Error codes for optional checks

This section documents various errors codes that mypy generates only if you enable certain options. See Error codes for general documentation about error codes. Error codes enabled by default documents error codes that are enabled by default.


The examples in this section use inline configuration to specify mypy options. You can also set the same options by using a configuration file or command-line options.

Check that type arguments exist [type-arg]

If you use --disallow-any-generics, mypy requires that each generic type has values for each type argument. For example, the types list or dict would be rejected. You should instead use types like list[int] or dict[str, int]. Any omitted generic type arguments get implicit Any values. The type list is equivalent to list[Any], and so on.


# mypy: disallow-any-generics

# Error: Missing type parameters for generic type "list"  [type-arg]
def remove_dups(items: list) -> list:

Check that every function has an annotation [no-untyped-def]

If you use --disallow-untyped-defs, mypy requires that all functions have annotations (either a Python 3 annotation or a type comment).


# mypy: disallow-untyped-defs

def inc(x):  # Error: Function is missing a type annotation  [no-untyped-def]
    return x + 1

def inc_ok(x: int) -> int:  # OK
    return x + 1

class Counter:
     # Error: Function is missing a type annotation  [no-untyped-def]
     def __init__(self):
         self.value = 0

class CounterOk:
     # OK: An explicit "-> None" is needed if "__init__" takes no arguments
     def __init__(self) -> None:
         self.value = 0

Check that cast is not redundant [redundant-cast]

If you use --warn-redundant-casts, mypy will generate an error if the source type of a cast is the same as the target type.


# mypy: warn-redundant-casts

from typing import cast

Count = int

def example(x: Count) -> int:
    # Error: Redundant cast to "int"  [redundant-cast]
    return cast(int, x)

Check that methods do not have redundant Self annotations [redundant-self]

If a method uses the Self type in the return type or the type of a non-self argument, there is no need to annotate the self argument explicitly. Such annotations are allowed by PEP 673 but are redundant. If you enable this error code, mypy will generate an error if there is a redundant Self type.


# mypy: enable-error-code="redundant-self"

from typing import Self

class C:
    # Error: Redundant "Self" annotation for the first method argument
    def copy(self: Self) -> Self:
        return type(self)()

Check that comparisons are overlapping [comparison-overlap]

If you use --strict-equality, mypy will generate an error if it thinks that a comparison operation is always true or false. These are often bugs. Sometimes mypy is too picky and the comparison can actually be useful. Instead of disabling strict equality checking everywhere, you can use # type: ignore[comparison-overlap] to ignore the issue on a particular line only.


# mypy: strict-equality

def is_magic(x: bytes) -> bool:
    # Error: Non-overlapping equality check (left operand type: "bytes",
    #        right operand type: "str")  [comparison-overlap]
    return x == 'magic'

We can fix the error by changing the string literal to a bytes literal:

# mypy: strict-equality

def is_magic(x: bytes) -> bool:
    return x == b'magic'  # OK

Check that no untyped functions are called [no-untyped-call]

If you use --disallow-untyped-calls, mypy generates an error when you call an unannotated function in an annotated function.


# mypy: disallow-untyped-calls

def do_it() -> None:
    # Error: Call to untyped function "bad" in typed context  [no-untyped-call]

def bad():

Check that function does not return Any value [no-any-return]

If you use --warn-return-any, mypy generates an error if you return a value with an Any type in a function that is annotated to return a non-Any value.


# mypy: warn-return-any

def fields(s):
     return s.split(',')

def first_field(x: str) -> str:
    # Error: Returning Any from function declared to return "str"  [no-any-return]
    return fields(x)[0]

Check that types have no Any components due to missing imports [no-any-unimported]

If you use --disallow-any-unimported, mypy generates an error if a component of a type becomes Any because mypy couldn’t resolve an import. These “stealth” Any types can be surprising and accidentally cause imprecise type checking.

In this example, we assume that mypy can’t find the module animals, which means that Cat falls back to Any in a type annotation:

# mypy: disallow-any-unimported

from animals import Cat  # type: ignore

# Error: Argument 1 to "feed" becomes "Any" due to an unfollowed import  [no-any-unimported]
def feed(cat: Cat) -> None:

Check that statement or expression is unreachable [unreachable]

If you use --warn-unreachable, mypy generates an error if it thinks that a statement or expression will never be executed. In most cases, this is due to incorrect control flow or conditional checks that are accidentally always true or false.

# mypy: warn-unreachable

def example(x: int) -> None:
    # Error: Right operand of "or" is never evaluated  [unreachable]
    assert isinstance(x, int) or x == 'unused'

    # Error: Statement is unreachable  [unreachable]

Check that expression is redundant [redundant-expr]

If you use --enable-error-code redundant-expr, mypy generates an error if it thinks that an expression is redundant.

# Use "mypy --enable-error-code redundant-expr ..."

def example(x: int) -> None:
    # Error: Left operand of "and" is always true  [redundant-expr]
    if isinstance(x, int) and x > 0:

    # Error: If condition is always true  [redundant-expr]
    1 if isinstance(x, int) else 0

    # Error: If condition in comprehension is always true  [redundant-expr]
    [i for i in range(x) if isinstance(i, int)]

Warn about variables that are defined only in some execution paths [possibly-undefined]

If you use --enable-error-code possibly-undefined, mypy generates an error if it cannot verify that a variable will be defined in all execution paths. This includes situations when a variable definition appears in a loop, in a conditional branch, in an except handler, etc. For example:

# Use "mypy --enable-error-code possibly-undefined ..."

from typing import Iterable

def test(values: Iterable[int], flag: bool) -> None:
    if flag:
        a = 1
    z = a + 1  # Error: Name "a" may be undefined [possibly-undefined]

    for v in values:
        b = v
    z = b + 1  # Error: Name "b" may be undefined [possibly-undefined]

Check that expression is not implicitly true in boolean context [truthy-bool]

Warn when the type of an expression in a boolean context does not implement __bool__ or __len__. Unless one of these is implemented by a subtype, the expression will always be considered true, and there may be a bug in the condition.

As an exception, the object type is allowed in a boolean context. Using an iterable value in a boolean context has a separate error code (see below).

# Use "mypy --enable-error-code truthy-bool ..."

class Foo:
foo = Foo()
# Error: "foo" has type "Foo" which does not implement __bool__ or __len__ so it could always be true in boolean context
if foo:

Check that iterable is not implicitly true in boolean context [truthy-iterable]

Generate an error if a value of type Iterable is used as a boolean condition, since Iterable does not implement __len__ or __bool__.


from typing import Iterable

def transform(items: Iterable[int]) -> list[int]:
    # Error: "items" has type "Iterable[int]" which can always be true in boolean context. Consider using "Collection[int]" instead.  [truthy-iterable]
    if not items:
        return [42]
    return [x + 1 for x in items]

If transform is called with a Generator argument, such as int(x) for x in [], this function would not return [42] unlike what might be intended. Of course, it’s possible that transform is only called with list or other container objects, and the if not items check is actually valid. If that is the case, it is recommended to annotate items as Collection[int] instead of Iterable[int].

Check that # type: ignore include an error code [ignore-without-code]

Warn when a # type: ignore comment does not specify any error codes. This clarifies the intent of the ignore and ensures that only the expected errors are silenced.


# Use "mypy --enable-error-code ignore-without-code ..."

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

f = Foo('foo')

# This line has a typo that mypy can't help with as both:
# - the expected error 'assignment', and
# - the unexpected error 'attr-defined'
# are silenced.
# Error: "type: ignore" comment without error code (consider "type: ignore[attr-defined]" instead)
f.nme = 42  # type: ignore

# This line warns correctly about the typo in the attribute name
# Error: "Foo" has no attribute "nme"; maybe "name"?
f.nme = 42  # type: ignore[assignment]

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

If you use --enable-error-code unused-awaitable, mypy generates an error if you don’t use a returned value that defines __await__.


# Use "mypy --enable-error-code unused-awaitable ..."

import asyncio

async def f() -> int: ...

async def g() -> None:
    # Error: Value of type "Task[int]" must be used
    #        Are you missing an await?

You can assign the value to a temporary, otherwise unused to variable to silence the error:

async def g() -> None:
    _ = asyncio.create_task(f())  # No error

Check that # type: ignore comment is used [unused-ignore]

If you use --enable-error-code unused-ignore, or --warn-unused-ignores mypy generates an error if you don’t use a # type: ignore comment, i.e. if there is a comment, but there would be no error generated by mypy on this line anyway.


# Use "mypy --warn-unused-ignores ..."

def add(a: int, b: int) -> int:
    # Error: unused "type: ignore" comment
    return a + b  # type: ignore

Note that due to a specific nature of this comment, the only way to selectively silence it, is to include the error code explicitly. Also note that this error is not shown if the # type: ignore is not used due to code being statically unreachable (e.g. due to platform or version checks).


# Use "mypy --warn-unused-ignores ..."

import sys

    # The "[unused-ignore]" is needed to get a clean mypy run
    # on both Python 3.8, and 3.9 where this module was added
    import graphlib  # type: ignore[import,unused-ignore]
except ImportError:

if sys.version_info >= (3, 9):
    # The following will not generate an error on either
    # Python 3.8, or Python 3.9
    42 + "testing..."  # type: ignore

Check that @override is used when overriding a base class method [explicit-override]

If you use --enable-error-code explicit-override mypy generates an error if you override a base class method without using the @override decorator. An error will not be emitted for overrides of __init__ or __new__. See PEP 698.


Starting with Python 3.12, the @override decorator can be imported from typing. To use it with older Python versions, import it from typing_extensions instead.


# Use "mypy --enable-error-code explicit-override ..."

from typing import override

class Parent:
    def f(self, x: int) -> None:

    def g(self, y: int) -> None:

class Child(Parent):
    def f(self, x: int) -> None:  # Error: Missing @override decorator

    def g(self, y: int) -> None:

Check that overrides of mutable attributes are safe [mutable-override]

mutable-override will enable the check for unsafe overrides of mutable attributes. For historical reasons, and because this is a relatively common pattern in Python, this check is not enabled by default. The example below is unsafe, and will be flagged when this error code is enabled:

from typing import Any

class C:
    x: float
    y: float
    z: float

class D(C):
    x: int  # Error: Covariant override of a mutable attribute
            # (base class "C" defined the type as "float",
            # expression has type "int")  [mutable-override]
    y: float  # OK
    z: Any  # OK

def f(c: C) -> None:
    c.x = 1.1
d = D()
d.x >> 1  # This will crash at runtime, because d.x is now float, not an int

Check that reveal_type is imported from typing or typing_extensions [unimported-reveal]

Mypy used to have reveal_type as a special builtin that only existed during type-checking. In runtime it fails with expected NameError, which can cause real problem in production, hidden from mypy.

But, in Python3.11 typing.reveal_type() was added. typing_extensions ported this helper to all supported Python versions.

Now users can actually import reveal_type to make the runtime code safe.


Starting with Python 3.11, the reveal_type function can be imported from typing. To use it with older Python versions, import it from typing_extensions instead.

# Use "mypy --enable-error-code unimported-reveal"

x = 1
reveal_type(x)  # Note: Revealed type is "" \
                # Error: Name "reveal_type" is not defined

Correct usage:

# Use "mypy --enable-error-code unimported-reveal"
from typing import reveal_type   # or `typing_extensions`

x = 1
# This won't raise an error:
reveal_type(x)  # Note: Revealed type is ""

When this code is enabled, using reveal_locals is always an error, because there’s no way one can import it.

Check that TypeIs narrows types [narrowed-type-not-subtype]

PEP 742 requires that when TypeIs is used, the narrowed type must be a subtype of the original type:

from typing_extensions import TypeIs

def f(x: int) -> TypeIs[str]:  # Error, str is not a subtype of int

def g(x: object) -> TypeIs[str]:  # OK