Source code for airflow.providers.google.cloud.links.mlengine

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"""This module contains Google ML Engine links."""
from __future__ import annotations

from typing import TYPE_CHECKING

from airflow.providers.google.cloud.links.base import BaseGoogleLink

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]MLENGINE_BASE_LINK = "https://console.cloud.google.com/ai-platform"
[docs]MLENGINE_MODEL_DETAILS_LINK = MLENGINE_BASE_LINK + "/models/{model_id}/versions?project={project_id}"
[docs]MLENGINE_MODEL_VERSION_DETAILS_LINK = (
    MLENGINE_BASE_LINK + "/models/{model_id}/versions/{version_id}/performance?project={project_id}"
)
[docs]MLENGINE_MODELS_LIST_LINK = MLENGINE_BASE_LINK + "/models/?project={project_id}"
[docs]MLENGINE_JOB_DETAILS_LINK = MLENGINE_BASE_LINK + "/jobs/{job_id}?project={project_id}"
[docs]MLENGINE_JOBS_LIST_LINK = MLENGINE_BASE_LINK + "/jobs?project={project_id}"


[docs]class MLEngineModelLink(BaseGoogleLink):
    """Helper class for constructing ML Engine link"""

[docs]    name = "MLEngine Model"
[docs]    key = "ml_engine_model"
[docs]    format_str = MLENGINE_MODEL_DETAILS_LINK

    @staticmethod
[docs]    def persist(
        context: Context,
        task_instance,
        model_id: str,
        project_id: str,
    ):
        task_instance.xcom_push(
            context,
            key=MLEngineModelLink.key,
            value={"model_id": model_id, "project_id": project_id},
        )


[docs]class MLEngineModelsListLink(BaseGoogleLink):
    """Helper class for constructing ML Engine link"""

[docs]    name = "MLEngine Models List"
[docs]    key = "ml_engine_models_list"
[docs]    format_str = MLENGINE_MODELS_LIST_LINK

    @staticmethod
[docs]    def persist(
        context: Context,
        task_instance,
        project_id: str,
    ):
        task_instance.xcom_push(
            context,
            key=MLEngineModelsListLink.key,
            value={"project_id": project_id},
        )


[docs]class MLEngineJobDetailsLink(BaseGoogleLink):
    """Helper class for constructing ML Engine link"""

[docs]    name = "MLEngine Job Details"
[docs]    key = "ml_engine_job_details"
[docs]    format_str = MLENGINE_JOB_DETAILS_LINK

    @staticmethod
[docs]    def persist(
        context: Context,
        task_instance,
        job_id: str,
        project_id: str,
    ):
        task_instance.xcom_push(
            context,
            key=MLEngineJobDetailsLink.key,
            value={"job_id": job_id, "project_id": project_id},
        )


[docs]class MLEngineModelVersionDetailsLink(BaseGoogleLink):
    """Helper class for constructing ML Engine link"""

[docs]    name = "MLEngine Version Details"
[docs]    key = "ml_engine_version_details"
[docs]    format_str = MLENGINE_MODEL_VERSION_DETAILS_LINK

    @staticmethod
[docs]    def persist(
        context: Context,
        task_instance,
        model_id: str,
        project_id: str,
        version_id: str,
    ):
        task_instance.xcom_push(
            context,
            key=MLEngineModelVersionDetailsLink.key,
            value={"model_id": model_id, "project_id": project_id, "version_id": version_id},
        )


[docs]class MLEngineJobSListLink(BaseGoogleLink):
    """Helper class for constructing ML Engine link"""

[docs]    name = "MLEngine Jobs List"
[docs]    key = "ml_engine_jobs_list"
[docs]    format_str = MLENGINE_JOBS_LIST_LINK

    @staticmethod
[docs]    def persist(
        context: Context,
        task_instance,
        project_id: str,
    ):
        task_instance.xcom_push(
            context,
            key=MLEngineJobSListLink.key,
            value={"project_id": project_id},
        )