# -*- coding: utf-8 -*-
# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from collections import OrderedDict
import os
import re
from typing import (
    Dict,
    Callable,
    Mapping,
    MutableMapping,
    MutableSequence,
    Optional,
    Sequence,
    Tuple,
    Type,
    Union,
    cast,
)
import warnings

from google.cloud.aiplatform_v1beta1 import gapic_version as package_version

from google.api_core import client_options as client_options_lib
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry as retries
from google.auth import credentials as ga_credentials  # type: ignore
from google.auth.transport import mtls  # type: ignore
from google.auth.transport.grpc import SslCredentials  # type: ignore
from google.auth.exceptions import MutualTLSChannelError  # type: ignore
from google.oauth2 import service_account  # type: ignore

try:
    OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault, None]
except AttributeError:  # pragma: NO COVER
    OptionalRetry = Union[retries.Retry, object, None]  # type: ignore

from google.api_core import operation as gac_operation  # type: ignore
from google.api_core import operation_async  # type: ignore
from google.cloud.aiplatform_v1beta1.services.metadata_service import pagers
from google.cloud.aiplatform_v1beta1.types import artifact
from google.cloud.aiplatform_v1beta1.types import artifact as gca_artifact
from google.cloud.aiplatform_v1beta1.types import context
from google.cloud.aiplatform_v1beta1.types import context as gca_context
from google.cloud.aiplatform_v1beta1.types import encryption_spec
from google.cloud.aiplatform_v1beta1.types import event
from google.cloud.aiplatform_v1beta1.types import execution
from google.cloud.aiplatform_v1beta1.types import execution as gca_execution
from google.cloud.aiplatform_v1beta1.types import lineage_subgraph
from google.cloud.aiplatform_v1beta1.types import metadata_schema
from google.cloud.aiplatform_v1beta1.types import metadata_schema as gca_metadata_schema
from google.cloud.aiplatform_v1beta1.types import metadata_service
from google.cloud.aiplatform_v1beta1.types import metadata_store
from google.cloud.aiplatform_v1beta1.types import metadata_store as gca_metadata_store
from google.cloud.aiplatform_v1beta1.types import operation as gca_operation
from google.cloud.location import locations_pb2  # type: ignore
from google.iam.v1 import iam_policy_pb2  # type: ignore
from google.iam.v1 import policy_pb2  # type: ignore
from google.longrunning import operations_pb2  # type: ignore
from google.protobuf import empty_pb2  # type: ignore
from google.protobuf import field_mask_pb2  # type: ignore
from google.protobuf import struct_pb2  # type: ignore
from google.protobuf import timestamp_pb2  # type: ignore
from .transports.base import MetadataServiceTransport, DEFAULT_CLIENT_INFO
from .transports.grpc import MetadataServiceGrpcTransport
from .transports.grpc_asyncio import MetadataServiceGrpcAsyncIOTransport
from .transports.rest import MetadataServiceRestTransport

try:
    from .transports.rest_asyncio import AsyncMetadataServiceRestTransport

    HAS_ASYNC_REST_DEPENDENCIES = True
except ImportError as e:  # pragma: NO COVER
    HAS_ASYNC_REST_DEPENDENCIES = False
    ASYNC_REST_EXCEPTION = e


class MetadataServiceClientMeta(type):
    """Metaclass for the MetadataService client.

    This provides class-level methods for building and retrieving
    support objects (e.g. transport) without polluting the client instance
    objects.
    """

    _transport_registry = (
        OrderedDict()
    )  # type: Dict[str, Type[MetadataServiceTransport]]
    _transport_registry["grpc"] = MetadataServiceGrpcTransport
    _transport_registry["grpc_asyncio"] = MetadataServiceGrpcAsyncIOTransport
    _transport_registry["rest"] = MetadataServiceRestTransport
    if HAS_ASYNC_REST_DEPENDENCIES:  # pragma: NO COVER
        _transport_registry["rest_asyncio"] = AsyncMetadataServiceRestTransport

    def get_transport_class(
        cls,
        label: Optional[str] = None,
    ) -> Type[MetadataServiceTransport]:
        """Returns an appropriate transport class.

        Args:
            label: The name of the desired transport. If none is
                provided, then the first transport in the registry is used.

        Returns:
            The transport class to use.
        """
        # If a specific transport is requested, return that one.
        if (
            label == "rest_asyncio" and not HAS_ASYNC_REST_DEPENDENCIES
        ):  # pragma: NO COVER
            raise ASYNC_REST_EXCEPTION
        if label:
            return cls._transport_registry[label]

        # No transport is requested; return the default (that is, the first one
        # in the dictionary).
        return next(iter(cls._transport_registry.values()))


class MetadataServiceClient(metaclass=MetadataServiceClientMeta):
    """Service for reading and writing metadata entries."""

    @staticmethod
    def _get_default_mtls_endpoint(api_endpoint):
        """Converts api endpoint to mTLS endpoint.

        Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to
        "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively.
        Args:
            api_endpoint (Optional[str]): the api endpoint to convert.
        Returns:
            str: converted mTLS api endpoint.
        """
        if not api_endpoint:
            return api_endpoint

        mtls_endpoint_re = re.compile(
            r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?"
        )

        m = mtls_endpoint_re.match(api_endpoint)
        name, mtls, sandbox, googledomain = m.groups()
        if mtls or not googledomain:
            return api_endpoint

        if sandbox:
            return api_endpoint.replace(
                "sandbox.googleapis.com", "mtls.sandbox.googleapis.com"
            )

        return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com")

    # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
    DEFAULT_ENDPOINT = "aiplatform.googleapis.com"
    DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__(  # type: ignore
        DEFAULT_ENDPOINT
    )

    _DEFAULT_ENDPOINT_TEMPLATE = "aiplatform.{UNIVERSE_DOMAIN}"
    _DEFAULT_UNIVERSE = "googleapis.com"

    @classmethod
    def from_service_account_info(cls, info: dict, *args, **kwargs):
        """Creates an instance of this client using the provided credentials
            info.

        Args:
            info (dict): The service account private key info.
            args: Additional arguments to pass to the constructor.
            kwargs: Additional arguments to pass to the constructor.

        Returns:
            MetadataServiceClient: The constructed client.
        """
        credentials = service_account.Credentials.from_service_account_info(info)
        kwargs["credentials"] = credentials
        return cls(*args, **kwargs)

    @classmethod
    def from_service_account_file(cls, filename: str, *args, **kwargs):
        """Creates an instance of this client using the provided credentials
            file.

        Args:
            filename (str): The path to the service account private key json
                file.
            args: Additional arguments to pass to the constructor.
            kwargs: Additional arguments to pass to the constructor.

        Returns:
            MetadataServiceClient: The constructed client.
        """
        credentials = service_account.Credentials.from_service_account_file(filename)
        kwargs["credentials"] = credentials
        return cls(*args, **kwargs)

    from_service_account_json = from_service_account_file

    @property
    def transport(self) -> MetadataServiceTransport:
        """Returns the transport used by the client instance.

        Returns:
            MetadataServiceTransport: The transport used by the client
                instance.
        """
        return self._transport

    @staticmethod
    def artifact_path(
        project: str,
        location: str,
        metadata_store: str,
        artifact: str,
    ) -> str:
        """Returns a fully-qualified artifact string."""
        return "projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}".format(
            project=project,
            location=location,
            metadata_store=metadata_store,
            artifact=artifact,
        )

    @staticmethod
    def parse_artifact_path(path: str) -> Dict[str, str]:
        """Parses a artifact path into its component segments."""
        m = re.match(
            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/metadataStores/(?P<metadata_store>.+?)/artifacts/(?P<artifact>.+?)$",
            path,
        )
        return m.groupdict() if m else {}

    @staticmethod
    def context_path(
        project: str,
        location: str,
        metadata_store: str,
        context: str,
    ) -> str:
        """Returns a fully-qualified context string."""
        return "projects/{project}/locations/{location}/metadataStores/{metadata_store}/contexts/{context}".format(
            project=project,
            location=location,
            metadata_store=metadata_store,
            context=context,
        )

    @staticmethod
    def parse_context_path(path: str) -> Dict[str, str]:
        """Parses a context path into its component segments."""
        m = re.match(
            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/metadataStores/(?P<metadata_store>.+?)/contexts/(?P<context>.+?)$",
            path,
        )
        return m.groupdict() if m else {}

    @staticmethod
    def execution_path(
        project: str,
        location: str,
        metadata_store: str,
        execution: str,
    ) -> str:
        """Returns a fully-qualified execution string."""
        return "projects/{project}/locations/{location}/metadataStores/{metadata_store}/executions/{execution}".format(
            project=project,
            location=location,
            metadata_store=metadata_store,
            execution=execution,
        )

    @staticmethod
    def parse_execution_path(path: str) -> Dict[str, str]:
        """Parses a execution path into its component segments."""
        m = re.match(
            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/metadataStores/(?P<metadata_store>.+?)/executions/(?P<execution>.+?)$",
            path,
        )
        return m.groupdict() if m else {}

    @staticmethod
    def metadata_schema_path(
        project: str,
        location: str,
        metadata_store: str,
        metadata_schema: str,
    ) -> str:
        """Returns a fully-qualified metadata_schema string."""
        return "projects/{project}/locations/{location}/metadataStores/{metadata_store}/metadataSchemas/{metadata_schema}".format(
            project=project,
            location=location,
            metadata_store=metadata_store,
            metadata_schema=metadata_schema,
        )

    @staticmethod
    def parse_metadata_schema_path(path: str) -> Dict[str, str]:
        """Parses a metadata_schema path into its component segments."""
        m = re.match(
            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/metadataStores/(?P<metadata_store>.+?)/metadataSchemas/(?P<metadata_schema>.+?)$",
            path,
        )
        return m.groupdict() if m else {}

    @staticmethod
    def metadata_store_path(
        project: str,
        location: str,
        metadata_store: str,
    ) -> str:
        """Returns a fully-qualified metadata_store string."""
        return "projects/{project}/locations/{location}/metadataStores/{metadata_store}".format(
            project=project,
            location=location,
            metadata_store=metadata_store,
        )

    @staticmethod
    def parse_metadata_store_path(path: str) -> Dict[str, str]:
        """Parses a metadata_store path into its component segments."""
        m = re.match(
            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/metadataStores/(?P<metadata_store>.+?)$",
            path,
        )
        return m.groupdict() if m else {}

    @staticmethod
    def common_billing_account_path(
        billing_account: str,
    ) -> str:
        """Returns a fully-qualified billing_account string."""
        return "billingAccounts/{billing_account}".format(
            billing_account=billing_account,
        )

    @staticmethod
    def parse_common_billing_account_path(path: str) -> Dict[str, str]:
        """Parse a billing_account path into its component segments."""
        m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
        return m.groupdict() if m else {}

    @staticmethod
    def common_folder_path(
        folder: str,
    ) -> str:
        """Returns a fully-qualified folder string."""
        return "folders/{folder}".format(
            folder=folder,
        )

    @staticmethod
    def parse_common_folder_path(path: str) -> Dict[str, str]:
        """Parse a folder path into its component segments."""
        m = re.match(r"^folders/(?P<folder>.+?)$", path)
        return m.groupdict() if m else {}

    @staticmethod
    def common_organization_path(
        organization: str,
    ) -> str:
        """Returns a fully-qualified organization string."""
        return "organizations/{organization}".format(
            organization=organization,
        )

    @staticmethod
    def parse_common_organization_path(path: str) -> Dict[str, str]:
        """Parse a organization path into its component segments."""
        m = re.match(r"^organizations/(?P<organization>.+?)$", path)
        return m.groupdict() if m else {}

    @staticmethod
    def common_project_path(
        project: str,
    ) -> str:
        """Returns a fully-qualified project string."""
        return "projects/{project}".format(
            project=project,
        )

    @staticmethod
    def parse_common_project_path(path: str) -> Dict[str, str]:
        """Parse a project path into its component segments."""
        m = re.match(r"^projects/(?P<project>.+?)$", path)
        return m.groupdict() if m else {}

    @staticmethod
    def common_location_path(
        project: str,
        location: str,
    ) -> str:
        """Returns a fully-qualified location string."""
        return "projects/{project}/locations/{location}".format(
            project=project,
            location=location,
        )

    @staticmethod
    def parse_common_location_path(path: str) -> Dict[str, str]:
        """Parse a location path into its component segments."""
        m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path)
        return m.groupdict() if m else {}

    @classmethod
    def get_mtls_endpoint_and_cert_source(
        cls, client_options: Optional[client_options_lib.ClientOptions] = None
    ):
        """Deprecated. Return the API endpoint and client cert source for mutual TLS.

        The client cert source is determined in the following order:
        (1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
        client cert source is None.
        (2) if `client_options.client_cert_source` is provided, use the provided one; if the
        default client cert source exists, use the default one; otherwise the client cert
        source is None.

        The API endpoint is determined in the following order:
        (1) if `client_options.api_endpoint` if provided, use the provided one.
        (2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
        default mTLS endpoint; if the environment variable is "never", use the default API
        endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
        use the default API endpoint.

        More details can be found at https://google.aip.dev/auth/4114.

        Args:
            client_options (google.api_core.client_options.ClientOptions): Custom options for the
                client. Only the `api_endpoint` and `client_cert_source` properties may be used
                in this method.

        Returns:
            Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
                client cert source to use.

        Raises:
            google.auth.exceptions.MutualTLSChannelError: If any errors happen.
        """

        warnings.warn(
            "get_mtls_endpoint_and_cert_source is deprecated. Use the api_endpoint property instead.",
            DeprecationWarning,
        )
        if client_options is None:
            client_options = client_options_lib.ClientOptions()
        use_client_cert = os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")
        use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto")
        if use_client_cert not in ("true", "false"):
            raise ValueError(
                "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
            )
        if use_mtls_endpoint not in ("auto", "never", "always"):
            raise MutualTLSChannelError(
                "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
            )

        # Figure out the client cert source to use.
        client_cert_source = None
        if use_client_cert == "true":
            if client_options.client_cert_source:
                client_cert_source = client_options.client_cert_source
            elif mtls.has_default_client_cert_source():
                client_cert_source = mtls.default_client_cert_source()

        # Figure out which api endpoint to use.
        if client_options.api_endpoint is not None:
            api_endpoint = client_options.api_endpoint
        elif use_mtls_endpoint == "always" or (
            use_mtls_endpoint == "auto" and client_cert_source
        ):
            api_endpoint = cls.DEFAULT_MTLS_ENDPOINT
        else:
            api_endpoint = cls.DEFAULT_ENDPOINT

        return api_endpoint, client_cert_source

    @staticmethod
    def _read_environment_variables():
        """Returns the environment variables used by the client.

        Returns:
            Tuple[bool, str, str]: returns the GOOGLE_API_USE_CLIENT_CERTIFICATE,
            GOOGLE_API_USE_MTLS_ENDPOINT, and GOOGLE_CLOUD_UNIVERSE_DOMAIN environment variables.

        Raises:
            ValueError: If GOOGLE_API_USE_CLIENT_CERTIFICATE is not
                any of ["true", "false"].
            google.auth.exceptions.MutualTLSChannelError: If GOOGLE_API_USE_MTLS_ENDPOINT
                is not any of ["auto", "never", "always"].
        """
        use_client_cert = os.getenv(
            "GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"
        ).lower()
        use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto").lower()
        universe_domain_env = os.getenv("GOOGLE_CLOUD_UNIVERSE_DOMAIN")
        if use_client_cert not in ("true", "false"):
            raise ValueError(
                "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
            )
        if use_mtls_endpoint not in ("auto", "never", "always"):
            raise MutualTLSChannelError(
                "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
            )
        return use_client_cert == "true", use_mtls_endpoint, universe_domain_env

    @staticmethod
    def _get_client_cert_source(provided_cert_source, use_cert_flag):
        """Return the client cert source to be used by the client.

        Args:
            provided_cert_source (bytes): The client certificate source provided.
            use_cert_flag (bool): A flag indicating whether to use the client certificate.

        Returns:
            bytes or None: The client cert source to be used by the client.
        """
        client_cert_source = None
        if use_cert_flag:
            if provided_cert_source:
                client_cert_source = provided_cert_source
            elif mtls.has_default_client_cert_source():
                client_cert_source = mtls.default_client_cert_source()
        return client_cert_source

    @staticmethod
    def _get_api_endpoint(
        api_override, client_cert_source, universe_domain, use_mtls_endpoint
    ):
        """Return the API endpoint used by the client.

        Args:
            api_override (str): The API endpoint override. If specified, this is always
                the return value of this function and the other arguments are not used.
            client_cert_source (bytes): The client certificate source used by the client.
            universe_domain (str): The universe domain used by the client.
            use_mtls_endpoint (str): How to use the mTLS endpoint, which depends also on the other parameters.
                Possible values are "always", "auto", or "never".

        Returns:
            str: The API endpoint to be used by the client.
        """
        if api_override is not None:
            api_endpoint = api_override
        elif use_mtls_endpoint == "always" or (
            use_mtls_endpoint == "auto" and client_cert_source
        ):
            _default_universe = MetadataServiceClient._DEFAULT_UNIVERSE
            if universe_domain != _default_universe:
                raise MutualTLSChannelError(
                    f"mTLS is not supported in any universe other than {_default_universe}."
                )
            api_endpoint = MetadataServiceClient.DEFAULT_MTLS_ENDPOINT
        else:
            api_endpoint = MetadataServiceClient._DEFAULT_ENDPOINT_TEMPLATE.format(
                UNIVERSE_DOMAIN=universe_domain
            )
        return api_endpoint

    @staticmethod
    def _get_universe_domain(
        client_universe_domain: Optional[str], universe_domain_env: Optional[str]
    ) -> str:
        """Return the universe domain used by the client.

        Args:
            client_universe_domain (Optional[str]): The universe domain configured via the client options.
            universe_domain_env (Optional[str]): The universe domain configured via the "GOOGLE_CLOUD_UNIVERSE_DOMAIN" environment variable.

        Returns:
            str: The universe domain to be used by the client.

        Raises:
            ValueError: If the universe domain is an empty string.
        """
        universe_domain = MetadataServiceClient._DEFAULT_UNIVERSE
        if client_universe_domain is not None:
            universe_domain = client_universe_domain
        elif universe_domain_env is not None:
            universe_domain = universe_domain_env
        if len(universe_domain.strip()) == 0:
            raise ValueError("Universe Domain cannot be an empty string.")
        return universe_domain

    @staticmethod
    def _compare_universes(
        client_universe: str, credentials: ga_credentials.Credentials
    ) -> bool:
        """Returns True iff the universe domains used by the client and credentials match.

        Args:
            client_universe (str): The universe domain configured via the client options.
            credentials (ga_credentials.Credentials): The credentials being used in the client.

        Returns:
            bool: True iff client_universe matches the universe in credentials.

        Raises:
            ValueError: when client_universe does not match the universe in credentials.
        """

        default_universe = MetadataServiceClient._DEFAULT_UNIVERSE
        credentials_universe = getattr(credentials, "universe_domain", default_universe)

        if client_universe != credentials_universe:
            raise ValueError(
                "The configured universe domain "
                f"({client_universe}) does not match the universe domain "
                f"found in the credentials ({credentials_universe}). "
                "If you haven't configured the universe domain explicitly, "
                f"`{default_universe}` is the default."
            )
        return True

    def _validate_universe_domain(self):
        """Validates client's and credentials' universe domains are consistent.

        Returns:
            bool: True iff the configured universe domain is valid.

        Raises:
            ValueError: If the configured universe domain is not valid.
        """
        self._is_universe_domain_valid = (
            self._is_universe_domain_valid
            or MetadataServiceClient._compare_universes(
                self.universe_domain, self.transport._credentials
            )
        )
        return self._is_universe_domain_valid

    @property
    def api_endpoint(self):
        """Return the API endpoint used by the client instance.

        Returns:
            str: The API endpoint used by the client instance.
        """
        return self._api_endpoint

    @property
    def universe_domain(self) -> str:
        """Return the universe domain used by the client instance.

        Returns:
            str: The universe domain used by the client instance.
        """
        return self._universe_domain

    def __init__(
        self,
        *,
        credentials: Optional[ga_credentials.Credentials] = None,
        transport: Optional[
            Union[
                str, MetadataServiceTransport, Callable[..., MetadataServiceTransport]
            ]
        ] = None,
        client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None,
        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
    ) -> None:
        """Instantiates the metadata service client.

        Args:
            credentials (Optional[google.auth.credentials.Credentials]): The
                authorization credentials to attach to requests. These
                credentials identify the application to the service; if none
                are specified, the client will attempt to ascertain the
                credentials from the environment.
            transport (Optional[Union[str,MetadataServiceTransport,Callable[..., MetadataServiceTransport]]]):
                The transport to use, or a Callable that constructs and returns a new transport.
                If a Callable is given, it will be called with the same set of initialization
                arguments as used in the MetadataServiceTransport constructor.
                If set to None, a transport is chosen automatically.
            client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]):
                Custom options for the client.

                1. The ``api_endpoint`` property can be used to override the
                default endpoint provided by the client when ``transport`` is
                not explicitly provided. Only if this property is not set and
                ``transport`` was not explicitly provided, the endpoint is
                determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment
                variable, which have one of the following values:
                "always" (always use the default mTLS endpoint), "never" (always
                use the default regular endpoint) and "auto" (auto-switch to the
                default mTLS endpoint if client certificate is present; this is
                the default value).

                2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
                is "true", then the ``client_cert_source`` property can be used
                to provide a client certificate for mTLS transport. If
                not provided, the default SSL client certificate will be used if
                present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
                set, no client certificate will be used.

                3. The ``universe_domain`` property can be used to override the
                default "googleapis.com" universe. Note that the ``api_endpoint``
                property still takes precedence; and ``universe_domain`` is
                currently not supported for mTLS.

            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
                The client info used to send a user-agent string along with
                API requests. If ``None``, then default info will be used.
                Generally, you only need to set this if you're developing
                your own client library.

        Raises:
            google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
                creation failed for any reason.
        """
        self._client_options = client_options
        if isinstance(self._client_options, dict):
            self._client_options = client_options_lib.from_dict(self._client_options)
        if self._client_options is None:
            self._client_options = client_options_lib.ClientOptions()
        self._client_options = cast(
            client_options_lib.ClientOptions, self._client_options
        )

        universe_domain_opt = getattr(self._client_options, "universe_domain", None)

        (
            self._use_client_cert,
            self._use_mtls_endpoint,
            self._universe_domain_env,
        ) = MetadataServiceClient._read_environment_variables()
        self._client_cert_source = MetadataServiceClient._get_client_cert_source(
            self._client_options.client_cert_source, self._use_client_cert
        )
        self._universe_domain = MetadataServiceClient._get_universe_domain(
            universe_domain_opt, self._universe_domain_env
        )
        self._api_endpoint = None  # updated below, depending on `transport`

        # Initialize the universe domain validation.
        self._is_universe_domain_valid = False

        api_key_value = getattr(self._client_options, "api_key", None)
        if api_key_value and credentials:
            raise ValueError(
                "client_options.api_key and credentials are mutually exclusive"
            )

        # Save or instantiate the transport.
        # Ordinarily, we provide the transport, but allowing a custom transport
        # instance provides an extensibility point for unusual situations.
        transport_provided = isinstance(transport, MetadataServiceTransport)
        if transport_provided:
            # transport is a MetadataServiceTransport instance.
            if credentials or self._client_options.credentials_file or api_key_value:
                raise ValueError(
                    "When providing a transport instance, "
                    "provide its credentials directly."
                )
            if self._client_options.scopes:
                raise ValueError(
                    "When providing a transport instance, provide its scopes "
                    "directly."
                )
            self._transport = cast(MetadataServiceTransport, transport)
            self._api_endpoint = self._transport.host

        self._api_endpoint = (
            self._api_endpoint
            or MetadataServiceClient._get_api_endpoint(
                self._client_options.api_endpoint,
                self._client_cert_source,
                self._universe_domain,
                self._use_mtls_endpoint,
            )
        )

        if not transport_provided:
            transport_init: Union[
                Type[MetadataServiceTransport], Callable[..., MetadataServiceTransport]
            ] = (
                MetadataServiceClient.get_transport_class(transport)
                if isinstance(transport, str) or transport is None
                else cast(Callable[..., MetadataServiceTransport], transport)
            )

            if "rest_asyncio" in str(transport_init):
                unsupported_params = {
                    "google.api_core.client_options.ClientOptions.credentials_file": self._client_options.credentials_file,
                    "google.api_core.client_options.ClientOptions.scopes": self._client_options.scopes,
                    "google.api_core.client_options.ClientOptions.quota_project_id": self._client_options.quota_project_id,
                    "google.api_core.client_options.ClientOptions.client_cert_source": self._client_options.client_cert_source,
                    "google.api_core.client_options.ClientOptions.api_audience": self._client_options.api_audience,
                }
                provided_unsupported_params = [
                    name
                    for name, value in unsupported_params.items()
                    if value is not None
                ]
                if provided_unsupported_params:
                    raise core_exceptions.AsyncRestUnsupportedParameterError(  # type: ignore
                        f"The following provided parameters are not supported for `transport=rest_asyncio`: {', '.join(provided_unsupported_params)}"
                    )
                self._transport = transport_init(
                    credentials=credentials,
                    host=self._api_endpoint,
                    client_info=client_info,
                )
                return

            import google.auth._default  # type: ignore

            if api_key_value and hasattr(
                google.auth._default, "get_api_key_credentials"
            ):
                credentials = google.auth._default.get_api_key_credentials(
                    api_key_value
                )

            # initialize with the provided callable or the passed in class
            self._transport = transport_init(
                credentials=credentials,
                credentials_file=self._client_options.credentials_file,
                host=self._api_endpoint,
                scopes=self._client_options.scopes,
                client_cert_source_for_mtls=self._client_cert_source,
                quota_project_id=self._client_options.quota_project_id,
                client_info=client_info,
                always_use_jwt_access=True,
                api_audience=self._client_options.api_audience,
            )

    def create_metadata_store(
        self,
        request: Optional[
            Union[metadata_service.CreateMetadataStoreRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        metadata_store: Optional[gca_metadata_store.MetadataStore] = None,
        metadata_store_id: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Initializes a MetadataStore, including allocation of
        resources.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_create_metadata_store():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CreateMetadataStoreRequest(
                    parent="parent_value",
                )

                # Make the request
                operation = client.create_metadata_store(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.CreateMetadataStoreRequest, dict]):
                The request object. Request message for
                [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.CreateMetadataStore].
            parent (str):
                Required. The resource name of the Location where the
                MetadataStore should be created. Format:
                ``projects/{project}/locations/{location}/``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            metadata_store (google.cloud.aiplatform_v1beta1.types.MetadataStore):
                Required. The MetadataStore to
                create.

                This corresponds to the ``metadata_store`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            metadata_store_id (str):
                The {metadatastore} portion of the resource name with
                the format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``
                If not provided, the MetadataStore's ID will be a UUID
                generated by the service. Must be 4-128 characters in
                length. Valid characters are ``/[a-z][0-9]-/``. Must be
                unique across all MetadataStores in the parent Location.
                (Otherwise the request will fail with ALREADY_EXISTS, or
                PERMISSION_DENIED if the caller can't view the
                preexisting MetadataStore.)

                This corresponds to the ``metadata_store_id`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.MetadataStore` Instance of a metadata store. Contains a set of metadata that can be
                   queried.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent, metadata_store, metadata_store_id])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.CreateMetadataStoreRequest):
            request = metadata_service.CreateMetadataStoreRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent
            if metadata_store is not None:
                request.metadata_store = metadata_store
            if metadata_store_id is not None:
                request.metadata_store_id = metadata_store_id

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.create_metadata_store]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            gca_metadata_store.MetadataStore,
            metadata_type=metadata_service.CreateMetadataStoreOperationMetadata,
        )

        # Done; return the response.
        return response

    def get_metadata_store(
        self,
        request: Optional[Union[metadata_service.GetMetadataStoreRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> metadata_store.MetadataStore:
        r"""Retrieves a specific MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_get_metadata_store():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetMetadataStoreRequest(
                    name="name_value",
                )

                # Make the request
                response = client.get_metadata_store(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.GetMetadataStoreRequest, dict]):
                The request object. Request message for
                [MetadataService.GetMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.GetMetadataStore].
            name (str):
                Required. The resource name of the MetadataStore to
                retrieve. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.MetadataStore:
                Instance of a metadata store.
                Contains a set of metadata that can be
                queried.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.GetMetadataStoreRequest):
            request = metadata_service.GetMetadataStoreRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_metadata_store]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def list_metadata_stores(
        self,
        request: Optional[
            Union[metadata_service.ListMetadataStoresRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> pagers.ListMetadataStoresPager:
        r"""Lists MetadataStores for a Location.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_list_metadata_stores():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.ListMetadataStoresRequest(
                    parent="parent_value",
                )

                # Make the request
                page_result = client.list_metadata_stores(request=request)

                # Handle the response
                for response in page_result:
                    print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.ListMetadataStoresRequest, dict]):
                The request object. Request message for
                [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataStores].
            parent (str):
                Required. The Location whose MetadataStores should be
                listed. Format:
                ``projects/{project}/locations/{location}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.services.metadata_service.pagers.ListMetadataStoresPager:
                Response message for
                   [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataStores].

                Iterating over this object will yield results and
                resolve additional pages automatically.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.ListMetadataStoresRequest):
            request = metadata_service.ListMetadataStoresRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_metadata_stores]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__iter__` convenience method.
        response = pagers.ListMetadataStoresPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def delete_metadata_store(
        self,
        request: Optional[
            Union[metadata_service.DeleteMetadataStoreRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Deletes a single MetadataStore and all its child
        resources (Artifacts, Executions, and Contexts).

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_delete_metadata_store():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.DeleteMetadataStoreRequest(
                    name="name_value",
                )

                # Make the request
                operation = client.delete_metadata_store(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.DeleteMetadataStoreRequest, dict]):
                The request object. Request message for
                [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.DeleteMetadataStore].
            name (str):
                Required. The resource name of the MetadataStore to
                delete. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                   empty messages in your APIs. A typical example is to
                   use it as the request or the response type of an API
                   method. For instance:

                      service Foo {
                         rpc Bar(google.protobuf.Empty) returns
                         (google.protobuf.Empty);

                      }

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.DeleteMetadataStoreRequest):
            request = metadata_service.DeleteMetadataStoreRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.delete_metadata_store]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            empty_pb2.Empty,
            metadata_type=metadata_service.DeleteMetadataStoreOperationMetadata,
        )

        # Done; return the response.
        return response

    def create_artifact(
        self,
        request: Optional[Union[metadata_service.CreateArtifactRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        artifact: Optional[gca_artifact.Artifact] = None,
        artifact_id: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_artifact.Artifact:
        r"""Creates an Artifact associated with a MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_create_artifact():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CreateArtifactRequest(
                    parent="parent_value",
                )

                # Make the request
                response = client.create_artifact(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.CreateArtifactRequest, dict]):
                The request object. Request message for
                [MetadataService.CreateArtifact][google.cloud.aiplatform.v1beta1.MetadataService.CreateArtifact].
            parent (str):
                Required. The resource name of the MetadataStore where
                the Artifact should be created. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            artifact (google.cloud.aiplatform_v1beta1.types.Artifact):
                Required. The Artifact to create.
                This corresponds to the ``artifact`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            artifact_id (str):
                The {artifact} portion of the resource name with the
                format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}``
                If not provided, the Artifact's ID will be a UUID
                generated by the service. Must be 4-128 characters in
                length. Valid characters are ``/[a-z][0-9]-/``. Must be
                unique across all Artifacts in the parent MetadataStore.
                (Otherwise the request will fail with ALREADY_EXISTS, or
                PERMISSION_DENIED if the caller can't view the
                preexisting Artifact.)

                This corresponds to the ``artifact_id`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Artifact:
                Instance of a general artifact.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent, artifact, artifact_id])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.CreateArtifactRequest):
            request = metadata_service.CreateArtifactRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent
            if artifact is not None:
                request.artifact = artifact
            if artifact_id is not None:
                request.artifact_id = artifact_id

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.create_artifact]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_artifact(
        self,
        request: Optional[Union[metadata_service.GetArtifactRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> artifact.Artifact:
        r"""Retrieves a specific Artifact.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_get_artifact():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetArtifactRequest(
                    name="name_value",
                )

                # Make the request
                response = client.get_artifact(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.GetArtifactRequest, dict]):
                The request object. Request message for
                [MetadataService.GetArtifact][google.cloud.aiplatform.v1beta1.MetadataService.GetArtifact].
            name (str):
                Required. The resource name of the Artifact to retrieve.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Artifact:
                Instance of a general artifact.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.GetArtifactRequest):
            request = metadata_service.GetArtifactRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_artifact]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def list_artifacts(
        self,
        request: Optional[Union[metadata_service.ListArtifactsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> pagers.ListArtifactsPager:
        r"""Lists Artifacts in the MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_list_artifacts():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.ListArtifactsRequest(
                    parent="parent_value",
                )

                # Make the request
                page_result = client.list_artifacts(request=request)

                # Handle the response
                for response in page_result:
                    print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.ListArtifactsRequest, dict]):
                The request object. Request message for
                [MetadataService.ListArtifacts][google.cloud.aiplatform.v1beta1.MetadataService.ListArtifacts].
            parent (str):
                Required. The MetadataStore whose Artifacts should be
                listed. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.services.metadata_service.pagers.ListArtifactsPager:
                Response message for
                   [MetadataService.ListArtifacts][google.cloud.aiplatform.v1beta1.MetadataService.ListArtifacts].

                Iterating over this object will yield results and
                resolve additional pages automatically.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.ListArtifactsRequest):
            request = metadata_service.ListArtifactsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_artifacts]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__iter__` convenience method.
        response = pagers.ListArtifactsPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def update_artifact(
        self,
        request: Optional[Union[metadata_service.UpdateArtifactRequest, dict]] = None,
        *,
        artifact: Optional[gca_artifact.Artifact] = None,
        update_mask: Optional[field_mask_pb2.FieldMask] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_artifact.Artifact:
        r"""Updates a stored Artifact.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_update_artifact():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.UpdateArtifactRequest(
                )

                # Make the request
                response = client.update_artifact(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.UpdateArtifactRequest, dict]):
                The request object. Request message for
                [MetadataService.UpdateArtifact][google.cloud.aiplatform.v1beta1.MetadataService.UpdateArtifact].
            artifact (google.cloud.aiplatform_v1beta1.types.Artifact):
                Required. The Artifact containing updates. The
                Artifact's
                [Artifact.name][google.cloud.aiplatform.v1beta1.Artifact.name]
                field is used to identify the Artifact to be updated.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}``

                This corresponds to the ``artifact`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            update_mask (google.protobuf.field_mask_pb2.FieldMask):
                Optional. A FieldMask indicating
                which fields should be updated.

                This corresponds to the ``update_mask`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Artifact:
                Instance of a general artifact.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([artifact, update_mask])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.UpdateArtifactRequest):
            request = metadata_service.UpdateArtifactRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if artifact is not None:
                request.artifact = artifact
            if update_mask is not None:
                request.update_mask = update_mask

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.update_artifact]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata(
                (("artifact.name", request.artifact.name),)
            ),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def delete_artifact(
        self,
        request: Optional[Union[metadata_service.DeleteArtifactRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Deletes an Artifact.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_delete_artifact():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.DeleteArtifactRequest(
                    name="name_value",
                )

                # Make the request
                operation = client.delete_artifact(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.DeleteArtifactRequest, dict]):
                The request object. Request message for
                [MetadataService.DeleteArtifact][google.cloud.aiplatform.v1beta1.MetadataService.DeleteArtifact].
            name (str):
                Required. The resource name of the Artifact to delete.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                   empty messages in your APIs. A typical example is to
                   use it as the request or the response type of an API
                   method. For instance:

                      service Foo {
                         rpc Bar(google.protobuf.Empty) returns
                         (google.protobuf.Empty);

                      }

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.DeleteArtifactRequest):
            request = metadata_service.DeleteArtifactRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.delete_artifact]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            empty_pb2.Empty,
            metadata_type=gca_operation.DeleteOperationMetadata,
        )

        # Done; return the response.
        return response

    def purge_artifacts(
        self,
        request: Optional[Union[metadata_service.PurgeArtifactsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Purges Artifacts.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_purge_artifacts():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.PurgeArtifactsRequest(
                    parent="parent_value",
                    filter="filter_value",
                )

                # Make the request
                operation = client.purge_artifacts(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.PurgeArtifactsRequest, dict]):
                The request object. Request message for
                [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1beta1.MetadataService.PurgeArtifacts].
            parent (str):
                Required. The metadata store to purge Artifacts from.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.PurgeArtifactsResponse` Response message for
                   [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1beta1.MetadataService.PurgeArtifacts].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.PurgeArtifactsRequest):
            request = metadata_service.PurgeArtifactsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.purge_artifacts]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            metadata_service.PurgeArtifactsResponse,
            metadata_type=metadata_service.PurgeArtifactsMetadata,
        )

        # Done; return the response.
        return response

    def create_context(
        self,
        request: Optional[Union[metadata_service.CreateContextRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        context: Optional[gca_context.Context] = None,
        context_id: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_context.Context:
        r"""Creates a Context associated with a MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_create_context():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CreateContextRequest(
                    parent="parent_value",
                )

                # Make the request
                response = client.create_context(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.CreateContextRequest, dict]):
                The request object. Request message for
                [MetadataService.CreateContext][google.cloud.aiplatform.v1beta1.MetadataService.CreateContext].
            parent (str):
                Required. The resource name of the MetadataStore where
                the Context should be created. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            context (google.cloud.aiplatform_v1beta1.types.Context):
                Required. The Context to create.
                This corresponds to the ``context`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            context_id (str):
                The {context} portion of the resource name with the
                format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``.
                If not provided, the Context's ID will be a UUID
                generated by the service. Must be 4-128 characters in
                length. Valid characters are ``/[a-z][0-9]-/``. Must be
                unique across all Contexts in the parent MetadataStore.
                (Otherwise the request will fail with ALREADY_EXISTS, or
                PERMISSION_DENIED if the caller can't view the
                preexisting Context.)

                This corresponds to the ``context_id`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Context:
                Instance of a general context.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent, context, context_id])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.CreateContextRequest):
            request = metadata_service.CreateContextRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent
            if context is not None:
                request.context = context
            if context_id is not None:
                request.context_id = context_id

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.create_context]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_context(
        self,
        request: Optional[Union[metadata_service.GetContextRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> context.Context:
        r"""Retrieves a specific Context.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_get_context():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetContextRequest(
                    name="name_value",
                )

                # Make the request
                response = client.get_context(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.GetContextRequest, dict]):
                The request object. Request message for
                [MetadataService.GetContext][google.cloud.aiplatform.v1beta1.MetadataService.GetContext].
            name (str):
                Required. The resource name of the Context to retrieve.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Context:
                Instance of a general context.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.GetContextRequest):
            request = metadata_service.GetContextRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_context]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def list_contexts(
        self,
        request: Optional[Union[metadata_service.ListContextsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> pagers.ListContextsPager:
        r"""Lists Contexts on the MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_list_contexts():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.ListContextsRequest(
                    parent="parent_value",
                )

                # Make the request
                page_result = client.list_contexts(request=request)

                # Handle the response
                for response in page_result:
                    print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.ListContextsRequest, dict]):
                The request object. Request message for
                [MetadataService.ListContexts][google.cloud.aiplatform.v1beta1.MetadataService.ListContexts]
            parent (str):
                Required. The MetadataStore whose Contexts should be
                listed. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.services.metadata_service.pagers.ListContextsPager:
                Response message for
                   [MetadataService.ListContexts][google.cloud.aiplatform.v1beta1.MetadataService.ListContexts].

                Iterating over this object will yield results and
                resolve additional pages automatically.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.ListContextsRequest):
            request = metadata_service.ListContextsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_contexts]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__iter__` convenience method.
        response = pagers.ListContextsPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def update_context(
        self,
        request: Optional[Union[metadata_service.UpdateContextRequest, dict]] = None,
        *,
        context: Optional[gca_context.Context] = None,
        update_mask: Optional[field_mask_pb2.FieldMask] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_context.Context:
        r"""Updates a stored Context.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_update_context():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.UpdateContextRequest(
                )

                # Make the request
                response = client.update_context(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.UpdateContextRequest, dict]):
                The request object. Request message for
                [MetadataService.UpdateContext][google.cloud.aiplatform.v1beta1.MetadataService.UpdateContext].
            context (google.cloud.aiplatform_v1beta1.types.Context):
                Required. The Context containing updates. The Context's
                [Context.name][google.cloud.aiplatform.v1beta1.Context.name]
                field is used to identify the Context to be updated.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                This corresponds to the ``context`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            update_mask (google.protobuf.field_mask_pb2.FieldMask):
                Optional. A FieldMask indicating
                which fields should be updated.

                This corresponds to the ``update_mask`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Context:
                Instance of a general context.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([context, update_mask])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.UpdateContextRequest):
            request = metadata_service.UpdateContextRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if context is not None:
                request.context = context
            if update_mask is not None:
                request.update_mask = update_mask

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.update_context]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata(
                (("context.name", request.context.name),)
            ),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def delete_context(
        self,
        request: Optional[Union[metadata_service.DeleteContextRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Deletes a stored Context.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_delete_context():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.DeleteContextRequest(
                    name="name_value",
                )

                # Make the request
                operation = client.delete_context(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.DeleteContextRequest, dict]):
                The request object. Request message for
                [MetadataService.DeleteContext][google.cloud.aiplatform.v1beta1.MetadataService.DeleteContext].
            name (str):
                Required. The resource name of the Context to delete.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                   empty messages in your APIs. A typical example is to
                   use it as the request or the response type of an API
                   method. For instance:

                      service Foo {
                         rpc Bar(google.protobuf.Empty) returns
                         (google.protobuf.Empty);

                      }

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.DeleteContextRequest):
            request = metadata_service.DeleteContextRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.delete_context]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            empty_pb2.Empty,
            metadata_type=gca_operation.DeleteOperationMetadata,
        )

        # Done; return the response.
        return response

    def purge_contexts(
        self,
        request: Optional[Union[metadata_service.PurgeContextsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Purges Contexts.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_purge_contexts():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.PurgeContextsRequest(
                    parent="parent_value",
                    filter="filter_value",
                )

                # Make the request
                operation = client.purge_contexts(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.PurgeContextsRequest, dict]):
                The request object. Request message for
                [MetadataService.PurgeContexts][google.cloud.aiplatform.v1beta1.MetadataService.PurgeContexts].
            parent (str):
                Required. The metadata store to purge Contexts from.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.PurgeContextsResponse` Response message for
                   [MetadataService.PurgeContexts][google.cloud.aiplatform.v1beta1.MetadataService.PurgeContexts].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.PurgeContextsRequest):
            request = metadata_service.PurgeContextsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.purge_contexts]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            metadata_service.PurgeContextsResponse,
            metadata_type=metadata_service.PurgeContextsMetadata,
        )

        # Done; return the response.
        return response

    def add_context_artifacts_and_executions(
        self,
        request: Optional[
            Union[metadata_service.AddContextArtifactsAndExecutionsRequest, dict]
        ] = None,
        *,
        context: Optional[str] = None,
        artifacts: Optional[MutableSequence[str]] = None,
        executions: Optional[MutableSequence[str]] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> metadata_service.AddContextArtifactsAndExecutionsResponse:
        r"""Adds a set of Artifacts and Executions to a Context.
        If any of the Artifacts or Executions have already been
        added to a Context, they are simply skipped.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_add_context_artifacts_and_executions():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.AddContextArtifactsAndExecutionsRequest(
                    context="context_value",
                )

                # Make the request
                response = client.add_context_artifacts_and_executions(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.AddContextArtifactsAndExecutionsRequest, dict]):
                The request object. Request message for
                [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1beta1.MetadataService.AddContextArtifactsAndExecutions].
            context (str):
                Required. The resource name of the Context that the
                Artifacts and Executions belong to. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                This corresponds to the ``context`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            artifacts (MutableSequence[str]):
                The resource names of the Artifacts to attribute to the
                Context.

                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}``

                This corresponds to the ``artifacts`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            executions (MutableSequence[str]):
                The resource names of the Executions to associate with
                the Context.

                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``

                This corresponds to the ``executions`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.AddContextArtifactsAndExecutionsResponse:
                Response message for
                   [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1beta1.MetadataService.AddContextArtifactsAndExecutions].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([context, artifacts, executions])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(
            request, metadata_service.AddContextArtifactsAndExecutionsRequest
        ):
            request = metadata_service.AddContextArtifactsAndExecutionsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if context is not None:
                request.context = context
            if artifacts is not None:
                request.artifacts = artifacts
            if executions is not None:
                request.executions = executions

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[
            self._transport.add_context_artifacts_and_executions
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("context", request.context),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def add_context_children(
        self,
        request: Optional[
            Union[metadata_service.AddContextChildrenRequest, dict]
        ] = None,
        *,
        context: Optional[str] = None,
        child_contexts: Optional[MutableSequence[str]] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> metadata_service.AddContextChildrenResponse:
        r"""Adds a set of Contexts as children to a parent Context. If any
        of the child Contexts have already been added to the parent
        Context, they are simply skipped. If this call would create a
        cycle or cause any Context to have more than 10 parents, the
        request will fail with an INVALID_ARGUMENT error.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_add_context_children():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.AddContextChildrenRequest(
                    context="context_value",
                )

                # Make the request
                response = client.add_context_children(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.AddContextChildrenRequest, dict]):
                The request object. Request message for
                [MetadataService.AddContextChildren][google.cloud.aiplatform.v1beta1.MetadataService.AddContextChildren].
            context (str):
                Required. The resource name of the parent Context.

                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                This corresponds to the ``context`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            child_contexts (MutableSequence[str]):
                The resource names of the child
                Contexts.

                This corresponds to the ``child_contexts`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.AddContextChildrenResponse:
                Response message for
                   [MetadataService.AddContextChildren][google.cloud.aiplatform.v1beta1.MetadataService.AddContextChildren].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([context, child_contexts])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.AddContextChildrenRequest):
            request = metadata_service.AddContextChildrenRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if context is not None:
                request.context = context
            if child_contexts is not None:
                request.child_contexts = child_contexts

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.add_context_children]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("context", request.context),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def remove_context_children(
        self,
        request: Optional[
            Union[metadata_service.RemoveContextChildrenRequest, dict]
        ] = None,
        *,
        context: Optional[str] = None,
        child_contexts: Optional[MutableSequence[str]] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> metadata_service.RemoveContextChildrenResponse:
        r"""Remove a set of children contexts from a parent
        Context. If any of the child Contexts were NOT added to
        the parent Context, they are simply skipped.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_remove_context_children():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.RemoveContextChildrenRequest(
                    context="context_value",
                )

                # Make the request
                response = client.remove_context_children(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.RemoveContextChildrenRequest, dict]):
                The request object. Request message for
                [MetadataService.DeleteContextChildrenRequest][].
            context (str):
                Required. The resource name of the parent Context.

                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                This corresponds to the ``context`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            child_contexts (MutableSequence[str]):
                The resource names of the child
                Contexts.

                This corresponds to the ``child_contexts`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.RemoveContextChildrenResponse:
                Response message for
                   [MetadataService.RemoveContextChildren][google.cloud.aiplatform.v1beta1.MetadataService.RemoveContextChildren].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([context, child_contexts])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.RemoveContextChildrenRequest):
            request = metadata_service.RemoveContextChildrenRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if context is not None:
                request.context = context
            if child_contexts is not None:
                request.child_contexts = child_contexts

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.remove_context_children]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("context", request.context),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def query_context_lineage_subgraph(
        self,
        request: Optional[
            Union[metadata_service.QueryContextLineageSubgraphRequest, dict]
        ] = None,
        *,
        context: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> lineage_subgraph.LineageSubgraph:
        r"""Retrieves Artifacts and Executions within the
        specified Context, connected by Event edges and returned
        as a LineageSubgraph.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_query_context_lineage_subgraph():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.QueryContextLineageSubgraphRequest(
                    context="context_value",
                )

                # Make the request
                response = client.query_context_lineage_subgraph(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.QueryContextLineageSubgraphRequest, dict]):
                The request object. Request message for
                [MetadataService.QueryContextLineageSubgraph][google.cloud.aiplatform.v1beta1.MetadataService.QueryContextLineageSubgraph].
            context (str):
                Required. The resource name of the Context whose
                Artifacts and Executions should be retrieved as a
                LineageSubgraph. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}``

                The request may error with FAILED_PRECONDITION if the
                number of Artifacts, the number of Executions, or the
                number of Events that would be returned for the Context
                exceeds 1000.

                This corresponds to the ``context`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.LineageSubgraph:
                A subgraph of the overall lineage
                graph. Event edges connect Artifact and
                Execution nodes.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([context])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.QueryContextLineageSubgraphRequest):
            request = metadata_service.QueryContextLineageSubgraphRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if context is not None:
                request.context = context

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[
            self._transport.query_context_lineage_subgraph
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("context", request.context),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def create_execution(
        self,
        request: Optional[Union[metadata_service.CreateExecutionRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        execution: Optional[gca_execution.Execution] = None,
        execution_id: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_execution.Execution:
        r"""Creates an Execution associated with a MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_create_execution():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.CreateExecutionRequest(
                    parent="parent_value",
                )

                # Make the request
                response = client.create_execution(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.CreateExecutionRequest, dict]):
                The request object. Request message for
                [MetadataService.CreateExecution][google.cloud.aiplatform.v1beta1.MetadataService.CreateExecution].
            parent (str):
                Required. The resource name of the MetadataStore where
                the Execution should be created. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            execution (google.cloud.aiplatform_v1beta1.types.Execution):
                Required. The Execution to create.
                This corresponds to the ``execution`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            execution_id (str):
                The {execution} portion of the resource name with the
                format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``
                If not provided, the Execution's ID will be a UUID
                generated by the service. Must be 4-128 characters in
                length. Valid characters are ``/[a-z][0-9]-/``. Must be
                unique across all Executions in the parent
                MetadataStore. (Otherwise the request will fail with
                ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't
                view the preexisting Execution.)

                This corresponds to the ``execution_id`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Execution:
                Instance of a general execution.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent, execution, execution_id])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.CreateExecutionRequest):
            request = metadata_service.CreateExecutionRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent
            if execution is not None:
                request.execution = execution
            if execution_id is not None:
                request.execution_id = execution_id

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.create_execution]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_execution(
        self,
        request: Optional[Union[metadata_service.GetExecutionRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> execution.Execution:
        r"""Retrieves a specific Execution.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_get_execution():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetExecutionRequest(
                    name="name_value",
                )

                # Make the request
                response = client.get_execution(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.GetExecutionRequest, dict]):
                The request object. Request message for
                [MetadataService.GetExecution][google.cloud.aiplatform.v1beta1.MetadataService.GetExecution].
            name (str):
                Required. The resource name of the Execution to
                retrieve. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Execution:
                Instance of a general execution.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.GetExecutionRequest):
            request = metadata_service.GetExecutionRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_execution]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def list_executions(
        self,
        request: Optional[Union[metadata_service.ListExecutionsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> pagers.ListExecutionsPager:
        r"""Lists Executions in the MetadataStore.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_list_executions():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.ListExecutionsRequest(
                    parent="parent_value",
                )

                # Make the request
                page_result = client.list_executions(request=request)

                # Handle the response
                for response in page_result:
                    print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.ListExecutionsRequest, dict]):
                The request object. Request message for
                [MetadataService.ListExecutions][google.cloud.aiplatform.v1beta1.MetadataService.ListExecutions].
            parent (str):
                Required. The MetadataStore whose Executions should be
                listed. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.services.metadata_service.pagers.ListExecutionsPager:
                Response message for
                   [MetadataService.ListExecutions][google.cloud.aiplatform.v1beta1.MetadataService.ListExecutions].

                Iterating over this object will yield results and
                resolve additional pages automatically.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.ListExecutionsRequest):
            request = metadata_service.ListExecutionsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_executions]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__iter__` convenience method.
        response = pagers.ListExecutionsPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def update_execution(
        self,
        request: Optional[Union[metadata_service.UpdateExecutionRequest, dict]] = None,
        *,
        execution: Optional[gca_execution.Execution] = None,
        update_mask: Optional[field_mask_pb2.FieldMask] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_execution.Execution:
        r"""Updates a stored Execution.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_update_execution():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.UpdateExecutionRequest(
                )

                # Make the request
                response = client.update_execution(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.UpdateExecutionRequest, dict]):
                The request object. Request message for
                [MetadataService.UpdateExecution][google.cloud.aiplatform.v1beta1.MetadataService.UpdateExecution].
            execution (google.cloud.aiplatform_v1beta1.types.Execution):
                Required. The Execution containing updates. The
                Execution's
                [Execution.name][google.cloud.aiplatform.v1beta1.Execution.name]
                field is used to identify the Execution to be updated.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``

                This corresponds to the ``execution`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            update_mask (google.protobuf.field_mask_pb2.FieldMask):
                Optional. A FieldMask indicating
                which fields should be updated.

                This corresponds to the ``update_mask`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.Execution:
                Instance of a general execution.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([execution, update_mask])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.UpdateExecutionRequest):
            request = metadata_service.UpdateExecutionRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if execution is not None:
                request.execution = execution
            if update_mask is not None:
                request.update_mask = update_mask

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.update_execution]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata(
                (("execution.name", request.execution.name),)
            ),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def delete_execution(
        self,
        request: Optional[Union[metadata_service.DeleteExecutionRequest, dict]] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Deletes an Execution.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_delete_execution():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.DeleteExecutionRequest(
                    name="name_value",
                )

                # Make the request
                operation = client.delete_execution(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.DeleteExecutionRequest, dict]):
                The request object. Request message for
                [MetadataService.DeleteExecution][google.cloud.aiplatform.v1beta1.MetadataService.DeleteExecution].
            name (str):
                Required. The resource name of the Execution to delete.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
                   empty messages in your APIs. A typical example is to
                   use it as the request or the response type of an API
                   method. For instance:

                      service Foo {
                         rpc Bar(google.protobuf.Empty) returns
                         (google.protobuf.Empty);

                      }

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.DeleteExecutionRequest):
            request = metadata_service.DeleteExecutionRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.delete_execution]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            empty_pb2.Empty,
            metadata_type=gca_operation.DeleteOperationMetadata,
        )

        # Done; return the response.
        return response

    def purge_executions(
        self,
        request: Optional[Union[metadata_service.PurgeExecutionsRequest, dict]] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gac_operation.Operation:
        r"""Purges Executions.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_purge_executions():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.PurgeExecutionsRequest(
                    parent="parent_value",
                    filter="filter_value",
                )

                # Make the request
                operation = client.purge_executions(request=request)

                print("Waiting for operation to complete...")

                response = operation.result()

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.PurgeExecutionsRequest, dict]):
                The request object. Request message for
                [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1beta1.MetadataService.PurgeExecutions].
            parent (str):
                Required. The metadata store to purge Executions from.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.api_core.operation.Operation:
                An object representing a long-running operation.

                The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.PurgeExecutionsResponse` Response message for
                   [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1beta1.MetadataService.PurgeExecutions].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.PurgeExecutionsRequest):
            request = metadata_service.PurgeExecutionsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.purge_executions]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Wrap the response in an operation future.
        response = gac_operation.from_gapic(
            response,
            self._transport.operations_client,
            metadata_service.PurgeExecutionsResponse,
            metadata_type=metadata_service.PurgeExecutionsMetadata,
        )

        # Done; return the response.
        return response

    def add_execution_events(
        self,
        request: Optional[
            Union[metadata_service.AddExecutionEventsRequest, dict]
        ] = None,
        *,
        execution: Optional[str] = None,
        events: Optional[MutableSequence[event.Event]] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> metadata_service.AddExecutionEventsResponse:
        r"""Adds Events to the specified Execution. An Event
        indicates whether an Artifact was used as an input or
        output for an Execution. If an Event already exists
        between the Execution and the Artifact, the Event is
        skipped.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_add_execution_events():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.AddExecutionEventsRequest(
                    execution="execution_value",
                )

                # Make the request
                response = client.add_execution_events(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.AddExecutionEventsRequest, dict]):
                The request object. Request message for
                [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1beta1.MetadataService.AddExecutionEvents].
            execution (str):
                Required. The resource name of the Execution that the
                Events connect Artifacts with. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``

                This corresponds to the ``execution`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            events (MutableSequence[google.cloud.aiplatform_v1beta1.types.Event]):
                The Events to create and add.
                This corresponds to the ``events`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.AddExecutionEventsResponse:
                Response message for
                   [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1beta1.MetadataService.AddExecutionEvents].

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([execution, events])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.AddExecutionEventsRequest):
            request = metadata_service.AddExecutionEventsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if execution is not None:
                request.execution = execution
            if events is not None:
                request.events = events

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.add_execution_events]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata(
                (("execution", request.execution),)
            ),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def query_execution_inputs_and_outputs(
        self,
        request: Optional[
            Union[metadata_service.QueryExecutionInputsAndOutputsRequest, dict]
        ] = None,
        *,
        execution: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> lineage_subgraph.LineageSubgraph:
        r"""Obtains the set of input and output Artifacts for
        this Execution, in the form of LineageSubgraph that also
        contains the Execution and connecting Events.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_query_execution_inputs_and_outputs():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.QueryExecutionInputsAndOutputsRequest(
                    execution="execution_value",
                )

                # Make the request
                response = client.query_execution_inputs_and_outputs(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.QueryExecutionInputsAndOutputsRequest, dict]):
                The request object. Request message for
                [MetadataService.QueryExecutionInputsAndOutputs][google.cloud.aiplatform.v1beta1.MetadataService.QueryExecutionInputsAndOutputs].
            execution (str):
                Required. The resource name of the Execution whose input
                and output Artifacts should be retrieved as a
                LineageSubgraph. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}``

                This corresponds to the ``execution`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.LineageSubgraph:
                A subgraph of the overall lineage
                graph. Event edges connect Artifact and
                Execution nodes.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([execution])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(
            request, metadata_service.QueryExecutionInputsAndOutputsRequest
        ):
            request = metadata_service.QueryExecutionInputsAndOutputsRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if execution is not None:
                request.execution = execution

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[
            self._transport.query_execution_inputs_and_outputs
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata(
                (("execution", request.execution),)
            ),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def create_metadata_schema(
        self,
        request: Optional[
            Union[metadata_service.CreateMetadataSchemaRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        metadata_schema: Optional[gca_metadata_schema.MetadataSchema] = None,
        metadata_schema_id: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gca_metadata_schema.MetadataSchema:
        r"""Creates a MetadataSchema.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_create_metadata_schema():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                metadata_schema = aiplatform_v1beta1.MetadataSchema()
                metadata_schema.schema = "schema_value"

                request = aiplatform_v1beta1.CreateMetadataSchemaRequest(
                    parent="parent_value",
                    metadata_schema=metadata_schema,
                )

                # Make the request
                response = client.create_metadata_schema(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.CreateMetadataSchemaRequest, dict]):
                The request object. Request message for
                [MetadataService.CreateMetadataSchema][google.cloud.aiplatform.v1beta1.MetadataService.CreateMetadataSchema].
            parent (str):
                Required. The resource name of the MetadataStore where
                the MetadataSchema should be created. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            metadata_schema (google.cloud.aiplatform_v1beta1.types.MetadataSchema):
                Required. The MetadataSchema to
                create.

                This corresponds to the ``metadata_schema`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            metadata_schema_id (str):
                The {metadata_schema} portion of the resource name with
                the format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}``
                If not provided, the MetadataStore's ID will be a UUID
                generated by the service. Must be 4-128 characters in
                length. Valid characters are ``/[a-z][0-9]-/``. Must be
                unique across all MetadataSchemas in the parent
                Location. (Otherwise the request will fail with
                ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't
                view the preexisting MetadataSchema.)

                This corresponds to the ``metadata_schema_id`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.MetadataSchema:
                Instance of a general MetadataSchema.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent, metadata_schema, metadata_schema_id])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.CreateMetadataSchemaRequest):
            request = metadata_service.CreateMetadataSchemaRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent
            if metadata_schema is not None:
                request.metadata_schema = metadata_schema
            if metadata_schema_id is not None:
                request.metadata_schema_id = metadata_schema_id

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.create_metadata_schema]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_metadata_schema(
        self,
        request: Optional[
            Union[metadata_service.GetMetadataSchemaRequest, dict]
        ] = None,
        *,
        name: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> metadata_schema.MetadataSchema:
        r"""Retrieves a specific MetadataSchema.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_get_metadata_schema():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.GetMetadataSchemaRequest(
                    name="name_value",
                )

                # Make the request
                response = client.get_metadata_schema(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.GetMetadataSchemaRequest, dict]):
                The request object. Request message for
                [MetadataService.GetMetadataSchema][google.cloud.aiplatform.v1beta1.MetadataService.GetMetadataSchema].
            name (str):
                Required. The resource name of the MetadataSchema to
                retrieve. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}``

                This corresponds to the ``name`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.MetadataSchema:
                Instance of a general MetadataSchema.
        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([name])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.GetMetadataSchemaRequest):
            request = metadata_service.GetMetadataSchemaRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if name is not None:
                request.name = name

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_metadata_schema]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def list_metadata_schemas(
        self,
        request: Optional[
            Union[metadata_service.ListMetadataSchemasRequest, dict]
        ] = None,
        *,
        parent: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> pagers.ListMetadataSchemasPager:
        r"""Lists MetadataSchemas.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_list_metadata_schemas():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.ListMetadataSchemasRequest(
                    parent="parent_value",
                )

                # Make the request
                page_result = client.list_metadata_schemas(request=request)

                # Handle the response
                for response in page_result:
                    print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.ListMetadataSchemasRequest, dict]):
                The request object. Request message for
                [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataSchemas].
            parent (str):
                Required. The MetadataStore whose MetadataSchemas should
                be listed. Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}``

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.services.metadata_service.pagers.ListMetadataSchemasPager:
                Response message for
                   [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataSchemas].

                Iterating over this object will yield results and
                resolve additional pages automatically.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([parent])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(request, metadata_service.ListMetadataSchemasRequest):
            request = metadata_service.ListMetadataSchemasRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if parent is not None:
                request.parent = parent

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_metadata_schemas]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # This method is paged; wrap the response in a pager, which provides
        # an `__iter__` convenience method.
        response = pagers.ListMetadataSchemasPager(
            method=rpc,
            request=request,
            response=response,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def query_artifact_lineage_subgraph(
        self,
        request: Optional[
            Union[metadata_service.QueryArtifactLineageSubgraphRequest, dict]
        ] = None,
        *,
        artifact: Optional[str] = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> lineage_subgraph.LineageSubgraph:
        r"""Retrieves lineage of an Artifact represented through
        Artifacts and Executions connected by Event edges and
        returned as a LineageSubgraph.

        .. code-block:: python

            # This snippet has been automatically generated and should be regarded as a
            # code template only.
            # It will require modifications to work:
            # - It may require correct/in-range values for request initialization.
            # - It may require specifying regional endpoints when creating the service
            #   client as shown in:
            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
            from google.cloud import aiplatform_v1beta1

            def sample_query_artifact_lineage_subgraph():
                # Create a client
                client = aiplatform_v1beta1.MetadataServiceClient()

                # Initialize request argument(s)
                request = aiplatform_v1beta1.QueryArtifactLineageSubgraphRequest(
                    artifact="artifact_value",
                )

                # Make the request
                response = client.query_artifact_lineage_subgraph(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.aiplatform_v1beta1.types.QueryArtifactLineageSubgraphRequest, dict]):
                The request object. Request message for
                [MetadataService.QueryArtifactLineageSubgraph][google.cloud.aiplatform.v1beta1.MetadataService.QueryArtifactLineageSubgraph].
            artifact (str):
                Required. The resource name of the Artifact whose
                Lineage needs to be retrieved as a LineageSubgraph.
                Format:
                ``projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}``

                The request may error with FAILED_PRECONDITION if the
                number of Artifacts, the number of Executions, or the
                number of Events that would be returned for the Context
                exceeds 1000.

                This corresponds to the ``artifact`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.

        Returns:
            google.cloud.aiplatform_v1beta1.types.LineageSubgraph:
                A subgraph of the overall lineage
                graph. Event edges connect Artifact and
                Execution nodes.

        """
        # Create or coerce a protobuf request object.
        # - Quick check: If we got a request object, we should *not* have
        #   gotten any keyword arguments that map to the request.
        has_flattened_params = any([artifact])
        if request is not None and has_flattened_params:
            raise ValueError(
                "If the `request` argument is set, then none of "
                "the individual field arguments should be set."
            )

        # - Use the request object if provided (there's no risk of modifying the input as
        #   there are no flattened fields), or create one.
        if not isinstance(
            request, metadata_service.QueryArtifactLineageSubgraphRequest
        ):
            request = metadata_service.QueryArtifactLineageSubgraphRequest(request)
            # If we have keyword arguments corresponding to fields on the
            # request, apply these.
            if artifact is not None:
                request.artifact = artifact

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[
            self._transport.query_artifact_lineage_subgraph
        ]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("artifact", request.artifact),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def __enter__(self) -> "MetadataServiceClient":
        return self

    def __exit__(self, type, value, traceback):
        """Releases underlying transport's resources.

        .. warning::
            ONLY use as a context manager if the transport is NOT shared
            with other clients! Exiting the with block will CLOSE the transport
            and may cause errors in other clients!
        """
        self.transport.close()

    def list_operations(
        self,
        request: Optional[operations_pb2.ListOperationsRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> operations_pb2.ListOperationsResponse:
        r"""Lists operations that match the specified filter in the request.

        Args:
            request (:class:`~.operations_pb2.ListOperationsRequest`):
                The request object. Request message for
                `ListOperations` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                    if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.operations_pb2.ListOperationsResponse:
                Response message for ``ListOperations`` method.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.ListOperationsRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_operations]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_operation(
        self,
        request: Optional[operations_pb2.GetOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> operations_pb2.Operation:
        r"""Gets the latest state of a long-running operation.

        Args:
            request (:class:`~.operations_pb2.GetOperationRequest`):
                The request object. Request message for
                `GetOperation` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                    if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.operations_pb2.Operation:
                An ``Operation`` object.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.GetOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def delete_operation(
        self,
        request: Optional[operations_pb2.DeleteOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> None:
        r"""Deletes a long-running operation.

        This method indicates that the client is no longer interested
        in the operation result. It does not cancel the operation.
        If the server doesn't support this method, it returns
        `google.rpc.Code.UNIMPLEMENTED`.

        Args:
            request (:class:`~.operations_pb2.DeleteOperationRequest`):
                The request object. Request message for
                `DeleteOperation` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                    if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            None
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.DeleteOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.delete_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

    def cancel_operation(
        self,
        request: Optional[operations_pb2.CancelOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> None:
        r"""Starts asynchronous cancellation on a long-running operation.

        The server makes a best effort to cancel the operation, but success
        is not guaranteed.  If the server doesn't support this method, it returns
        `google.rpc.Code.UNIMPLEMENTED`.

        Args:
            request (:class:`~.operations_pb2.CancelOperationRequest`):
                The request object. Request message for
                `CancelOperation` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                    if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            None
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.CancelOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.cancel_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

    def wait_operation(
        self,
        request: Optional[operations_pb2.WaitOperationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> operations_pb2.Operation:
        r"""Waits until the specified long-running operation is done or reaches at most
        a specified timeout, returning the latest state.

        If the operation is already done, the latest state is immediately returned.
        If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC
        timeout is used.  If the server does not support this method, it returns
        `google.rpc.Code.UNIMPLEMENTED`.

        Args:
            request (:class:`~.operations_pb2.WaitOperationRequest`):
                The request object. Request message for
                `WaitOperation` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                    if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.operations_pb2.Operation:
                An ``Operation`` object.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = operations_pb2.WaitOperationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.wait_operation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def set_iam_policy(
        self,
        request: Optional[iam_policy_pb2.SetIamPolicyRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> policy_pb2.Policy:
        r"""Sets the IAM access control policy on the specified function.

        Replaces any existing policy.

        Args:
            request (:class:`~.iam_policy_pb2.SetIamPolicyRequest`):
                The request object. Request message for `SetIamPolicy`
                method.
            retry (google.api_core.retry.Retry): Designation of what errors, if any,
                should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.policy_pb2.Policy:
                Defines an Identity and Access Management (IAM) policy.
                It is used to specify access control policies for Cloud
                Platform resources.
                A ``Policy`` is a collection of ``bindings``. A
                ``binding`` binds one or more ``members`` to a single
                ``role``. Members can be user accounts, service
                accounts, Google groups, and domains (such as G Suite).
                A ``role`` is a named list of permissions (defined by
                IAM or configured by users). A ``binding`` can
                optionally specify a ``condition``, which is a logic
                expression that further constrains the role binding
                based on attributes about the request and/or target
                resource.

                **JSON Example**

                ::

                    {
                      "bindings": [
                        {
                          "role": "roles/resourcemanager.organizationAdmin",
                          "members": [
                            "user:mike@example.com",
                            "group:admins@example.com",
                            "domain:google.com",
                            "serviceAccount:my-project-id@appspot.gserviceaccount.com"
                          ]
                        },
                        {
                          "role": "roles/resourcemanager.organizationViewer",
                          "members": ["user:eve@example.com"],
                          "condition": {
                            "title": "expirable access",
                            "description": "Does not grant access after Sep 2020",
                            "expression": "request.time <
                            timestamp('2020-10-01T00:00:00.000Z')",
                          }
                        }
                      ]
                    }

                **YAML Example**

                ::

                    bindings:
                    - members:
                      - user:mike@example.com
                      - group:admins@example.com
                      - domain:google.com
                      - serviceAccount:my-project-id@appspot.gserviceaccount.com
                      role: roles/resourcemanager.organizationAdmin
                    - members:
                      - user:eve@example.com
                      role: roles/resourcemanager.organizationViewer
                      condition:
                        title: expirable access
                        description: Does not grant access after Sep 2020
                        expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

                For a description of IAM and its features, see the `IAM
                developer's
                guide <https://cloud.google.com/iam/docs>`__.
        """
        # Create or coerce a protobuf request object.

        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = iam_policy_pb2.SetIamPolicyRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.set_iam_policy]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("resource", request.resource),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_iam_policy(
        self,
        request: Optional[iam_policy_pb2.GetIamPolicyRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> policy_pb2.Policy:
        r"""Gets the IAM access control policy for a function.

        Returns an empty policy if the function exists and does not have a
        policy set.

        Args:
            request (:class:`~.iam_policy_pb2.GetIamPolicyRequest`):
                The request object. Request message for `GetIamPolicy`
                method.
            retry (google.api_core.retry.Retry): Designation of what errors, if
                any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.policy_pb2.Policy:
                Defines an Identity and Access Management (IAM) policy.
                It is used to specify access control policies for Cloud
                Platform resources.
                A ``Policy`` is a collection of ``bindings``. A
                ``binding`` binds one or more ``members`` to a single
                ``role``. Members can be user accounts, service
                accounts, Google groups, and domains (such as G Suite).
                A ``role`` is a named list of permissions (defined by
                IAM or configured by users). A ``binding`` can
                optionally specify a ``condition``, which is a logic
                expression that further constrains the role binding
                based on attributes about the request and/or target
                resource.

                **JSON Example**

                ::

                    {
                      "bindings": [
                        {
                          "role": "roles/resourcemanager.organizationAdmin",
                          "members": [
                            "user:mike@example.com",
                            "group:admins@example.com",
                            "domain:google.com",
                            "serviceAccount:my-project-id@appspot.gserviceaccount.com"
                          ]
                        },
                        {
                          "role": "roles/resourcemanager.organizationViewer",
                          "members": ["user:eve@example.com"],
                          "condition": {
                            "title": "expirable access",
                            "description": "Does not grant access after Sep 2020",
                            "expression": "request.time <
                            timestamp('2020-10-01T00:00:00.000Z')",
                          }
                        }
                      ]
                    }

                **YAML Example**

                ::

                    bindings:
                    - members:
                      - user:mike@example.com
                      - group:admins@example.com
                      - domain:google.com
                      - serviceAccount:my-project-id@appspot.gserviceaccount.com
                      role: roles/resourcemanager.organizationAdmin
                    - members:
                      - user:eve@example.com
                      role: roles/resourcemanager.organizationViewer
                      condition:
                        title: expirable access
                        description: Does not grant access after Sep 2020
                        expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

                For a description of IAM and its features, see the `IAM
                developer's
                guide <https://cloud.google.com/iam/docs>`__.
        """
        # Create or coerce a protobuf request object.

        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = iam_policy_pb2.GetIamPolicyRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_iam_policy]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("resource", request.resource),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def test_iam_permissions(
        self,
        request: Optional[iam_policy_pb2.TestIamPermissionsRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> iam_policy_pb2.TestIamPermissionsResponse:
        r"""Tests the specified IAM permissions against the IAM access control
            policy for a function.

        If the function does not exist, this will return an empty set
        of permissions, not a NOT_FOUND error.

        Args:
            request (:class:`~.iam_policy_pb2.TestIamPermissionsRequest`):
                The request object. Request message for
                `TestIamPermissions` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                 if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.iam_policy_pb2.TestIamPermissionsResponse:
                Response message for ``TestIamPermissions`` method.
        """
        # Create or coerce a protobuf request object.

        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = iam_policy_pb2.TestIamPermissionsRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.test_iam_permissions]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("resource", request.resource),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def get_location(
        self,
        request: Optional[locations_pb2.GetLocationRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> locations_pb2.Location:
        r"""Gets information about a location.

        Args:
            request (:class:`~.location_pb2.GetLocationRequest`):
                The request object. Request message for
                `GetLocation` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                 if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.location_pb2.Location:
                Location object.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = locations_pb2.GetLocationRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.get_location]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response

    def list_locations(
        self,
        request: Optional[locations_pb2.ListLocationsRequest] = None,
        *,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> locations_pb2.ListLocationsResponse:
        r"""Lists information about the supported locations for this service.

        Args:
            request (:class:`~.location_pb2.ListLocationsRequest`):
                The request object. Request message for
                `ListLocations` method.
            retry (google.api_core.retry.Retry): Designation of what errors,
                 if any, should be retried.
            timeout (float): The timeout for this request.
            metadata (Sequence[Tuple[str, str]]): Strings which should be
                sent along with the request as metadata.
        Returns:
            ~.location_pb2.ListLocationsResponse:
                Response message for ``ListLocations`` method.
        """
        # Create or coerce a protobuf request object.
        # The request isn't a proto-plus wrapped type,
        # so it must be constructed via keyword expansion.
        if isinstance(request, dict):
            request = locations_pb2.ListLocationsRequest(**request)

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[self._transport.list_locations]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
        )

        # Validate the universe domain.
        self._validate_universe_domain()

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response


DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
    gapic_version=package_version.__version__
)


__all__ = ("MetadataServiceClient",)
