Back to skills
SKILL.md
Typing Patterns
ASecurityPython type annotation patterns without `type: ignore`. Always the correct solution.
- 4 stars
- 0 votes
- 0 copies
- 2 views
- Added May 26, 2026
Security analysis
100/100Pro scans all 4 files and shows the line behind each finding
npx -y skills add ruslan-korneev/claude-plugins --skill typing-patterns --agent claude-codeAre you the author of Typing Patterns?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/ruslan-korneev-typing-patterns)# Python Typing Patterns
Python type annotation patterns without `type: ignore`. Always the correct solution.
## Triggers
Use this skill when the user:
- Gets mypy/pyright errors
- Asks about Python type annotations
- Wants to add type hints
- Works with generics, protocols, TypeVar
## Main Principle: NEVER type: ignore
Every type error has a correct solution. `type: ignore` is:
- Masking potential bugs
- Disabling type checking
- Technical debt
More details: `${CLAUDE_PLUGIN_ROOT}/skills/typing-patterns/references/why-no-type-ignore.md`
## Dictionary Typing — TypedDict Instead of dict
More details: `${CLAUDE_PLUGIN_ROOT}/skills/typing-patterns/references/dict-typing.md`
```python
# Bad: Weak level
def process(data: dict): ...
# Warning: Medium level
def process(data: dict[str, Any]): ...
# Good: Strong level
class UserData(TypedDict):
id: int
email: str
name: str
def process(data: UserData): ...
```
**Why TypedDict is better:**
- Key checking at compile time (`data["emial"]` → error)
- Value type checking
- IDE autocomplete
- Data structure documentation
**When `dict[K, V]` is acceptable:**
- Homogeneous collections: `dict[str, User]`, `dict[int, float]`
- Caches, counters, ID → object mappings
## Basic Types (Python 3.10+)
```python
# Primitives
x: int = 1
y: str = "hello"
z: bool = True
f: float = 1.5
# Collections (built-in)
items: list[str] = ["a", "b"]
mapping: dict[str, int] = {"a": 1}
unique: set[int] = {1, 2, 3}
pair: tuple[int, str] = (1, "a")
# Union (Python 3.10+)
value: int | str = 1
optional: str | None = None
# Callable
from collections.abc import Callable
handler: Callable[[int, str], bool] = lambda x, s: True
```
## Generics
More details: `${CLAUDE_PLUGIN_ROOT}/skills/typing-patterns/references/generics.md`
```python
from typing import TypeVar, Generic
T = TypeVar("T")
K = TypeVar("K")
V = TypeVar("V")
class Repository(Generic[T]):
def get(self, id: int) -> T | None: ...
def save(self, item: T) -> T: ...
# Usage
class UserRepository(Repository[User]):
pass
# Python 3.12+ syntax
class Repository[T]:
def get(self, id: int) -> T | None: ...
```
## Protocols
```python
from typing import Protocol
class Readable(Protocol):
def read(self) -> str: ...
class Writable(Protocol):
def write(self, data: str) -> None: ...
# Structural subtyping — no explicit inherit needed
class MyFile:
def read(self) -> str:
return "content"
def process(source: Readable) -> str:
return source.read()
process(MyFile()) # OK — MyFile implements Readable
```
## TypeVar with Constraints
```python
from typing import TypeVar
# Bound — only subtypes
T = TypeVar("T", bound=BaseModel)
def validate(model: T) -> T:
# model is guaranteed to have BaseModel methods
return model
# Constraints — only specific types
S = TypeVar("S", str, bytes)
def process(data: S) -> S:
# data is either str or bytes
return data
```
## Overload
```python
from typing import overload
@overload
def process(x: int) -> int: ...
@overload
def process(x: str) -> str: ...
def process(x: int | str) -> int | str:
if isinstance(x, int):
return x * 2
return x.upper()
```
## TypeGuard
```python
from typing import TypeGuard
def is_string_list(val: list[object]) -> TypeGuard[list[str]]:
return all(isinstance(x, str) for x in val)
items: list[object] = ["a", "b", "c"]
if is_string_list(items):
# mypy knows: items is list[str]
print(items[0].upper())
```
## Common Error Solutions
### Optional Without Check
```python
# Bad
def get_name(user: User | None) -> str:
return user.name # Error: Item "None" has no attribute "name"
# Good
def get_name(user: User | None) -> str:
if user is None:
raise ValueError("User is required")
return user.name
```
### Missing Return Type
```python
# Bad
def process(x):
return x * 2
# Good
def process(x: int) -> int:
return x * 2
```
### list Without Type
```python
# Bad
items = [] # Need type annotation
# Good
items: list[str] = []
```
### Callable Types
```python
# Bad
def register(callback):
...
# Good
from collections.abc import Callable
def register(callback: Callable[[int], str]) -> None:
...
# Or with ParamSpec for exact signature passing
from typing import ParamSpec, TypeVar
P = ParamSpec("P")
R = TypeVar("R")
def decorator(func: Callable[P, R]) -> Callable[P, R]:
def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
return func(*args, **kwargs)
return wrapper
```
## Configuration
### mypy (strict)
```toml
[tool.mypy]
python_version = "3.12"
strict = true
warn_return_any = true
warn_unused_ignores = true
disallow_untyped_defs = true
disallow_untyped_calls = true
```
### pyright
```json
{
"typeCheckingMode": "strict",
"pythonVersion": "3.12"
}
```
## Plugin Commands
- `/types:check [path]` — check types
- `/types:explain <error>` — explain error + solution
Files in this skill
- SKILL.md
- references/dict-typing.md
- references/generics.md
- references/why-no-type-ignore.md
Attribution
Comments
Loading comments…
Newsletter
Get the weekly list of safe new skills, and the ones we pulled.