/wshobson/agents --skill python-type-safety SKILL.md 
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 

def get_user ( user_id : str ) - > User | None : """Return type makes 'might not exist' explicit.""" . . . # Type checker enforces handling None case user = 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. 

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. 

# 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. 

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. 

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 types def 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 
Advanced Patterns 
Pattern 5: Generic Repository 
Create type-safe data access patterns. 

from typing import TypeVar , Generic from abc import ABC , abstractmethod T = TypeVar ( "T" ) ID = TypeVar ( "ID" ) class Repository ( ABC , Generic [ T , ID ] ) : """Generic repository interface.""" @abstractmethod async def get ( self , id : ID ) - > T | None : """Get entity by ID.""" . . . @abstractmethod async def save ( self , entity : T ) - > T : """Save and return entity.""" . . . @abstractmethod async def delete ( self , id : ID ) - > bool : """Delete entity, return True if existed.""" . . . class UserRepository ( Repository [ User , str ] ) : """Concrete repository for Users with string IDs.""" async def get ( self , id : str ) - > User | None : row = await self . _db . fetchrow ( "SELECT * FROM users WHERE id = $1" , id ) return User ( ** row ) if row else None async def save ( self , entity : User ) - > User : . . . async def delete ( self , id : str ) - > bool : . . . 
Pattern 6: TypeVar with Bounds 
Restrict generic parameters to specific types. 

from typing import TypeVar from pydantic import BaseModel ModelT = TypeVar ( "ModelT" , bound = BaseModel ) def validate_and_create ( model_cls : type [ ModelT ] , data : dict ) - > ModelT : """Create a validated Pydantic model from dict.""" return model_cls . model_validate ( data ) # Works with any BaseModel subclass class User ( BaseModel ) : name : str email : str user = validate_and_create ( User , { "name" : "Alice" , "email" : "a@b.com" } ) # user is typed as User # Type error: str is not a BaseModel subclass result = validate_and_create ( str , { "name" : "Alice" } ) # Error! 
Pattern 7: Protocols for Structural Typing 
Define interfaces without requiring inheritance. 

from typing import Protocol , runtime_checkable @runtime_checkable class Serializable ( Protocol ) : """Any class that can be serialized to/from dict.""" def to_dict ( self ) - > dict : . . . @classmethod def from_dict ( cls , data : dict ) - > "Serializable" : . . . # User satisfies Serializable without inheriting from it class User : def __init__ ( self , id : str , name : str ) - > None : self . id = id self . name = name def to_dict ( self ) - > dict : return { "id" : self . id , "name" : self . name } @classmethod def from_dict ( cls , data : dict ) - > "User" : return cls ( id = data [ "id" ] , name = data [ "name" ] ) def serialize ( obj : Serializable ) - > str : """Works with any Serializable object.""" return json . dumps ( obj . to_dict ( ) ) # Works - User matches the protocol serialize ( User ( "1" , "Alice" ) ) # Runtime checking with @runtime_checkable isinstance ( User ( "1" , "Alice" ) , Serializable ) # True 
Pattern 8: Common Protocol Patterns 
Define reusable structural interfaces. 

from typing import Protocol class Closeable ( Protocol ) : """Resource that can be closed.""" def close ( self ) - > None : . . . class AsyncCloseable ( Protocol ) : """Async resource that can be closed.""" async def close ( self ) - > None : . . . class Readable ( Protocol ) : """Object that can be read from.""" def read ( self , n : int = - 1 ) - > bytes : . . . class HasId ( Protocol ) : """Object with an ID property.""" @property def id ( self ) - > str : . . . class Comparable ( Protocol ) : """Object that supports comparison.""" def __lt__ ( self , other : "Comparable" ) - > bool : . . . def __le__ ( self , other : "Comparable" ) - > bool : . . . 
Pattern 9: Type Aliases 
Create meaningful type names. 
Note: The 
type statement was introduced in Python 3.10 for simple aliases. Generic type statements require Python 3.12+. 

# Python 3.10+ type statement for simple aliases type UserId = str type UserDict = dict [ str , Any ] # Python 3.12+ type statement with generics type Handler [ T ] = Callable [ [ Request ] , T ] type AsyncHandler [ T ] = Callable [ [ Request ] , Awaitable [ T ] ] # Python 3.9-3.11 style (needed for broader compatibility) from typing import TypeAlias from collections . abc import Callable , Awaitable UserId : TypeAlias = str Handler : TypeAlias = Callable [ [ Request ] , Response ] # Usage def register_handler ( path : str , handler : Handler [ Response ] ) - > None : . . . 
Pattern 10: Callable Types 
Type function parameters and callbacks. 

from collections . abc import Callable , Awaitable # Sync callback ProgressCallback = Callable [ [ int , int ] , None ] # (current, total) # Async callback AsyncHandler = Callable [ [ Request ] , Awaitable [ Response ] ] # With named parameters (using Protocol) class OnProgress ( Protocol ) : def __call__ ( self , current : int , total : int , * , message : str = "" , ) - > None : . . . def process_items ( items : list [ Item ] , on_progress : ProgressCallback | None = None , ) - > list [ Result ] : for i , item in enumerate ( items ) : if on_progress : on_progress ( i , len ( items ) ) . . . 
Configuration 
Strict Mode Checklist 
For 
mypy --strict compliance: 

# pyproject.toml [ tool.mypy ] python_version = "3.12" strict = true warn_return_any = true warn_unused_ignores = true disallow_untyped_defs = true disallow_incomplete_defs = true no_implicit_optional = true 
Incremental adoption goals: 
All function parameters annotated 
All return types annotated 
Class attributes annotated 
Minimize 
Any usage (acceptable for truly dynamic data) 
Generic collections use type parameters ( 
list[str] not 
list ) 
For existing codebases, enable strict mode per-module using 
# mypy: strict or configure per-module overrides in 
pyproject.toml . 
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 Weekly Installs 1.2K Repository wshobson/agents First Seen Jan 30, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass Installed on claude-code 868 opencode 803 gemini-cli 765 codex 724 cursor 585 github-copilot 575