Error codes enabled by default

This section documents various errors codes that mypy can generate with default options. See Error codes for general documentation about error codes. Error codes for optional checks documents additional error codes that you can enable.

Check that attribute exists [attr-defined]

Mypy checks that an attribute is defined in the target class or module when using the dot operator. This applies to both getting and setting an attribute. New attributes are defined by assignments in the class body, or assignments to self.x in methods. These assignments don’t generate attr-defined errors.

Example:

class Resource:
    def __init__(self, name: str) -> None:
        self.name = name

r = Resource('x')
print(r.name)  # OK
print(r.id)  # Error: "Resource" has no attribute "id"  [attr-defined]
r.id = 5  # Error: "Resource" has no attribute "id"  [attr-defined]

This error code is also generated if an imported name is not defined in the module in a from ... import statement (as long as the target module can be found):

# Error: Module "os" has no attribute "non_existent"  [attr-defined]
from os import non_existent

A reference to a missing attribute is given the Any type. In the above example, the type of non_existent will be Any, which can be important if you silence the error.

Check that attribute exists in each union item [union-attr]

If you access the attribute of a value with a union type, mypy checks that the attribute is defined for every type in that union. Otherwise the operation can fail at runtime. This also applies to optional types.

Example:

from typing import Union

class Cat:
    def sleep(self) -> None: ...
    def miaow(self) -> None: ...

class Dog:
    def sleep(self) -> None: ...
    def follow_me(self) -> None: ...

def func(animal: Union[Cat, Dog]) -> None:
    # OK: 'sleep' is defined for both Cat and Dog
    animal.sleep()
    # Error: Item "Cat" of "Union[Cat, Dog]" has no attribute "follow_me"  [union-attr]
    animal.follow_me()

You can often work around these errors by using assert isinstance(obj, ClassName) or assert obj is not None to tell mypy that you know that the type is more specific than what mypy thinks.

Check that name is defined [name-defined]

Mypy expects that all references to names have a corresponding definition in an active scope, such as an assignment, function definition or an import. This can catch missing definitions, missing imports, and typos.

This example accidentally calls sort() instead of sorted():

x = sort([3, 2, 4])  # Error: Name "sort" is not defined  [name-defined]

Check arguments in calls [call-arg]

Mypy expects that the number and names of arguments match the called function. Note that argument type checks have a separate error code arg-type.

Example:

from typing import Sequence

def greet(name: str) -> None:
     print('hello', name)

greet('jack')  # OK
greet('jill', 'jack')  # Error: Too many arguments for "greet"  [call-arg]

Check argument types [arg-type]

Mypy checks that argument types in a call match the declared argument types in the signature of the called function (if one exists).

Example:

from typing import Optional

def first(x: list[int]) -> Optional[int]:
    return x[0] if x else 0

t = (5, 4)
# Error: Argument 1 to "first" has incompatible type "tuple[int, int]";
#        expected "list[int]"  [arg-type]
print(first(t))

Check calls to overloaded functions [call-overload]

When you call an overloaded function, mypy checks that at least one of the signatures of the overload items match the argument types in the call.

Example:

from typing import overload, Optional

@overload
def inc_maybe(x: None) -> None: ...

@overload
def inc_maybe(x: int) -> int: ...

def inc_maybe(x: Optional[int]) -> Optional[int]:
     if x is None:
         return None
     else:
         return x + 1

inc_maybe(None)  # OK
inc_maybe(5)  # OK

# Error: No overload variant of "inc_maybe" matches argument type "float"  [call-overload]
inc_maybe(1.2)

Check validity of types [valid-type]

Mypy checks that each type annotation and any expression that represents a type is a valid type. Examples of valid types include classes, union types, callable types, type aliases, and literal types. Examples of invalid types include bare integer literals, functions, variables, and modules.

This example incorrectly uses the function log as a type:

def log(x: object) -> None:
    print('log:', repr(x))

# Error: Function "t.log" is not valid as a type  [valid-type]
def log_all(objs: list[object], f: log) -> None:
    for x in objs:
        f(x)

You can use Callable as the type for callable objects:

from typing import Callable

# OK
def log_all(objs: list[object], f: Callable[[object], None]) -> None:
    for x in objs:
        f(x)

Require annotation if variable type is unclear [var-annotated]

In some cases mypy can’t infer the type of a variable without an explicit annotation. Mypy treats this as an error. This typically happens when you initialize a variable with an empty collection or None. If mypy can’t infer the collection item type, mypy replaces any parts of the type it couldn’t infer with Any and generates an error.

Example with an error:

class Bundle:
    def __init__(self) -> None:
        # Error: Need type annotation for "items"
        #        (hint: "items: list[<type>] = ...")  [var-annotated]
        self.items = []

reveal_type(Bundle().items)  # list[Any]

To address this, we add an explicit annotation:

 class Bundle:
     def __init__(self) -> None:
         self.items: list[str] = []  # OK

reveal_type(Bundle().items)  # list[str]

Check validity of overrides [override]

Mypy checks that an overridden method or attribute is compatible with the base class. A method in a subclass must accept all arguments that the base class method accepts, and the return type must conform to the return type in the base class (Liskov substitution principle).

Argument types can be more general is a subclass (i.e., they can vary contravariantly). The return type can be narrowed in a subclass (i.e., it can vary covariantly). It’s okay to define additional arguments in a subclass method, as long all extra arguments have default values or can be left out (*args, for example).

Example:

from typing import Optional, Union

class Base:
    def method(self,
               arg: int) -> Optional[int]:
        ...

class Derived(Base):
    def method(self,
               arg: Union[int, str]) -> int:  # OK
        ...

class DerivedBad(Base):
    # Error: Argument 1 of "method" is incompatible with "Base"  [override]
    def method(self,
               arg: bool) -> int:
        ...

Check that function returns a value [return]

If a function has a non-None return type, mypy expects that the function always explicitly returns a value (or raises an exception). The function should not fall off the end of the function, since this is often a bug.

Example:

# Error: Missing return statement  [return]
def show(x: int) -> int:
    print(x)

# Error: Missing return statement  [return]
def pred1(x: int) -> int:
    if x > 0:
        return x - 1

# OK
def pred2(x: int) -> int:
    if x > 0:
        return x - 1
    else:
        raise ValueError('not defined for zero')

Check that return value is compatible [return-value]

Mypy checks that the returned value is compatible with the type signature of the function.

Example:

def func(x: int) -> str:
    # Error: Incompatible return value type (got "int", expected "str")  [return-value]
    return x + 1

Check types in assignment statement [assignment]

Mypy checks that the assigned expression is compatible with the assignment target (or targets).

Example:

class Resource:
    def __init__(self, name: str) -> None:
        self.name = name

r = Resource('A')

r.name = 'B'  # OK

# Error: Incompatible types in assignment (expression has type "int",
#        variable has type "str")  [assignment]
r.name = 5

Check type variable values [type-var]

Mypy checks that value of a type variable is compatible with a value restriction or the upper bound type.

Example:

from typing import TypeVar

T1 = TypeVar('T1', int, float)

def add(x: T1, y: T1) -> T1:
    return x + y

add(4, 5.5)  # OK

# Error: Value of type variable "T1" of "add" cannot be "str"  [type-var]
add('x', 'y')

Check uses of various operators [operator]

Mypy checks that operands support a binary or unary operation, such as + or ~. Indexing operations are so common that they have their own error code index (see below).

Example:

# Error: Unsupported operand types for + ("int" and "str")  [operator]
1 + 'x'

Check indexing operations [index]

Mypy checks that the indexed value in indexing operation such as x[y] supports indexing, and that the index expression has a valid type.

Example:

a = {'x': 1, 'y': 2}

a['x']  # OK

# Error: Invalid index type "int" for "dict[str, int]"; expected type "str"  [index]
print(a[1])

# Error: Invalid index type "bytes" for "dict[str, int]"; expected type "str"  [index]
a[b'x'] = 4

Check list items [list-item]

When constructing a list using [item, ...], mypy checks that each item is compatible with the list type that is inferred from the surrounding context.

Example:

# Error: List item 0 has incompatible type "int"; expected "str"  [list-item]
a: list[str] = [0]

Check dict items [dict-item]

When constructing a dictionary using {key: value, ...} or dict(key=value, ...), mypy checks that each key and value is compatible with the dictionary type that is inferred from the surrounding context.

Example:

# Error: Dict entry 0 has incompatible type "str": "str"; expected "str": "int"  [dict-item]
d: dict[str, int] = {'key': 'value'}

Check TypedDict items [typeddict-item]

When constructing a TypedDict object, mypy checks that each key and value is compatible with the TypedDict type that is inferred from the surrounding context.

When getting a TypedDict item, mypy checks that the key exists. When assigning to a TypedDict, mypy checks that both the key and the value are valid.

Example:

from typing_extensions import TypedDict

class Point(TypedDict):
    x: int
    y: int

# Error: Incompatible types (expression has type "float",
#        TypedDict item "x" has type "int")  [typeddict-item]
p: Point = {'x': 1.2, 'y': 4}

Check that type of target is known [has-type]

Mypy sometimes generates an error when it hasn’t inferred any type for a variable being referenced. This can happen for references to variables that are initialized later in the source file, and for references across modules that form an import cycle. When this happens, the reference gets an implicit Any type.

In this example the definitions of x and y are circular:

class Problem:
    def set_x(self) -> None:
        # Error: Cannot determine type of "y"  [has-type]
        self.x = self.y

    def set_y(self) -> None:
        self.y = self.x

To work around this error, you can add an explicit type annotation to the target variable or attribute. Sometimes you can also reorganize the code so that the definition of the variable is placed earlier than the reference to the variable in a source file. Untangling cyclic imports may also help.

We add an explicit annotation to the y attribute to work around the issue:

class Problem:
    def set_x(self) -> None:
        self.x = self.y  # OK

    def set_y(self) -> None:
        self.y: int = self.x  # Added annotation here

Check that import target can be found [import]

Mypy generates an error if it can’t find the source code or a stub file for an imported module.

Example:

# Error: Cannot find implementation or library stub for module named 'acme'  [import]
import acme

See Missing imports for how to work around these errors.

Check that each name is defined once [no-redef]

Mypy may generate an error if you have multiple definitions for a name in the same namespace. The reason is that this is often an error, as the second definition may overwrite the first one. Also, mypy often can’t be able to determine whether references point to the first or the second definition, which would compromise type checking.

If you silence this error, all references to the defined name refer to the first definition.

Example:

class A:
    def __init__(self, x: int) -> None: ...

class A:  # Error: Name "A" already defined on line 1  [no-redef]
    def __init__(self, x: str) -> None: ...

# Error: Argument 1 to "A" has incompatible type "str"; expected "int"
#        (the first definition wins!)
A('x')

Check that called function returns a value [func-returns-value]

Mypy reports an error if you call a function with a None return type and don’t ignore the return value, as this is usually (but not always) a programming error.

In this example, the if f() check is always false since f returns None:

def f() -> None:
    ...

# OK: we don't do anything with the return value
f()

# Error: "f" does not return a value  [func-returns-value]
if f():
     print("not false")

Check instantiation of abstract classes [abstract]

Mypy generates an error if you try to instantiate an abstract base class (ABC). An abstract base class is a class with at least one abstract method or attribute. (See also abc module documentation)

Sometimes a class is made accidentally abstract, often due to an unimplemented abstract method. In a case like this you need to provide an implementation for the method to make the class concrete (non-abstract).

Example:

from abc import ABCMeta, abstractmethod

class Persistent(metaclass=ABCMeta):
    @abstractmethod
    def save(self) -> None: ...

class Thing(Persistent):
    def __init__(self) -> None:
        ...

    ...  # No "save" method

# Error: Cannot instantiate abstract class "Thing" with abstract attribute "save"  [abstract]
t = Thing()

Safe handling of abstract type object types [type-abstract]

Mypy always allows instantiating (calling) type objects typed as Type[t], even if it is not known that t is non-abstract, since it is a common pattern to create functions that act as object factories (custom constructors). Therefore, to prevent issues described in the above section, when an abstract type object is passed where Type[t] is expected, mypy will give an error. Example:

from abc import ABCMeta, abstractmethod
from typing import List, Type, TypeVar

class Config(metaclass=ABCMeta):
    @abstractmethod
    def get_value(self, attr: str) -> str: ...

T = TypeVar("T")
def make_many(typ: Type[T], n: int) -> List[T]:
    return [typ() for _ in range(n)]  # This will raise if typ is abstract

# Error: Only concrete class can be given where "Type[Config]" is expected [type-abstract]
make_many(Config, 5)

Check that call to an abstract method via super is valid [safe-super]

Abstract methods often don’t have any default implementation, i.e. their bodies are just empty. Calling such methods in subclasses via super() will cause runtime errors, so mypy prevents you from doing so:

from abc import abstractmethod
class Base:
    @abstractmethod
    def foo(self) -> int: ...
class Sub(Base):
    def foo(self) -> int:
        return super().foo() + 1  # error: Call to abstract method "foo" of "Base" with
                                  # trivial body via super() is unsafe  [safe-super]
Sub().foo()  # This will crash at runtime.

Mypy considers the following as trivial bodies: a pass statement, a literal ellipsis ..., a docstring, and a raise NotImplementedError statement.

Check the target of NewType [valid-newtype]

The target of a NewType definition must be a class type. It can’t be a union type, Any, or various other special types.

You can also get this error if the target has been imported from a module whose source mypy cannot find, since any such definitions are treated by mypy as values with Any types. Example:

from typing import NewType

# The source for "acme" is not available for mypy
from acme import Entity  # type: ignore

# Error: Argument 2 to NewType(...) must be subclassable (got "Any")  [valid-newtype]
UserEntity = NewType('UserEntity', Entity)

To work around the issue, you can either give mypy access to the sources for acme or create a stub file for the module. See Missing imports for more information.

Check the return type of __exit__ [exit-return]

If mypy can determine that __exit__ always returns False, mypy checks that the return type is not bool. The boolean value of the return type affects which lines mypy thinks are reachable after a with statement, since any __exit__ method that can return True may swallow exceptions. An imprecise return type can result in mysterious errors reported near with statements.

To fix this, use either typing_extensions.Literal[False] or None as the return type. Returning None is equivalent to returning False in this context, since both are treated as false values.

Example:

class MyContext:
    ...
    def __exit__(self, exc, value, tb) -> bool:  # Error
        print('exit')
        return False

This produces the following output from mypy:

example.py:3: error: "bool" is invalid as return type for "__exit__" that always returns False
example.py:3: note: Use "typing_extensions.Literal[False]" as the return type or change it to
    "None"
example.py:3: note: If return type of "__exit__" implies that it may return True, the context
    manager may swallow exceptions

You can use Literal[False] to fix the error:

from typing_extensions import Literal

class MyContext:
    ...
    def __exit__(self, exc, value, tb) -> Literal[False]:  # OK
        print('exit')
        return False

You can also use None:

class MyContext:
    ...
    def __exit__(self, exc, value, tb) -> None:  # Also OK
        print('exit')

Check that naming is consistent [name-match]

The definition of a named tuple or a TypedDict must be named consistently when using the call-based syntax. Example:

from typing import NamedTuple

# Error: First argument to namedtuple() should be "Point2D", not "Point"
Point2D = NamedTuple("Point", [("x", int), ("y", int)])

Check that overloaded functions have an implementation [no-overload-impl]

Overloaded functions outside of stub files must be followed by a non overloaded implementation.

from typing import overload

@overload
def func(value: int) -> int:
    ...

@overload
def func(value: str) -> str:
    ...

# presence of required function below is checked
def func(value):
    pass  # actual implementation

Check that coroutine return value is used [unused-coroutine]

Mypy ensures that return values of async def functions are not ignored, as this is usually a programming error, as the coroutine won’t be executed at the call site.

async def f() -> None:
    ...

async def g() -> None:
    f()  # Error: missing await
    await f()  # OK

You can work around this error by assigning the result to a temporary, otherwise unused variable:

_ = f()  # No error

Check types in assert_type [assert-type]

The inferred type for an expression passed to assert_type must match the provided type.

from typing_extensions import assert_type

assert_type([1], list[int])  # OK

assert_type([1], list[str])  # Error

Report syntax errors [syntax]

If the code being checked is not syntactically valid, mypy issues a syntax error. Most, but not all, syntax errors are blocking errors: they can’t be ignored with a # type: ignore comment.

Miscellaneous checks [misc]

Mypy performs numerous other, less commonly failing checks that don’t have specific error codes. These use the misc error code. Other than being used for multiple unrelated errors, the misc error code is not special. For example, you can ignore all errors in this category by using # type: ignore[misc] comment. Since these errors are not expected to be common, it’s unlikely that you’ll see two different errors with the misc code on a single line – though this can certainly happen once in a while.

Note

Future mypy versions will likely add new error codes for some errors that currently use the misc error code.