This section documents various errors codes that mypy generates only if you enable certain options. See :ref:`error-codes` for general documentation about error codes and their configuration. :ref:`error-code-list` documents error codes that are enabled by default.
Note
The examples in this section use :ref:`inline configuration <inline-config>` to specify mypy options. You can also set the same options by using a :ref:`configuration file <config-file>` or :ref:`command-line options <command-line>`.
If you use :option:`--disallow-any-generics <mypy --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.
Example:
# mypy: disallow-any-generics
# Error: Missing type parameters for generic type "list" [type-arg]
def remove_dups(items: list) -> list:
...If you use :option:`--disallow-untyped-defs <mypy --disallow-untyped-defs>`, mypy requires that all functions have annotations (either a Python 3 annotation or a type comment).
Example:
# 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 = 0If you use :option:`--warn-redundant-annotation <mypy --warn-redundant-annotation>`, mypy will generate an error if the annotation type is the same as the inferred type.
Example:
# mypy: warn-redundant-annotation
# Error: Annotation "int" is redundant [redundant-annotation]
count: int = 4If you use :option:`--warn-redundant-casts <mypy --warn-redundant-casts>`, mypy will generate an error if the source type of a cast is the same as the target type.
Example:
# 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)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.
Example:
# 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)()If you use :option:`--strict-equality <mypy --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.
Example:
# 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:option:`--strict-equality <mypy --strict-equality>` does not include comparisons with
None:
# mypy: strict-equality
def is_none(x: str) -> bool:
return x is None # OKIf you want such checks, you must also activate :option:`--strict-equality-for-none <mypy --strict-equality-for-none>` (we might merge these two options later).
# mypy: strict-equality strict-equality-for-none
def is_none(x: str) -> bool:
# Error: Non-overlapping identity check
# (left operand type: "str", right operand type: "None")
return x is NoneIf you use :option:`--disallow-untyped-calls <mypy --disallow-untyped-calls>`, mypy generates an error when you call an unannotated function in an annotated function.
Example:
# mypy: disallow-untyped-calls
def do_it() -> None:
# Error: Call to untyped function "bad" in typed context [no-untyped-call]
bad()
def bad():
...If you use :option:`--warn-return-any <mypy --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.
Example:
# 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]If you use :option:`--disallow-any-unimported <mypy --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:
...If you use :option:`--warn-unreachable <mypy --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'
return
# Error: Statement is unreachable [unreachable]
print('unreachable')If you use :option:`--enable-error-code deprecated <mypy --enable-error-code>`,
mypy generates an error if your code imports a deprecated feature explicitly with a
from mod import depr statement or uses a deprecated feature imported otherwise or defined
locally. Features are considered deprecated when decorated with warnings.deprecated, as
specified in PEP 702.
Use the :option:`--report-deprecated-as-note <mypy --report-deprecated-as-note>` option to
turn all such errors into notes.
Use :option:`--deprecated-calls-exclude <mypy --deprecated-calls-exclude>` to hide warnings
for specific functions, classes and packages.
Note
The warnings module provides the @deprecated decorator since Python 3.13.
To use it with older Python versions, import it from typing_extensions instead.
Examples:
# mypy: report-deprecated-as-error
# Error: abc.abstractproperty is deprecated: Deprecated, use 'property' with 'abstractmethod' instead
from abc import abstractproperty
from typing_extensions import deprecated
@deprecated("use new_function")
def old_function() -> None:
print("I am old")
# Error: __main__.old_function is deprecated: use new_function
old_function()
old_function() # type: ignore[deprecated]If you use :option:`--enable-error-code redundant-expr <mypy --enable-error-code>`, mypy generates an error if it thinks that an expression is redundant.
# 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:
pass
# 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)]If you use :option:`--enable-error-code possibly-undefined <mypy --enable-error-code>`, 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:
# mypy: enable-error-code="possibly-undefined"
from collections.abc 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]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).
# mypy: enable-error-code="truthy-bool"
class Foo:
pass
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:
...Generate an error if a value of type Iterable is used as a boolean
condition, since Iterable does not implement __len__ or __bool__.
Example:
from collections.abc 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].
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.
Example:
# mypy: enable-error-code="ignore-without-code"
class Foo:
def __init__(self, name: str) -> None:
self.name = 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]If you use :option:`--enable-error-code unused-awaitable <mypy --enable-error-code>`,
mypy generates an error if you don't use a returned value that defines __await__.
Example:
# 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?
asyncio.create_task(f())You can assign the value to a temporary, otherwise unused variable to silence the error:
async def g() -> None:
_ = asyncio.create_task(f()) # No errorIf you use :option:`--enable-error-code unused-ignore <mypy --enable-error-code>`,
or :option:`--warn-unused-ignores <mypy --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.
Example:
# Use "mypy --warn-unused-ignores ..."
def add(a: int, b: int) -> int:
# Error: unused "type: ignore" comment
return a + b # type: ignoreNote 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).
Example:
# Use "mypy --warn-unused-ignores ..."
import sys
try:
# 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:
pass
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: ignoreIf you use :option:`--enable-error-code explicit-override <mypy --enable-error-code>`
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.
Note
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.
Example:
# mypy: enable-error-code="explicit-override"
from typing import override
class Parent:
def f(self, x: int) -> None:
pass
def g(self, y: int) -> None:
pass
class Child(Parent):
def f(self, x: int) -> None: # Error: Missing @override decorator
pass
@override
def g(self, y: int) -> None:
passmutable-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()
f(d)
d.x >> 1 # This will crash at runtime, because d.x is now float, not an intMypy 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 :py:func:`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.
Note
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.
# mypy: enable-error-code="unimported-reveal"
x = 1
reveal_type(x) # Note: Revealed type is "builtins.int" \
# Error: Name "reveal_type" is not definedCorrect usage:
# 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 "builtins.int"When this code is enabled, using reveal_locals is always an error,
because there's no way one can import it.
If you use :option:`--disallow-any-explicit <mypy --disallow-any-explicit>`, mypy generates an error
if you use an explicit Any type annotation.
Example:
# mypy: disallow-any-explicit
from typing import Any
x: Any = 1 # Error: Explicit "Any" type annotation [explicit-any]If enabled with :option:`--enable-error-code exhaustive-match <mypy --enable-error-code>`, mypy generates an error if a match statement does not match all possible cases/types.
Example:
import enum
class Color(enum.Enum):
RED = 1
BLUE = 2
val: Color = Color.RED
# OK without --enable-error-code exhaustive-match
match val:
case Color.RED:
print("red")
# With --enable-error-code exhaustive-match
# Error: Match statement has unhandled case for values of type "Literal[Color.BLUE]"
match val:
case Color.RED:
print("red")
# OK with or without --enable-error-code exhaustive-match, since all cases are handled
match val:
case Color.RED:
print("red")
case _:
print("other")If enabled with :option:`--disallow-untyped-decorators <mypy --disallow-untyped-decorators>` mypy generates an error if a typed function is wrapped by an untyped decorator (as this would effectively remove the benefits of typing the function).
Example:
def printing_decorator(func):
def wrapper(*args, **kwds):
print("Calling", func)
return func(*args, **kwds)
return wrapper
# A decorated function.
@printing_decorator # E: Untyped decorator makes function "add_forty_two" untyped [untyped-decorator]
def add_forty_two(value: int) -> int:
return value + 42