__init__.py

# SPDX-License-Identifier: LGPL-3.0-or-later
"""DeePMD-kit is a package written in Python/C++, designed to
minimize the effort required to build deep learning-based model
of interatomic potential energy and force field and to perform
molecular dynamics (MD).

The top module (deepmd.__init__) should not import any third-party
modules for performance.
"""

from typing import (
    TYPE_CHECKING,
    Any,
)

if TYPE_CHECKING:
    from deepmd.infer import DeepPotential as DeepPotentialType
    from deepmd.property import (
        PropertyPredictor,
        PropertyTrainer,
    )

try:
    from deepmd._version import version as __version__
except ImportError:
    from .__about__ import (
        __version__,
    )


def DeepPotential(*args: Any, **kwargs: Any) -> "DeepPotentialType":
    """Factory function that forwards to DeepEval (for compatibility
    and performance).

    Parameters
    ----------
    *args
        positional arguments
    **kwargs
        keyword arguments

    Returns
    -------
    DeepEval
        potentials
    """
    from deepmd.infer import (
        DeepPotential,
    )

    return DeepPotential(*args, **kwargs)


def __getattr__(name: str) -> Any:
    """Lazily expose optional high-level helpers.

    The top-level module should avoid importing third-party-heavy modules at
    import time for performance. Keep these exports lazy.
    """
    if name in {"PropertyPredictor", "PropertyTrainer"}:
        from .property import (
            PropertyPredictor,
            PropertyTrainer,
        )

        return {
            "PropertyPredictor": PropertyPredictor,
            "PropertyTrainer": PropertyTrainer,
        }[name]
    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")


__all__ = [
    "DeepPotential",
    "PropertyPredictor",
    "PropertyTrainer",
    "__version__",
]