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Now please implement the following requirements in the source tree:
PEP 696: Type Defaults for Type Parameters
Abstract
This PEP introduces the concept of type defaults for type parameters,
including TypeVar, ParamSpec, and TypeVarTuple,
which act as defaults for type parameters for which no type is specified.
Default type argument support is available in some popular languages
such as C++, TypeScript, and Rust. A survey of type parameter syntax in
some common languages has been conducted by the author of PEP 695
and can be found in its
Appendix A <695#appendix-a-survey-of-type-parameter-syntax>.
Motivation
T = TypeVar("T", default=int) # This means that if no type is specified T = int
@dataclass
class Box(Generic[T]):
value: T | None = None
reveal_type(Box()) # type is Box[int]
reveal_type(Box(value="Hello World!")) # type is Box[str]
One place this regularly comes up is Generator. I
propose changing the stub definition to something like:
YieldT = TypeVar("YieldT")
SendT = TypeVar("SendT", default=None)
ReturnT = TypeVar("ReturnT", default=None)
class Generator(Generic[YieldT, SendT, ReturnT]): ...
Generator[int] == Generator[int, None] == Generator[int, None, None]
This is also useful for a Generic that is commonly over one type.
class Bot: ...
BotT = TypeVar("BotT", bound=Bot, default=Bot)
class Context(Generic[BotT]):
bot: BotT
class MyBot(Bot): ...
reveal_type(Context().bot) # type is Bot # notice this is not Any which is what it would be currently
reveal_type(Context[MyBot]().bot) # type is MyBot
Not only does this improve typing for those who explicitly use it, it also helps non-typing users who rely on auto-complete to speed up their development.
This design pattern is common in projects like:
- discord.py — where the example above was taken from.
- NumPy — the default for types
like
ndarray'sdtypewould befloat64. Currently it'sUnknownorAny. - TensorFlow — this
could be used for Tensor similarly to
numpy.ndarrayand would be useful to simplify the definition ofLayer.
Specification
Default Ordering and Subscription Rules
The order for defaults should follow the standard function parameter
rules, so a type parameter with no default cannot follow one with
a default value. Doing so should ideally raise a TypeError in
typing._GenericAlias/types.GenericAlias, and a type checker
should flag this as an error.
DefaultStrT = TypeVar("DefaultStrT", default=str)
DefaultIntT = TypeVar("DefaultIntT", default=int)
DefaultBoolT = TypeVar("DefaultBoolT", default=bool)
T = TypeVar("T")
T2 = TypeVar("T2")
class NonDefaultFollowsDefault(Generic[DefaultStrT, T]): ... # Invalid: non-default TypeVars cannot follow ones with defaults
class NoNonDefaults(Generic[DefaultStrT, DefaultIntT]): ...
(
NoNoneDefaults ==
NoNoneDefaults[str] ==
NoNoneDefaults[str, int]
) # All valid
class OneDefault(Generic[T, DefaultBoolT]): ...
OneDefault[float] == OneDefault[float, bool] # Valid
reveal_type(OneDefault) # type is type[OneDefault[T, DefaultBoolT = bool]]
reveal_type(OneDefault[float]()) # type is OneDefault[float, bool]
class AllTheDefaults(Generic[T1, T2, DefaultStrT, DefaultIntT, DefaultBoolT]): ...
reveal_type(AllTheDefaults) # type is type[AllTheDefaults[T1, T2, DefaultStrT = str, DefaultIntT = int, DefaultBoolT = bool]]
reveal_type(AllTheDefaults[int, complex]()) # type is AllTheDefaults[int, complex, str, int, bool]
AllTheDefaults[int] # Invalid: expected 2 arguments to AllTheDefaults
(
AllTheDefaults[int, complex] ==
AllTheDefaults[int, complex, str] ==
AllTheDefaults[int, complex, str, int] ==
AllTheDefaults[int, complex, str, int, bool]
) # All valid
With the new Python 3.12 syntax for generics (introduced by PEP 695), this can be enforced at compile time:
type Alias[DefaultT = int, T] = tuple[DefaultT, T] # SyntaxError: non-default TypeVars cannot follow ones with defaults
def generic_func[DefaultT = int, T](x: DefaultT, y: T) -> None: ... # SyntaxError: non-default TypeVars cannot follow ones with defaults
class GenericClass[DefaultT = int, T]: ... # SyntaxError: non-default TypeVars cannot follow ones with defaults
ParamSpec Defaults
''''''''''''''''''''''
ParamSpec defaults are defined using the same syntax as
TypeVar \ s but use a list of types or an ellipsis
literal "..." or another in-scope ParamSpec (see Scoping Rules_).
DefaultP = ParamSpec("DefaultP", default=[str, int])
class Foo(Generic[DefaultP]): ...
reveal_type(Foo) # type is type[Foo[DefaultP = [str, int]]]
reveal_type(Foo()) # type is Foo[[str, int]]
reveal_type(Foo[[bool, bool]]()) # type is Foo[[bool, bool]]
TypeVarTuple Defaults
'''''''''''''''''''''''''
TypeVarTuple defaults are defined using the same syntax as
TypeVar \ s but use an unpacked tuple of types instead of a single type
or another in-scope TypeVarTuple (see Scoping Rules_).
DefaultTs = TypeVarTuple("DefaultTs", default=Unpack[tuple[str, int]])
class Foo(Generic[*DefaultTs]): ...
reveal_type(Foo) # type is type[Foo[DefaultTs = *tuple[str, int]]]
reveal_type(Foo()) # type is Foo[str, int]
reveal_type(Foo[int, bool]()) # type is Foo[int, bool]
Using Another Type Parameter as default
This allows for a value to be used again when the type parameter to a generic is missing but another type parameter is specified.
To use another type parameter as a default the default and the
type parameter must be the same type (a TypeVar's default must be
a TypeVar, etc.).
This could be used on builtins.slice
where the start parameter should default to int, stop
default to the type of start and step default to int | None.
StartT = TypeVar("StartT", default=int)
StopT = TypeVar("StopT", default=StartT)
StepT = TypeVar("StepT", default=int | None)
class slice(Generic[StartT, StopT, StepT]): ...
reveal_type(slice) # type is type[slice[StartT = int, StopT = StartT, StepT = int | None]]
reveal_type(slice()) # type is slice[int, int, int | None]
reveal_type(slice[str]()) # type is slice[str, str, int | None]
reveal_type(slice[str, bool, timedelta]()) # type is slice[str, bool, timedelta]
T2 = TypeVar("T2", default=DefaultStrT)
class Foo(Generic[DefaultStrT, T2]):
def __init__(self, a: DefaultStrT, b: T2) -> None: ...
reveal_type(Foo(1, "")) # type is Foo[int, str]
Foo[int](1, "") # Invalid: Foo[int, str] cannot be assigned to self: Foo[int, int] in Foo.__init__
Foo[int]("", 1) # Invalid: Foo[str, int] cannot be assigned to self: Foo[int, int] in Foo.__init__
When using a type parameter as the default to another type parameter, the
following rules apply, where T1 is the default for T2.
Scoping Rules
T1 must be used before T2 in the parameter list of the generic.
T2 = TypeVar("T2", default=T1)
class Foo(Generic[T1, T2]): ... # Valid
class Foo(Generic[T1]):
class Bar(Generic[T2]): ... # Valid
StartT = TypeVar("StartT", default="StopT") # Swapped defaults around from previous example
StopT = TypeVar("StopT", default=int)
class slice(Generic[StartT, StopT, StepT]): ...
# ^^^^^^ Invalid: ordering does not allow StopT to be bound
Using a type parameter from an outer scope as a default is not supported.
Bound Rules
T1's bound must be a subtype of T2's bound.
T1 = TypeVar("T1", bound=int)
TypeVar("Ok", default=T1, bound=float) # Valid
TypeVar("AlsoOk", default=T1, bound=int) # Valid
TypeVar("Invalid", default=T1, bound=str) # Invalid: int is not a subtype of str
Constraint Rules
The constraints of T2 must be a superset of the constraints of T1.
T1 = TypeVar("T1", bound=int)
TypeVar("Invalid", float, str, default=T1) # Invalid: upper bound int is incompatible with constraints float or str
T1 = TypeVar("T1", int, str)
TypeVar("AlsoOk", int, str, bool, default=T1) # Valid
TypeVar("AlsoInvalid", bool, complex, default=T1) # Invalid: {bool, complex} is not a superset of {int, str}
Type Parameters as Parameters to Generics
Type parameters are valid as parameters to generics inside of a
default when the first parameter is in scope as determined by the
[previous section](scoping rules_).
T = TypeVar("T")
ListDefaultT = TypeVar("ListDefaultT", default=list[T])
class Bar(Generic[T, ListDefaultT]):
def __init__(self, x: T, y: ListDefaultT): ...
reveal_type(Bar) # type is type[Bar[T, ListDefaultT = list[T]]]
reveal_type(Bar[int]) # type is type[Bar[int, list[int]]]
reveal_type(Bar[int]()) # type is Bar[int, list[int]]
reveal_type(Bar[int, list[str]]()) # type is Bar[int, list[str]]
reveal_type(Bar[int, str]()) # type is Bar[int, str]
Specialisation Rules
Type parameters currently cannot be further subscripted. This might change if Higher Kinded TypeVars are implemented.
Generic TypeAlias\ es
'''''''''''''''''''''''''''''
Generic TypeAlias\ es should be able to be further subscripted
following normal subscription rules. If a type parameter has a default
that hasn't been overridden it should be treated like it was
substituted into the TypeAlias. However, it can be specialised
further down the line.
class SomethingWithNoDefaults(Generic[T, T2]): ...
MyAlias: TypeAlias = SomethingWithNoDefaults[int, DefaultStrT] # Valid
reveal_type(MyAlias) # type is type[SomethingWithNoDefaults[int, DefaultStrT]]
reveal_type(MyAlias[bool]()) # type is SomethingWithNoDefaults[int, bool]
MyAlias[bool, int] # Invalid: too many arguments passed to MyAlias
Subclassing
Subclasses of Generic\ s with type parameters that have defaults
behave similarly to Generic TypeAlias\ es. That is, subclasses can be
further subscripted following normal subscription rules, non-overridden
defaults should be substituted in, and type parameters with such defaults can be
further specialised down the line.
class SubclassMe(Generic[T, DefaultStrT]):
x: DefaultStrT
class Bar(SubclassMe[int, DefaultStrT]): ...
reveal_type(Bar) # type is type[Bar[DefaultStrT = str]]
reveal_type(Bar()) # type is Bar[str]
reveal_type(Bar[bool]()) # type is Bar[bool]
class Foo(SubclassMe[float]): ...
reveal_type(Foo().x) # type is str
Foo[str] # Invalid: Foo cannot be further subscripted
class Baz(Generic[DefaultIntT, DefaultStrT]): ...
class Spam(Baz): ...
reveal_type(Spam()) # type is <subclass of Baz[int, str]>
Using bound and default
If both bound and default are passed default must be a
subtype of bound. Otherwise the type checker should generate an
error.
TypeVar("Ok", bound=float, default=int) # Valid
TypeVar("Invalid", bound=str, default=int) # Invalid: the bound and default are incompatible
Constraints
For constrained TypeVar\ s, the default needs to be one of the
constraints. A type checker should generate an error even if it is a
subtype of one of the constraints.
TypeVar("Ok", float, str, default=float) # Valid
TypeVar("Invalid", float, str, default=int) # Invalid: expected one of float or str got int
Function Defaults
In generic functions, type checkers may use a type parameter's default when the
type parameter cannot be solved to anything. We leave the semantics of this
usage unspecified, as ensuring the default is returned in every code path
where the type parameter can go unsolved may be too hard to implement. Type
checkers are free to either disallow this case or experiment with implementing
support.
T = TypeVar('T', default=int)
def func(x: int | set[T]) -> T: ...
reveal_type(func(0)) # a type checker may reveal T's default of int here
Defaults following TypeVarTuple
A TypeVar that immediately follows a TypeVarTuple is not allowed
to have a default, because it would be ambiguous whether a type argument
should be bound to the TypeVarTuple or the defaulted TypeVar.
Ts = TypeVarTuple("Ts")
T = TypeVar("T", default=bool)
class Foo(Generic[Ts, T]): ... # Type checker error
## Could be reasonably interpreted as either Ts = (int, str, float), T = bool
## or Ts = (int, str), T = float
Foo[int, str, float]
With the Python 3.12 built-in generic syntax, this case should raise a SyntaxError.
However, it is allowed to have a ParamSpec with a default following a
TypeVarTuple with a default, as there can be no ambiguity between a type argument
for the ParamSpec and one for the TypeVarTuple.
Ts = TypeVarTuple("Ts")
P = ParamSpec("P", default=[float, bool])
class Foo(Generic[Ts, P]): ... # Valid
Foo[int, str] # Ts = (int, str), P = [float, bool]
Foo[int, str, [bytes]] # Ts = (int, str), P = [bytes]
Subtyping
Type parameter defaults do not affect the subtyping rules for generic classes. In particular, defaults can be ignored when considering whether a class is compatible with a generic protocol.
TypeVarTuple\ s as Defaults
'''''''''''''''''''''''''''''''
Using a TypeVarTuple as a default is not supported because:
Scoping Rules_ does not allow usage of type parameters from outer scopes.- Multiple
TypeVarTuple\ s cannot appear in the type parameter list for a single object, as specified in646#multiple-type-variable-tuples-not-allowed.
These reasons leave no current valid location where a
TypeVarTuple could be used as the default of another TypeVarTuple.
Binding rules
Type parameter defaults should be bound by attribute access (including call and subscript).
class Foo[T = int]:
def meth(self) -> Self:
return self
reveal_type(Foo.meth) # type is (self: Foo[int]) -> Foo[int]
Implementation
At runtime, this would involve the following changes to the typing
module.
- The classes
TypeVar,ParamSpec, andTypeVarTupleshould expose the type passed todefault. This would be available as a__default__attribute, which would be the publictyping.NoDefaultsentinel — a dedicated marker object returned in place ofNonewhen no default is set, so thatNoneitself stays usable as a genuine default — if no argument is passed, andNoneTypeifdefault=None.
The following changes would be required to both GenericAlias\ es:
- logic to determine the defaults required for a subscription.
- ideally, logic to determine if subscription (like
Generic[T, DefaultT]) would be valid.
The grammar for type parameter lists would need to be updated to allow defaults; see below.
A reference implementation of the runtime changes can be found at https://github.com/Gobot1234/cpython/tree/pep-696
A reference implementation of the type checker can be found at https://github.com/Gobot1234/mypy/tree/TypeVar-defaults
Pyright currently supports this functionality.
Grammar changes
The syntax added in PEP 695 will be extended to introduce a way to specify defaults for type parameters using the "=" operator inside of the square brackets like so:
## TypeVars
class Foo[T = str]: ...
## ParamSpecs
class Baz[**P = [int, str]]: ...
## TypeVarTuples
class Qux[*Ts = *tuple[int, bool]]: ...
## TypeAliases
type Foo[T, U = str] = Bar[T, U]
type Baz[**P = [int, str]] = Spam[**P]
type Qux[*Ts = *tuple[str]] = Ham[*Ts]
type Rab[U, T = str] = Bar[T, U]
Similarly to the bound for a type parameter <695-scoping-behavior>,
defaults should be lazily evaluated, with the same scoping rules to
avoid the unnecessary usage of quotes around them.
This functionality was included in the initial draft of PEP 695 but was removed due to scope creep.
The following changes would be made to the grammar:
type_param:
| a=NAME b=[type_param_bound] d=[type_param_default]
| a=NAME c=[type_param_constraint] d=[type_param_default]
| '*' a=NAME d=[type_param_default]
| '**' a=NAME d=[type_param_default]
type_param_default:
| '=' e=expression
| '=' e=starred_expression
The compiler would enforce that type parameters without defaults cannot
follow type parameters with defaults and that TypeVar\ s with defaults
cannot immediately follow TypeVarTuple\ s.
Rejected Alternatives
Allowing the Type Parameters Defaults to Be Passed to type.__new__'s **kwargs
T = TypeVar("T")
@dataclass
class Box(Generic[T], T=int):
value: T | None = None
While this is much easier to read and follows a similar rationale to the
TypeVar unary syntax, it would not be
backwards compatible as T might already be passed to a
metaclass/superclass or support classes that don't subclass Generic
at runtime.
Ideally, if PEP 637 wasn't rejected, the following would be acceptable:
T = TypeVar("T")
@dataclass
class Box(Generic[T = int]):
value: T | None = None
Allowing Non-defaults to Follow Defaults
YieldT = TypeVar("YieldT", default=Any)
SendT = TypeVar("SendT", default=Any)
ReturnT = TypeVar("ReturnT")
class Coroutine(Generic[YieldT, SendT, ReturnT]): ...
Coroutine[int] == Coroutine[Any, Any, int]
Allowing non-defaults to follow defaults would alleviate the issues with
returning types like Coroutine from functions where the most used
type argument is the last (the return). Allowing non-defaults to follow
defaults is too confusing and potentially ambiguous, even if only the
above two forms were valid. Changing the argument order now would also
break a lot of codebases. This is also solvable in most cases using a
TypeAlias.
Coro: TypeAlias = Coroutine[Any, Any, T]
Coro[int] == Coroutine[Any, Any, int]
Having default Implicitly Be bound
In an earlier version of this PEP, the default was implicitly set
to bound if no value was passed for default. This while
convenient, could have a type parameter with no default follow a
type parameter with a default. Consider:
T = TypeVar("T", bound=int) # default is implicitly int
U = TypeVar("U")
class Foo(Generic[T, U]):
...
## would expand to
T = TypeVar("T", bound=int, default=int)
U = TypeVar("U")
class Foo(Generic[T, U]):
...
This would have also been a breaking change for a small number of cases
where the code relied on Any being the implicit default.
Allowing Type Parameters With Defaults To Be Used in Function Signatures
A previous version of this PEP allowed TypeVarLike\s with defaults to be used in
function signatures. This was removed for the reasons described in
Function Defaults_. Hopefully, this can be added in the future if
a way to get the runtime value of a type parameter is added.
Allowing Type Parameters from Outer Scopes in default
This was deemed too niche a feature to be worth the added complexity. If any cases arise where this is needed, it can be added in a future PEP.
Linked Issue #975 — Allow Generator type annotation to have one argument.
To annotate a generator yielding an int, it's --> Generator[int, None, None]
That's really quite ugly.
It should be Generator[int]
Passing None does not fit the rest of Python where arguments are optional. Also in the rest of Python, the common cases are the default. This makes an unlikely case most prominent over the far more common case. It's Python's job to provide syntactic sugar to deal with the low-level details, not the user. This looks more like C.
https://docs.python.org/3/library/typing.html#typing.Generator
"Alternatively, annotate your generator as having a return type of either Iterable[YieldType] or Iterator[YieldType]"
Yes a generator is an iterator and an iterator is an iterable but then why not set everything as Any? Are we annotating the types or not? That advice makes a mockery of the whole idea. Makes Python harder to teach for no good reason. "Put the type the function returns, unless it's a generator then do this..."
Several people have pointed this out before, their bugs got closed without explanation. One suggested making a bug here, so this is it. Enjoy.
https://github.com/python/mypy/issues/4221 https://bugs.python.org/issue31700
I'm hoping this bug gets closed because someone's already fixed it in a development version.
Cheers.
Source: https://github.com/python/typing/issues/975
Linked Issue #159 — builtins.slice should be generic
It is entirely reasonable that some libraries would have slices with a component type other than int.
Source: https://github.com/python/typing/issues/159
Linked Issue #548 — Higher-Kinded TypeVars
aka type constructors, generic TypeVars
Has there already been discussion about those? I do a lot of FP that results in impossible situations because of this. Consider an example:
A = TypeVar('A')
B = TypeVar('B')
F = TypeVar('F')
class M(Generic[F[X], A]):
def x(fa: F[A], f: Callable[[A], B]) -> F[B]:
return map(f, fa)
M().x([1], str)
I haven't found a way to make this work, does anyone know a trick or is it impossible?
If not, consider the syntax as a proposal.
Reference implementations would be Haskell, Scala.
optimally, the HK's type param would be indexable as well, allowing for F[X[X, X], X[X]]
Summary of current status (by [user-redacted], 2024-02-08):
- [user-redacted] has indicated interest in sponsoring a PEP, conditional on a prototype implementation in a major type checker and a well-specified draft PEP.
- Drafting the PEP takes place in [user-redacted]'s fork of the
pepsrepo. The stub PEP draft so far contains a few examples of the proposed syntax. - That same repo's GitHub Discussions forum forum has been designated as the place to discuss the PEP (and presumably the prototype implementation?). Some limited further discussions have taken place there.
- If you want to be notified of new discussion threads, I think you have to set the whole repo as "watched" in GitHub?
Source: https://github.com/python/typing/issues/548
Linked Issue #813 — [Feature Request] TypeVar variance definition alias
Defining the two variances of a TypeVar is rather verbose:
T_co = TypeVar("T_co", covariant=True)
T_contra = TypeVar("T_contra", contravariant=True)
So I propose an alternative syntax, similar to that of Scala's variances:
T_co = +TypeVar("T_co")
T_contra = -TypeVar("T_contra")
Co- and contra-variance describe increasing and decreasing specificities of the typevars, respectively. So using + and - to symbolize these "directions" makes intuitive sense.