epy.lazy_imports#

etils.epy.lazy_imports( *, error_callback: str | Callable[[Exception], None] | None = None, success_callback: Callable[[str], None] | None = None, ) → Iterator[None][source]

Context Manager which lazy loads packages.

Their import is not executed immediately, but is postponed to the first call of one of their attributes.

Limitation:

You can only lazy load modules (from x import y will not work if y is a constant or a function or a class).

Usage:

with epy.lazy_imports():
  import tensorflow as tf

with epy.lazy_imports(success_callback=check_tf_version):
  import tensorflow as tf

When using type annotations, make sure to also use from __future__ import annotations, otherwise the lazy-import will be triggered at import time when used in typing annotations:

```pthon with epy.lazy_imports():

import tensorflow as tf

# !!! Resolve the lazy-import when __future__.annotations isn’t present def get_dataset() -> tf.data.Dataset: .. code-block:

This support `ecolab.adhoc` imports: When the lazy-import is resolved,
the original `ecolab.adhoc` context is re-created to import the lazy module.

:param error_callback: A additional message to append to the `ImportError` if the
                       import fails. Can also be a `Callable[[Exception], None]`. The exception
                       is passed as an arg, so user can use `epy.reraise(e, 'Additional
                       message')`.
:param success_callback: a callback to trigger when an import succeeds. The
                         callback is passed the name of the imported module as an arg.

:Yields: None