# -*- coding: utf-8 -*- # Copyright 2025 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 from http import HTTPStatus import json import logging as std_logging import os import re from typing import ( Callable, Dict, Mapping, MutableMapping, MutableSequence, Optional, Sequence, Tuple, Type, Union, cast, ) import warnings 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.exceptions import MutualTLSChannelError # type: ignore from google.auth.transport import mtls # type: ignore from google.auth.transport.grpc import SslCredentials # type: ignore from google.oauth2 import service_account # type: ignore import google.protobuf from google.analytics.data_v1beta import gapic_version as package_version try: OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault, None] except AttributeError: # pragma: NO COVER OptionalRetry = Union[retries.Retry, object, None] # type: ignore try: from google.api_core import client_logging # type: ignore CLIENT_LOGGING_SUPPORTED = True # pragma: NO COVER except ImportError: # pragma: NO COVER CLIENT_LOGGING_SUPPORTED = False _LOGGER = std_logging.getLogger(__name__) from google.api_core import operation # type: ignore from google.api_core import operation_async # type: ignore from google.longrunning import operations_pb2 # type: ignore from google.protobuf import timestamp_pb2 # type: ignore from google.analytics.data_v1beta.services.beta_analytics_data import pagers from google.analytics.data_v1beta.types import analytics_data_api, data from .transports.base import DEFAULT_CLIENT_INFO, BetaAnalyticsDataTransport from .transports.grpc import BetaAnalyticsDataGrpcTransport from .transports.grpc_asyncio import BetaAnalyticsDataGrpcAsyncIOTransport from .transports.rest import BetaAnalyticsDataRestTransport class BetaAnalyticsDataClientMeta(type): """Metaclass for the BetaAnalyticsData 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[BetaAnalyticsDataTransport]] _transport_registry["grpc"] = BetaAnalyticsDataGrpcTransport _transport_registry["grpc_asyncio"] = BetaAnalyticsDataGrpcAsyncIOTransport _transport_registry["rest"] = BetaAnalyticsDataRestTransport def get_transport_class( cls, label: Optional[str] = None, ) -> Type[BetaAnalyticsDataTransport]: """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: 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 BetaAnalyticsDataClient(metaclass=BetaAnalyticsDataClientMeta): """Google Analytics reporting data service.""" @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[^.]+)(?P\.mtls)?(?P\.sandbox)?(?P\.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 = "analyticsdata.googleapis.com" DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore DEFAULT_ENDPOINT ) _DEFAULT_ENDPOINT_TEMPLATE = "analyticsdata.{UNIVERSE_DOMAIN}" _DEFAULT_UNIVERSE = "googleapis.com" @staticmethod def _use_client_cert_effective(): """Returns whether client certificate should be used for mTLS if the google-auth version supports should_use_client_cert automatic mTLS enablement. Alternatively, read from the GOOGLE_API_USE_CLIENT_CERTIFICATE env var. Returns: bool: whether client certificate should be used for mTLS Raises: ValueError: (If using a version of google-auth without should_use_client_cert and GOOGLE_API_USE_CLIENT_CERTIFICATE is set to an unexpected value.) """ # check if google-auth version supports should_use_client_cert for automatic mTLS enablement if hasattr(mtls, "should_use_client_cert"): # pragma: NO COVER return mtls.should_use_client_cert() else: # pragma: NO COVER # if unsupported, fallback to reading from env var use_client_cert_str = os.getenv( "GOOGLE_API_USE_CLIENT_CERTIFICATE", "false" ).lower() if use_client_cert_str not in ("true", "false"): raise ValueError( "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be" " either `true` or `false`" ) return use_client_cert_str == "true" @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: BetaAnalyticsDataClient: 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: BetaAnalyticsDataClient: 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) -> BetaAnalyticsDataTransport: """Returns the transport used by the client instance. Returns: BetaAnalyticsDataTransport: The transport used by the client instance. """ return self._transport @staticmethod def audience_export_path( property: str, audience_export: str, ) -> str: """Returns a fully-qualified audience_export string.""" return "properties/{property}/audienceExports/{audience_export}".format( property=property, audience_export=audience_export, ) @staticmethod def parse_audience_export_path(path: str) -> Dict[str, str]: """Parses a audience_export path into its component segments.""" m = re.match( r"^properties/(?P.+?)/audienceExports/(?P.+?)$", path, ) return m.groupdict() if m else {} @staticmethod def metadata_path( property: str, ) -> str: """Returns a fully-qualified metadata string.""" return "properties/{property}/metadata".format( property=property, ) @staticmethod def parse_metadata_path(path: str) -> Dict[str, str]: """Parses a metadata path into its component segments.""" m = re.match(r"^properties/(?P.+?)/metadata$", 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.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_folder_path( folder: str, ) -> str: """Returns a fully-qualified folder string.""" return "folders/{folder}".format( folder=folder, ) @staticmethod def parse_common_folder_path(path: str) -> Dict[str, str]: """Parse a folder path into its component segments.""" m = re.match(r"^folders/(?P.+?)$", 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.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_project_path( project: str, ) -> str: """Returns a fully-qualified project string.""" return "projects/{project}".format( project=project, ) @staticmethod def parse_common_project_path(path: str) -> Dict[str, str]: """Parse a project path into its component segments.""" m = re.match(r"^projects/(?P.+?)$", 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.+?)/locations/(?P.+?)$", 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 = BetaAnalyticsDataClient._use_client_cert_effective() use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto") 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: 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 = BetaAnalyticsDataClient._use_client_cert_effective() use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto").lower() universe_domain_env = os.getenv("GOOGLE_CLOUD_UNIVERSE_DOMAIN") 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, 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 = BetaAnalyticsDataClient._DEFAULT_UNIVERSE if universe_domain != _default_universe: raise MutualTLSChannelError( f"mTLS is not supported in any universe other than {_default_universe}." ) api_endpoint = BetaAnalyticsDataClient.DEFAULT_MTLS_ENDPOINT else: api_endpoint = BetaAnalyticsDataClient._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 = BetaAnalyticsDataClient._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 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. """ # NOTE (b/349488459): universe validation is disabled until further notice. return True def _add_cred_info_for_auth_errors( self, error: core_exceptions.GoogleAPICallError ) -> None: """Adds credential info string to error details for 401/403/404 errors. Args: error (google.api_core.exceptions.GoogleAPICallError): The error to add the cred info. """ if error.code not in [ HTTPStatus.UNAUTHORIZED, HTTPStatus.FORBIDDEN, HTTPStatus.NOT_FOUND, ]: return cred = self._transport._credentials # get_cred_info is only available in google-auth>=2.35.0 if not hasattr(cred, "get_cred_info"): return # ignore the type check since pypy test fails when get_cred_info # is not available cred_info = cred.get_cred_info() # type: ignore if cred_info and hasattr(error._details, "append"): error._details.append(json.dumps(cred_info)) @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, BetaAnalyticsDataTransport, Callable[..., BetaAnalyticsDataTransport], ] ] = None, client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiates the beta analytics data 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,BetaAnalyticsDataTransport,Callable[..., BetaAnalyticsDataTransport]]]): 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 BetaAnalyticsDataTransport 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, ) = BetaAnalyticsDataClient._read_environment_variables() self._client_cert_source = BetaAnalyticsDataClient._get_client_cert_source( self._client_options.client_cert_source, self._use_client_cert ) self._universe_domain = BetaAnalyticsDataClient._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 if CLIENT_LOGGING_SUPPORTED: # pragma: NO COVER # Setup logging. client_logging.initialize_logging() 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, BetaAnalyticsDataTransport) if transport_provided: # transport is a BetaAnalyticsDataTransport 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(BetaAnalyticsDataTransport, transport) self._api_endpoint = self._transport.host self._api_endpoint = ( self._api_endpoint or BetaAnalyticsDataClient._get_api_endpoint( self._client_options.api_endpoint, self._client_cert_source, self._universe_domain, self._use_mtls_endpoint, ) ) if not transport_provided: 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 ) transport_init: Union[ Type[BetaAnalyticsDataTransport], Callable[..., BetaAnalyticsDataTransport], ] = ( BetaAnalyticsDataClient.get_transport_class(transport) if isinstance(transport, str) or transport is None else cast(Callable[..., BetaAnalyticsDataTransport], transport) ) # 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, ) if "async" not in str(self._transport): if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor( std_logging.DEBUG ): # pragma: NO COVER _LOGGER.debug( "Created client `google.analytics.data_v1beta.BetaAnalyticsDataClient`.", extra={ "serviceName": "google.analytics.data.v1beta.BetaAnalyticsData", "universeDomain": getattr( self._transport._credentials, "universe_domain", "" ), "credentialsType": f"{type(self._transport._credentials).__module__}.{type(self._transport._credentials).__qualname__}", "credentialsInfo": getattr( self.transport._credentials, "get_cred_info", lambda: None )(), } if hasattr(self._transport, "_credentials") else { "serviceName": "google.analytics.data.v1beta.BetaAnalyticsData", "credentialsType": None, }, ) def run_report( self, request: Optional[Union[analytics_data_api.RunReportRequest, dict]] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.RunReportResponse: r"""Returns a customized report of your Google Analytics event data. Reports contain statistics derived from data collected by the Google Analytics tracking code. The data returned from the API is as a table with columns for the requested dimensions and metrics. Metrics are individual measurements of user activity on your property, such as active users or event count. Dimensions break down metrics across some common criteria, such as country or event name. For a guide to constructing requests & understanding responses, see `Creating a Report `__. .. 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.analytics import data_v1beta def sample_run_report(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.RunReportRequest( ) # Make the request response = client.run_report(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.RunReportRequest, dict]): The request object. The request to generate a report. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.RunReportResponse: The response report table corresponding to a request. """ # Create or coerce a protobuf request object. # - 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, analytics_data_api.RunReportRequest): request = analytics_data_api.RunReportRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.run_report] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("property", request.property),)), ) # 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 run_pivot_report( self, request: Optional[Union[analytics_data_api.RunPivotReportRequest, dict]] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.RunPivotReportResponse: r"""Returns a customized pivot report of your Google Analytics event data. Pivot reports are more advanced and expressive formats than regular reports. In a pivot report, dimensions are only visible if they are included in a pivot. Multiple pivots can be specified to further dissect your data. .. 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.analytics import data_v1beta def sample_run_pivot_report(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.RunPivotReportRequest( ) # Make the request response = client.run_pivot_report(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.RunPivotReportRequest, dict]): The request object. The request to generate a pivot report. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.RunPivotReportResponse: The response pivot report table corresponding to a pivot request. """ # Create or coerce a protobuf request object. # - 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, analytics_data_api.RunPivotReportRequest): request = analytics_data_api.RunPivotReportRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.run_pivot_report] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("property", request.property),)), ) # 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 batch_run_reports( self, request: Optional[ Union[analytics_data_api.BatchRunReportsRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.BatchRunReportsResponse: r"""Returns multiple reports in a batch. All reports must be for the same Google Analytics property. .. 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.analytics import data_v1beta def sample_batch_run_reports(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.BatchRunReportsRequest( ) # Make the request response = client.batch_run_reports(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.BatchRunReportsRequest, dict]): The request object. The batch request containing multiple report requests. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.BatchRunReportsResponse: The batch response containing multiple reports. """ # Create or coerce a protobuf request object. # - 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, analytics_data_api.BatchRunReportsRequest): request = analytics_data_api.BatchRunReportsRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.batch_run_reports] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("property", request.property),)), ) # 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 batch_run_pivot_reports( self, request: Optional[ Union[analytics_data_api.BatchRunPivotReportsRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.BatchRunPivotReportsResponse: r"""Returns multiple pivot reports in a batch. All reports must be for the same Google Analytics property. .. 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.analytics import data_v1beta def sample_batch_run_pivot_reports(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.BatchRunPivotReportsRequest( ) # Make the request response = client.batch_run_pivot_reports(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.BatchRunPivotReportsRequest, dict]): The request object. The batch request containing multiple pivot report requests. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.BatchRunPivotReportsResponse: The batch response containing multiple pivot reports. """ # Create or coerce a protobuf request object. # - 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, analytics_data_api.BatchRunPivotReportsRequest): request = analytics_data_api.BatchRunPivotReportsRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.batch_run_pivot_reports] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("property", request.property),)), ) # 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( self, request: Optional[Union[analytics_data_api.GetMetadataRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.Metadata: r"""Returns metadata for dimensions and metrics available in reporting methods. Used to explore the dimensions and metrics. In this method, a Google Analytics property identifier is specified in the request, and the metadata response includes Custom dimensions and metrics as well as Universal metadata. For example if a custom metric with parameter name ``levels_unlocked`` is registered to a property, the Metadata response will contain ``customEvent:levels_unlocked``. Universal metadata are dimensions and metrics applicable to any property such as ``country`` and ``totalUsers``. .. 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.analytics import data_v1beta def sample_get_metadata(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.GetMetadataRequest( name="name_value", ) # Make the request response = client.get_metadata(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.GetMetadataRequest, dict]): The request object. Request for a property's dimension and metric metadata. name (str): Required. The resource name of the metadata to retrieve. This name field is specified in the URL path and not URL parameters. Property is a numeric Google Analytics property identifier. To learn more, see `where to find your Property ID `__. Example: properties/1234/metadata Set the Property ID to 0 for dimensions and metrics common to all properties. In this special mode, this method will not return custom dimensions and metrics. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.Metadata: The dimensions, metrics and comparisons currently accepted in reporting methods. """ # 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. flattened_params = [name] has_flattened_params = ( len([param for param in flattened_params if param is not None]) > 0 ) 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, analytics_data_api.GetMetadataRequest): request = analytics_data_api.GetMetadataRequest(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] # 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 run_realtime_report( self, request: Optional[ Union[analytics_data_api.RunRealtimeReportRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.RunRealtimeReportResponse: r"""Returns a customized report of realtime event data for your property. Events appear in realtime reports seconds after they have been sent to the Google Analytics. Realtime reports show events and usage data for the periods of time ranging from the present moment to 30 minutes ago (up to 60 minutes for Google Analytics 360 properties). For a guide to constructing realtime requests & understanding responses, see `Creating a Realtime Report `__. .. 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.analytics import data_v1beta def sample_run_realtime_report(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.RunRealtimeReportRequest( ) # Make the request response = client.run_realtime_report(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.RunRealtimeReportRequest, dict]): The request object. The request to generate a realtime report. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.RunRealtimeReportResponse: The response realtime report table corresponding to a request. """ # Create or coerce a protobuf request object. # - 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, analytics_data_api.RunRealtimeReportRequest): request = analytics_data_api.RunRealtimeReportRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.run_realtime_report] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("property", request.property),)), ) # 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 check_compatibility( self, request: Optional[ Union[analytics_data_api.CheckCompatibilityRequest, dict] ] = None, *, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.CheckCompatibilityResponse: r"""This compatibility method lists dimensions and metrics that can be added to a report request and maintain compatibility. This method fails if the request's dimensions and metrics are incompatible. In Google Analytics, reports fail if they request incompatible dimensions and/or metrics; in that case, you will need to remove dimensions and/or metrics from the incompatible report until the report is compatible. The Realtime and Core reports have different compatibility rules. This method checks compatibility for Core reports. .. 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.analytics import data_v1beta def sample_check_compatibility(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.CheckCompatibilityRequest( ) # Make the request response = client.check_compatibility(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.CheckCompatibilityRequest, dict]): The request object. The request for compatibility information for a report's dimensions and metrics. Check compatibility provides a preview of the compatibility of a report; fields shared with the ``runReport`` request should be the same values as in your ``runReport`` request. 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.CheckCompatibilityResponse: The compatibility response with the compatibility of each dimension & metric. """ # Create or coerce a protobuf request object. # - 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, analytics_data_api.CheckCompatibilityRequest): request = analytics_data_api.CheckCompatibilityRequest(request) # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.check_compatibility] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("property", request.property),)), ) # 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_audience_export( self, request: Optional[ Union[analytics_data_api.CreateAudienceExportRequest, dict] ] = None, *, parent: Optional[str] = None, audience_export: Optional[analytics_data_api.AudienceExport] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> operation.Operation: r"""Creates an audience export for later retrieval. This method quickly returns the audience export's resource name and initiates a long running asynchronous request to form an audience export. To export the users in an audience export, first create the audience export through this method and then send the audience resource name to the ``QueryAudienceExport`` method. See `Creating an Audience Export `__ for an introduction to Audience Exports with examples. An audience export is a snapshot of the users currently in the audience at the time of audience export creation. Creating audience exports for one audience on different days will return different results as users enter and exit the audience. Audiences in Google Analytics 4 allow you to segment your users in the ways that are important to your business. To learn more, see https://support.google.com/analytics/answer/9267572. Audience exports contain the users in each audience. Audience Export APIs have some methods at alpha and other methods at beta stability. The intention is to advance methods to beta stability after some feedback and adoption. To give your feedback on this API, complete the `Google Analytics Audience Export API Feedback `__ form. .. 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.analytics import data_v1beta def sample_create_audience_export(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) audience_export = data_v1beta.AudienceExport() audience_export.audience = "audience_value" request = data_v1beta.CreateAudienceExportRequest( parent="parent_value", audience_export=audience_export, ) # Make the request operation = client.create_audience_export(request=request) print("Waiting for operation to complete...") response = operation.result() # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.CreateAudienceExportRequest, dict]): The request object. A request to create a new audience export. parent (str): Required. The parent resource where this audience export will be created. Format: ``properties/{property}`` This corresponds to the ``parent`` field on the ``request`` instance; if ``request`` is provided, this should not be set. audience_export (google.analytics.data_v1beta.types.AudienceExport): Required. The audience export to create. This corresponds to the ``audience_export`` 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.api_core.operation.Operation: An object representing a long-running operation. The result type for the operation will be :class:`google.analytics.data_v1beta.types.AudienceExport` An audience export is a list of users in an audience at the time of the list's creation. One audience may have multiple audience exports created for different days. """ # 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. flattened_params = [parent, audience_export] has_flattened_params = ( len([param for param in flattened_params if param is not None]) > 0 ) 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, analytics_data_api.CreateAudienceExportRequest): request = analytics_data_api.CreateAudienceExportRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if parent is not None: request.parent = parent if audience_export is not None: request.audience_export = audience_export # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.create_audience_export] # 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 = operation.from_gapic( response, self._transport.operations_client, analytics_data_api.AudienceExport, metadata_type=analytics_data_api.AudienceExportMetadata, ) # Done; return the response. return response def query_audience_export( self, request: Optional[ Union[analytics_data_api.QueryAudienceExportRequest, dict] ] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.QueryAudienceExportResponse: r"""Retrieves an audience export of users. After creating an audience, the users are not immediately available for exporting. First, a request to ``CreateAudienceExport`` is necessary to create an audience export of users, and then second, this method is used to retrieve the users in the audience export. See `Creating an Audience Export `__ for an introduction to Audience Exports with examples. Audiences in Google Analytics 4 allow you to segment your users in the ways that are important to your business. To learn more, see https://support.google.com/analytics/answer/9267572. Audience Export APIs have some methods at alpha and other methods at beta stability. The intention is to advance methods to beta stability after some feedback and adoption. To give your feedback on this API, complete the `Google Analytics Audience Export API Feedback `__ form. .. 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.analytics import data_v1beta def sample_query_audience_export(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.QueryAudienceExportRequest( name="name_value", ) # Make the request response = client.query_audience_export(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.QueryAudienceExportRequest, dict]): The request object. A request to list users in an audience export. name (str): Required. The name of the audience export to retrieve users from. Format: ``properties/{property}/audienceExports/{audience_export}`` 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.QueryAudienceExportResponse: A list of users in an audience export. """ # 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. flattened_params = [name] has_flattened_params = ( len([param for param in flattened_params if param is not None]) > 0 ) 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, analytics_data_api.QueryAudienceExportRequest): request = analytics_data_api.QueryAudienceExportRequest(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.query_audience_export] # 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_audience_export( self, request: Optional[ Union[analytics_data_api.GetAudienceExportRequest, dict] ] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> analytics_data_api.AudienceExport: r"""Gets configuration metadata about a specific audience export. This method can be used to understand an audience export after it has been created. See `Creating an Audience Export `__ for an introduction to Audience Exports with examples. Audience Export APIs have some methods at alpha and other methods at beta stability. The intention is to advance methods to beta stability after some feedback and adoption. To give your feedback on this API, complete the `Google Analytics Audience Export API Feedback `__ form. .. 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.analytics import data_v1beta def sample_get_audience_export(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.GetAudienceExportRequest( name="name_value", ) # Make the request response = client.get_audience_export(request=request) # Handle the response print(response) Args: request (Union[google.analytics.data_v1beta.types.GetAudienceExportRequest, dict]): The request object. A request to retrieve configuration metadata about a specific audience export. name (str): Required. The audience export resource name. Format: ``properties/{property}/audienceExports/{audience_export}`` 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.types.AudienceExport: An audience export is a list of users in an audience at the time of the list's creation. One audience may have multiple audience exports created for different days. """ # 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. flattened_params = [name] has_flattened_params = ( len([param for param in flattened_params if param is not None]) > 0 ) 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, analytics_data_api.GetAudienceExportRequest): request = analytics_data_api.GetAudienceExportRequest(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_audience_export] # 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_audience_exports( self, request: Optional[ Union[analytics_data_api.ListAudienceExportsRequest, dict] ] = None, *, parent: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, Union[str, bytes]]] = (), ) -> pagers.ListAudienceExportsPager: r"""Lists all audience exports for a property. This method can be used for you to find and reuse existing audience exports rather than creating unnecessary new audience exports. The same audience can have multiple audience exports that represent the export of users that were in an audience on different days. See `Creating an Audience Export `__ for an introduction to Audience Exports with examples. Audience Export APIs have some methods at alpha and other methods at beta stability. The intention is to advance methods to beta stability after some feedback and adoption. To give your feedback on this API, complete the `Google Analytics Audience Export API Feedback `__ form. .. 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.analytics import data_v1beta def sample_list_audience_exports(): # Create a client client = data_v1beta.BetaAnalyticsDataClient() # Initialize request argument(s) request = data_v1beta.ListAudienceExportsRequest( parent="parent_value", ) # Make the request page_result = client.list_audience_exports(request=request) # Handle the response for response in page_result: print(response) Args: request (Union[google.analytics.data_v1beta.types.ListAudienceExportsRequest, dict]): The request object. A request to list all audience exports for a property. parent (str): Required. All audience exports for this property will be listed in the response. Format: ``properties/{property}`` 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, Union[str, bytes]]]): Key/value pairs which should be sent along with the request as metadata. Normally, each value must be of type `str`, but for metadata keys ending with the suffix `-bin`, the corresponding values must be of type `bytes`. Returns: google.analytics.data_v1beta.services.beta_analytics_data.pagers.ListAudienceExportsPager: A list of all audience exports for a property. 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. flattened_params = [parent] has_flattened_params = ( len([param for param in flattened_params if param is not None]) > 0 ) 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, analytics_data_api.ListAudienceExportsRequest): request = analytics_data_api.ListAudienceExportsRequest(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_audience_exports] # 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.ListAudienceExportsPager( method=rpc, request=request, response=response, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response def __enter__(self) -> "BetaAnalyticsDataClient": 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() DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=package_version.__version__ ) if hasattr(DEFAULT_CLIENT_INFO, "protobuf_runtime_version"): # pragma: NO COVER DEFAULT_CLIENT_INFO.protobuf_runtime_version = google.protobuf.__version__ __all__ = ("BetaAnalyticsDataClient",)