Error codes for strict checks¶
This section documents various errors codes that basedmypy generates
by default, but will be disabled when strict is false (no_strict).
See Error codes for general documentation about error codes
and their configuration. Error codes part 1 documents error codes
that are enabled regardless of strict.
Note
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.
Example:
# 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).
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 = 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.
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)
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.
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)()
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.
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
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.
Example:
# mypy: disallow-untyped-calls
def do_it() -> None:
# Error: Call to untyped function "bad" in typed context [no-untyped-call]
bad()
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.
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]
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'
return
# Error: Statement is unreachable [unreachable]
print('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.
# 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)]
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:
# 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]
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).
# 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:
...
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__.
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].
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.
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]
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__.
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 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.
Example:
# 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).
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: 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.
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:
pass
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()
f(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.
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 defined
Correct 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.
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
...