Agent skill
python-mypy
Static type checking with Mypy for Python code quality. Use when writing or reviewing Python code to ensure type safety, catch bugs early, and maintain code quality through proper type annotations and Mypy configuration.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/python-mypy
SKILL.md
Python Mypy Type Checking Skill
This skill automatically activates when writing Python code to ensure proper type annotations and compatibility with Mypy static type checking.
Core Principles
- Type Safety: Catch type errors before runtime
- Gradual Typing: Start with critical paths, expand coverage over time
- Strict Mode: Enable strict checks for new code
- CI Integration: Run Mypy in continuous integration
Type Annotation Patterns
Function Signatures
from typing import Optional
from collections.abc import Sequence
# Good: Complete type hints
def process_items(
items: list[str],
max_count: int | None = None,
debug: bool = False,
) -> dict[str, int]:
"""Process items and return counts."""
result: dict[str, int] = {}
# Implementation
return result
# Good: Generic types with TypeVar
from typing import TypeVar
T = TypeVar('T')
def first(items: Sequence[T]) -> T | None:
"""Get first item from sequence."""
return items[0] if items else None
Class Type Hints
from typing import ClassVar
from dataclasses import dataclass
@dataclass
class User:
"""User model with type hints."""
id: int
name: str
email: str | None = None
active: bool = True
# Class variable
_registry: ClassVar[dict[int, 'User']] = {}
def __post_init__(self) -> None:
"""Register user after initialization."""
self._registry[self.id] = self
Protocol for Structural Typing
from typing import Protocol
class Drawable(Protocol):
"""Protocol for drawable objects."""
def draw(self) -> str:
"""Draw the object."""
...
def render(obj: Drawable) -> None:
"""Render any drawable object."""
print(obj.draw())
# Any class with draw() method satisfies this
class Circle:
def draw(self) -> str:
return "○"
render(Circle()) # OK with Mypy
TypedDict for Structured Dictionaries
from typing import TypedDict, NotRequired
class UserDict(TypedDict):
"""Structured user dictionary."""
id: int
name: str
email: NotRequired[str] # Optional key (Python 3.11+)
def create_user(data: UserDict) -> None:
"""Create user from typed dictionary."""
user_id: int = data["id"] # Type-safe access
# Mypy knows 'email' might not exist
Mypy Configuration Best Practices
Recommended mypy.ini
[mypy]
python_version = 3.11
warn_return_any = True
warn_unused_configs = True
disallow_untyped_defs = True
disallow_any_generics = True
disallow_subclassing_any = True
disallow_untyped_calls = True
disallow_incomplete_defs = True
check_untyped_defs = True
no_implicit_optional = True
warn_redundant_casts = True
warn_unused_ignores = True
warn_no_return = True
warn_unreachable = True
strict_equality = True
show_error_codes = True
show_column_numbers = True
# Start strict, relax per-module if needed
[mypy-tests.*]
disallow_untyped_defs = False
[mypy-migrations.*]
ignore_errors = True
# Third-party without stubs
[mypy-some_library.*]
ignore_missing_imports = True
pyproject.toml Configuration
[tool.mypy]
python_version = "3.11"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
show_error_codes = true
[[tool.mypy.overrides]]
module = "tests.*"
disallow_untyped_defs = false
[[tool.mypy.overrides]]
module = "migrations.*"
ignore_errors = true
Common Mypy Checks
Strict Optional Checking
# Bad: Implicit Optional
def find_user(id: int) -> User: # Mypy error if can return None
return users.get(id) # dict.get returns User | None
# Good: Explicit Optional
def find_user(id: int) -> User | None:
return users.get(id)
# Good: Narrow type with assertion
def get_user(id: int) -> User:
user = users.get(id)
assert user is not None, f"User {id} not found"
return user # Mypy knows this is User, not None
Type Narrowing
def process(value: str | int) -> str:
"""Process value based on type."""
if isinstance(value, str):
# Mypy knows value is str here
return value.upper()
else:
# Mypy knows value is int here
return str(value * 2)
Generics
from typing import Generic, TypeVar
T = TypeVar('T')
class Stack(Generic[T]):
"""Type-safe stack."""
def __init__(self) -> None:
self._items: list[T] = []
def push(self, item: T) -> None:
self._items.append(item)
def pop(self) -> T:
return self._items.pop()
# Usage
int_stack: Stack[int] = Stack()
int_stack.push(1) # OK
int_stack.push("x") # Mypy error!
Type Checking Strategies
Gradual Adoption
- Start with New Code: Use strict mode for new modules
- Core Paths First: Type-check critical business logic
- Expand Coverage: Gradually increase
disallow_untyped_defs - Per-Module Configuration: Use mypy overrides for legacy code
[mypy]
# Strict by default
disallow_untyped_defs = True
# Relax for legacy
[mypy-legacy.*]
disallow_untyped_defs = False
check_untyped_defs = True # Still check what we can
Type Ignores (Use Sparingly)
# When third-party library lacks types
import untyped_library # type: ignore[import-untyped]
# When dealing with dynamic code (rare)
def dynamic_call() -> Any:
result = getattr(obj, method_name)() # type: ignore[misc]
return result
Common Patterns
Context Managers
from typing import Generator
from contextlib import contextmanager
@contextmanager
def database_transaction() -> Generator[Connection, None, None]:
"""Type-safe context manager."""
conn = get_connection()
try:
yield conn
conn.commit()
except Exception:
conn.rollback()
raise
finally:
conn.close()
Callable Types
from collections.abc import Callable
def retry(
func: Callable[[int], str],
times: int = 3,
) -> str:
"""Retry a function that takes int and returns str."""
for _ in range(times):
try:
return func(42)
except Exception:
continue
raise RuntimeError("All retries failed")
Overloads for Multiple Signatures
from typing import overload
@overload
def parse(data: str) -> dict[str, str]: ...
@overload
def parse(data: bytes) -> dict[str, bytes]: ...
def parse(data: str | bytes) -> dict[str, str] | dict[str, bytes]:
"""Parse data with type-specific return."""
if isinstance(data, str):
return {"parsed": data}
return {"parsed": data}
Django Integration
Model Type Hints
from django.db import models
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from django.db.models.manager import RelatedManager
class Author(models.Model):
name = models.CharField(max_length=100)
if TYPE_CHECKING:
books: RelatedManager['Book']
class Book(models.Model):
title = models.CharField(max_length=200)
author: models.ForeignKey[Author] = models.ForeignKey(
Author,
on_delete=models.CASCADE,
related_name='books',
)
Django Mypy Plugin
[mypy]
plugins = mypy_django_plugin.main
[mypy.plugins.django-stubs]
django_settings_module = "myproject.settings"
Running Mypy
Basic Check
# Check all files
mypy .
# Check specific files/directories
mypy src/
# Show error codes
mypy --show-error-codes .
# Generate HTML report
mypy --html-report ./mypy-report .
In CI/CD
# .github/workflows/type-check.yml
- name: Type check with Mypy
run: |
pip install mypy
mypy --strict src/
Anti-Patterns to Avoid
Don't Use Any Unnecessarily
# Bad: Any hides all type errors
def process(data: Any) -> Any:
return data.unknown_method() # No error!
# Good: Use specific types
def process(data: dict[str, int]) -> list[int]:
return list(data.values())
Don't Ignore All Errors
# Bad: Blanket ignore
x = dangerous_call() # type: ignore
# Good: Specific ignore with reason
x = legacy_api_call() # type: ignore[misc] # TODO: Add types to legacy API
Don't Mix str and bytes
# Bad: Mypy will catch this
def process(data: str) -> None:
encoded: bytes = data # Error!
# Good: Explicit conversion
def process(data: str) -> None:
encoded: bytes = data.encode('utf-8')
Coverage Reporting
# Check type coverage
mypy --html-report ./coverage .
# Show coverage stats
mypy --any-exprs-report ./coverage .
Integration with Other Tools
- Pre-commit: Run Mypy before commits
- VS Code: Use Pylance with type checking mode
- Ruff: Complement Mypy with Ruff for runtime checks
Related Skills
| Skill | Purpose |
|---|---|
python-experts:python-style |
Python coding standards |
python-experts:python-code-review |
Code review guidelines |
python-experts:python-testing-expert |
Testing patterns |
References
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