使用從泛型類型派生的類的最佳方法是什么?

假設我們得到了一個通用類定義,例如:

from dataclasses import dataclass
from typing import TypeVar, Generic, List


T1 = TypeVar('T1')
T2 = TypeVar('T2')


@dataclass
class MyGenericClass(Generic[T1, T2]):
    val: T1
    results: List[T2]


@dataclass
class BaseClass:
    my_str: str


@dataclass
class MyTestClass(BaseClass, MyGenericClass[str, int]):
    ...

確定MyTestClass是泛型類(即與常規數據類相反)的最佳方法是什么?

此外,在這種情況下,typing模塊是否提供了將泛型類型(TypeVar)解析為具體類型關系的簡單方法?

例如,給定上面的results: List[T2],我想理解MyTestClass上下文中的T2將解析為int類型。

確定類是否為泛型

當前,如果運行set(vars(MyTestClass)) - set(vars(BaseClass)),將得到以下結果:

{'__parameters__', '__orig_bases__'}

然而,我想知道typing是否提供了一種簡單的方法來確定類是泛型還是來自泛型類的sub-classes,例如typing.Dict

所以我感興趣的是is_cls_generic()的效果。

解析TypeVar類型

目前,當我調用typing.get_type_hints(MyTestClass)時,我得到以下結果:

{'val': ~T1, 'results': typing.List[~T2], 'my_str': <class 'str'>}

我想知道typing模塊是否提供了一種簡單的方法來解析這些TypeVar變量,因此期望的結果是:

{'val': str, 'results': typing.List[int], 'my_str': str}
? 最佳回答:

Credits

Introspection helpers

mypy沒有提供您需要的功能,但手工實現并不太困難。

# introspection.py

# mypy issue 776
import sys
from typing import get_args, get_origin, get_type_hints, Generic, Protocol
from typing import _collect_type_vars, _eval_type, _strip_annotations

def _generic_mro(result, tp):
    origin = get_origin(tp)
    if origin is None:
        origin = tp
    result[origin] = tp
    if hasattr(origin, "__orig_bases__"):
        parameters = _collect_type_vars(origin.__orig_bases__)
        if origin is tp and parameters:
            result[origin] = origin[parameters]
        substitution = dict(zip(parameters, get_args(tp)))
        for base in origin.__orig_bases__:
            if get_origin(base) in result:
                continue
            base_parameters = getattr(base, "__parameters__", ())
            if base_parameters:
                base = base[tuple(substitution.get(p, p) for p in base_parameters)]
            _generic_mro(result, base)

def generic_mro(tp):
    origin = get_origin(tp)
    if origin is None and not hasattr(tp, "__orig_bases__"):
        if not isinstance(tp, type):
            raise TypeError(f"{tp!r} is not a type or a generic alias")
        return tp.__mro__
    # sentinel value to avoid to subscript Generic and Protocol
    result = {Generic: Generic, Protocol: Protocol}
    _generic_mro(result, tp)
    cls = origin if origin is not None else tp
    return tuple(result.get(sub_cls, sub_cls) for sub_cls in cls.__mro__)

def _class_annotations(cls, globalns, localns):
    hints = {}
    if globalns is None:
        base_globals = sys.modules[cls.__module__].__dict__
    else:
        base_globals = globalns
    for name, value in cls.__dict__.get("__annotations__", {}).items():
        if value is None:
            value = type(None)
        if isinstance(value, str):
            value = ForwardRef(value, is_argument=False)
        hints[name] = _eval_type(value, base_globals, localns)
    return hints


# For brevety of the example, the implementation just add the substitute_type_vars
# implementation and default to get_type_hints. Of course, it would have to be directly
# integrated into get_type_hints
def get_type_hints2(
    obj, globalns=None, localns=None, include_extras=False, substitute_type_vars=False
):
    if substitute_type_vars and (isinstance(obj, type) or isinstance(get_origin(obj), type)):
        hints = {}
        for base in reversed(generic_mro(obj)):
            origin = get_origin(base)
            if hasattr(origin, "__orig_bases__"):
                parameters = _collect_type_vars(origin.__orig_bases__)
                substitution = dict(zip(parameters, get_args(base)))
                annotations = _class_annotations(get_origin(base), globalns, localns)
                for name, tp in annotations.items():
                    if isinstance(tp, TypeVar):
                        hints[name] = substitution.get(tp, tp)
                    elif tp_params := getattr(tp, "__parameters__", ()):
                        hints[name] = tp[
                            tuple(substitution.get(p, p) for p in tp_params)
                        ]
                    else:
                        hints[name] = tp
            else:
                hints.update(_class_annotations(base, globalns, localns))
        return (
            hints
            if include_extras
            else {k: _strip_annotations(t) for k, t in hints.items()}
        )
    else:
        return get_type_hints(obj, globalns, localns, include_extras)

# Generic classes that accept at least one parameter type.
# It works also for `Protocol`s that have at least one argument.
def is_generic_class(klass):
    return hasattr(klass, '__orig_bases__') and getattr(klass, '__parameters__', None)

Usage

from dataclasses import dataclass
from typing import TypeVar, Generic, List
from .introspection import get_type_hints2, is_generic_class

T1 = TypeVar('T1')
T2 = TypeVar('T2')

@dataclass
class MyGenericClass(Generic[T1, T2]):
    val: T1
    results: List[T2]

@dataclass
class BaseClass:
    my_str: str

@dataclass
class MyTestClass(BaseClass, MyGenericClass[str, int]):
    ...

print(get_type_hints2(MyTestClass, substitute_type_vars=True))
# {'val': <class 'str'>, 'results': typing.List[int], 'my_str': <class 'str'>}
print(get_type_hints2(BaseClass, substitute_type_vars=True))
# {'my_str': <class 'str'>}
print(get_type_hints2(MyGenericClass, substitute_type_vars=True))
# {'val': ~T1, 'results': typing.List[~T2]}
print(is_generic_class(MyGenericClass))
# True
print(is_generic_class(MyTestClass))
# False
print(is_generic_class(BaseClass))
# False
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