如何保持导入轻量级并仍然正确键入注释？

Question

Tensorflow 是一个超级重磅导入。我只想在需要时导入它。但是，我有这样的模型加载功能：

from typing import Dict, Any
from keras.models import Model  # Heavy import! Takes 2 seconds or so!

# Model loading is a heavy task. Only do it once and keep it in memory
model = None  # type: Optional[Model]

def load_model(config: Dict[str, Any], shape) -> Model:
    """Load a model."""
    if globals()['model'] is None:
        globals()['model'] = create_model(wili.n_classes, shape)
        print(globals()['model'].summary())
    return globals()['model']

Answer 1

也许 TYPE_CHECKING 常量可以帮助您：

if the import is only needed for type annotations in forward references (string literals) or comments, you can write the imports inside if TYPE_CHECKING: so that they are not executed at runtime.

The TYPE_CHECKING constant defined by the typing module is False at runtime but True while type checking.

示例：

# foo.py
from typing import List, TYPE_CHECKING

if TYPE_CHECKING:
    import bar

def listify(arg: 'bar.BarClass') -> 'List[bar.BarClass]':
    return [arg]

# bar.py
from typing import List
from foo import listify

class BarClass:
    def listifyme(self) -> 'List[BarClass]':
        return listify(self)

TYPE_CHECKING也可以用来避免import cycles.

如何保持导入轻量级并仍然正确键入注释？

How can I keep imports lightweight and still properly type annotate?

python

tensorflow

mypy

python-typing