Python Mypy

Python mypy — Static Type Checking

Mypy is an optional static type checker for Python that catches type errors at development time without runtime overhead. It combines the expressive power of Python with a powerful type system based on PEP 484, enabling gradual migration from dynamic to static typing.

Installation

pip install mypy

# Install type stubs for common third-party libraries
pip install types-requests types-PyYAML types-boto3

# Run mypy
mypy src/
mypy --strict src/

Core Annotation Patterns

Functions

Annotate all function signatures — return type and all parameters:

from collections.abc import Iterable, Sequence

def process(items: list[str], limit: int = 10) -> list[str]:
    return items[:limit]

# Use abstract types for parameters (accept more, restrict less)
def summarize(records: Iterable[dict[str, str]]) -> str:
    return ", ".join(r["name"] for r in records)

# None return type for procedures
def log_event(event: str, level: str = "INFO") -> None:
    print(f"[{level}] {event}")

Optional and Union

# Python 3.10+ syntax (preferred)
def find_user(user_id: int) -> str | None:
    ...

# Python 3.9 and earlier
from typing import Optional, Union
def find_user(user_id: int) -> Optional[str]:
    ...

# Union for multiple possible types
def normalize_id(user_id: int | str) -> str:
    if isinstance(user_id, int):
        return f"user-{user_id}"
    return user_id

Classes

from typing import ClassVar

class Repository:
    default_limit: ClassVar[int] = 100

    def __init__(self, name: str, url: str) -> None:
        self.name = name
        self.url = url
        self._cache: dict[str, list[str]] = {}

    def fetch(self, query: str) -> list[str]:
        return self._cache.get(query, [])

TypedDict for Structured Dicts

Use TypedDict instead of dict[str, Any] for known-structure dictionaries:

from typing import TypedDict

class UserRecord(TypedDict):
    id: int
    name: str
    email: str

class PartialUser(TypedDict, total=False):
    nickname: str
    avatar_url: str

def create_user(data: UserRecord) -> None:
    print(data["name"])  # mypy knows this is str

Protocols for Duck Typing

Prefer Protocol over concrete base classes for flexible interfaces:

from typing import Protocol

class Closeable(Protocol):
    def close(self) -> None: ...

class Readable(Protocol):
    def read(self, n: int = -1) -> bytes: ...

def process_stream(stream: Readable) -> bytes:
    return stream.read()

Strictness Levels

Adopt strictness incrementally. Start permissive, tighten over time.

Recommended Progression

Level 1 — New project baseline (pyproject.toml):

[tool.mypy]
python_version = "3.12"
warn_return_any = true
warn_unused_configs = true
warn_unused_ignores = true

Level 2 — Growing codebase:

[tool.mypy]
python_version = "3.12"
warn_return_any = true
warn_unused_configs = true
warn_unused_ignores = true
disallow_incomplete_defs = true
check_untyped_defs = true

Level 3 — Strict (production-ready):

[tool.mypy]
python_version = "3.12"
strict = true
warn_unused_ignores = true

strict enables: disallow_untyped_defs, disallow_any_generics, warn_return_any, no_implicit_reexport, strict_equality, and more.

Handling Third-Party Libraries

Install Type Stubs

# Check if stubs are available
mypy --install-types

# Install specific stubs
pip install types-requests types-PyYAML types-redis

Suppress Missing Stubs Per Module

Avoid global ignore_missing_imports. Scope it to specific libraries:

# pyproject.toml — preferred approach
[[tool.mypy.overrides]]
module = ["boto3.*", "botocore.*", "some_untyped_lib"]
ignore_missing_imports = true

Inline Suppression (Use Sparingly)

import untyped_lib  # type: ignore[import-untyped]

result = complex_dynamic_call()  # type: ignore[no-any-return]  # reason: third-party returns Any

Always add a comment explaining why the suppression is necessary.

Common Use Cases

Migrating an Existing Codebase

Start with zero annotations and progressively type the codebase:

1. Run mypy --ignore-missing-imports src/ — establish a zero-error baseline.
2. Enable check_untyped_defs = true to catch bugs inside unannotated functions.
3. Add annotations to public API functions first (highest value).
4. Enable disallow_incomplete_defs to prevent partially-annotated functions.
5. Gradually enable disallow_untyped_defs per package via [[tool.mypy.overrides]].
6. Reach strict = true as the final goal.

# Migrate package-by-package
[[tool.mypy.overrides]]
module = "myapp.core.*"
disallow_untyped_defs = true

[[tool.mypy.overrides]]
module = "myapp.legacy.*"
ignore_errors = true  # deal with later

FastAPI / Pydantic Integration

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    price: float
    tags: list[str] = []

# FastAPI + mypy works seamlessly — Pydantic models are fully typed
from fastapi import FastAPI
app = FastAPI()

@app.get("/items/{item_id}")
async def get_item(item_id: int) -> Item:
    return Item(name="Widget", price=9.99)

SQLAlchemy with mypy Plugin

[tool.mypy]
plugins = ["sqlalchemy.ext.mypy.plugin"]

from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "users"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str]
    email: Mapped[str | None]

Type Narrowing

Mypy understands isinstance, assert, and guard patterns:

def render(value: str | int | None) -> str:
    if value is None:
        return ""
    if isinstance(value, int):
        return str(value)
    return value.upper()  # mypy knows: value is str here

Use reveal_type() during development to inspect inferred types:

x = [1, 2, 3]
reveal_type(x)  # Revealed type is "builtins.list[builtins.int]"

CI Integration

Pre-commit Hook

# .pre-commit-config.yaml
repos:
  - repo: https://github.com/pre-commit/mirrors-mypy
    rev: v1.9.0
    hooks:
      - id: mypy
        additional_dependencies:
          - types-requests
          - pydantic

GitHub Actions

- name: Run mypy
  run: mypy src/ --config-file pyproject.toml

Quick Reference

Additional Resources

For complete configuration options and advanced patterns:

• references/configuration-guide.md — Complete pyproject.toml templates and per-module override patterns
• references/type-patterns.md — Generics, Protocols, TypeVar, ParamSpec, overloads, and advanced patterns
• examples/pyproject.toml — Ready-to-use configuration for new and migrating projects