As of January 1, 2020 this library no longer supports Python 2 on the latest released version.
Library versions released prior to that date will continue to be available. For more information please
visit Python 2 support on Google Cloud.
Source code for google.analytics.data_v1alpha.services.alpha_analytics_data.client
# -*- coding: utf-8 -*-
# Copyright 2023 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,
Mapping,
MutableMapping,
MutableSequence,
Optional,
Sequence,
Tuple,
Type,
Union,
cast,
)
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
from google.analytics.data_v1alpha import gapic_version as package_version
try:
OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault]
except AttributeError: # pragma: NO COVER
OptionalRetry = Union[retries.Retry, object] # type: ignore
from google.api_core import operation # type: ignore
from google.api_core import operation_async # type: ignore
from google.protobuf import timestamp_pb2 # type: ignore
from google.analytics.data_v1alpha.services.alpha_analytics_data import pagers
from google.analytics.data_v1alpha.types import analytics_data_api, data
from .transports.base import DEFAULT_CLIENT_INFO, AlphaAnalyticsDataTransport
from .transports.grpc import AlphaAnalyticsDataGrpcTransport
from .transports.grpc_asyncio import AlphaAnalyticsDataGrpcAsyncIOTransport
from .transports.rest import AlphaAnalyticsDataRestTransport
class AlphaAnalyticsDataClientMeta(type):
"""Metaclass for the AlphaAnalyticsData 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[AlphaAnalyticsDataTransport]]
_transport_registry["grpc"] = AlphaAnalyticsDataGrpcTransport
_transport_registry["grpc_asyncio"] = AlphaAnalyticsDataGrpcAsyncIOTransport
_transport_registry["rest"] = AlphaAnalyticsDataRestTransport
def get_transport_class(
cls,
label: Optional[str] = None,
) -> Type[AlphaAnalyticsDataTransport]:
"""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()))
[docs]class AlphaAnalyticsDataClient(metaclass=AlphaAnalyticsDataClientMeta):
"""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<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")
DEFAULT_ENDPOINT = "analyticsdata.googleapis.com"
DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore
DEFAULT_ENDPOINT
)
[docs] @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:
AlphaAnalyticsDataClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_info(info)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
[docs] @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:
AlphaAnalyticsDataClient: 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) -> AlphaAnalyticsDataTransport:
"""Returns the transport used by the client instance.
Returns:
AlphaAnalyticsDataTransport: The transport used by the client
instance.
"""
return self._transport
[docs] @staticmethod
def audience_list_path(
propertyId: str,
audienceListId: str,
) -> str:
"""Returns a fully-qualified audience_list string."""
return "properties/{propertyId}/audienceLists/{audienceListId}".format(
propertyId=propertyId,
audienceListId=audienceListId,
)
[docs] @staticmethod
def parse_audience_list_path(path: str) -> Dict[str, str]:
"""Parses a audience_list path into its component segments."""
m = re.match(
r"^properties/(?P<propertyId>.+?)/audienceLists/(?P<audienceListId>.+?)$",
path,
)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_billing_account_path(
billing_account: str,
) -> str:
"""Returns a fully-qualified billing_account string."""
return "billingAccounts/{billing_account}".format(
billing_account=billing_account,
)
[docs] @staticmethod
def parse_common_billing_account_path(path: str) -> Dict[str, str]:
"""Parse a billing_account path into its component segments."""
m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_folder_path(
folder: str,
) -> str:
"""Returns a fully-qualified folder string."""
return "folders/{folder}".format(
folder=folder,
)
[docs] @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>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_organization_path(
organization: str,
) -> str:
"""Returns a fully-qualified organization string."""
return "organizations/{organization}".format(
organization=organization,
)
[docs] @staticmethod
def parse_common_organization_path(path: str) -> Dict[str, str]:
"""Parse a organization path into its component segments."""
m = re.match(r"^organizations/(?P<organization>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_project_path(
project: str,
) -> str:
"""Returns a fully-qualified project string."""
return "projects/{project}".format(
project=project,
)
[docs] @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>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_location_path(
project: str,
location: str,
) -> str:
"""Returns a fully-qualified location string."""
return "projects/{project}/locations/{location}".format(
project=project,
location=location,
)
[docs] @staticmethod
def parse_common_location_path(path: str) -> Dict[str, str]:
"""Parse a location path into its component segments."""
m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path)
return m.groupdict() if m else {}
[docs] @classmethod
def get_mtls_endpoint_and_cert_source(
cls, client_options: Optional[client_options_lib.ClientOptions] = None
):
"""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.
"""
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
def __init__(
self,
*,
credentials: Optional[ga_credentials.Credentials] = None,
transport: Optional[Union[str, AlphaAnalyticsDataTransport]] = None,
client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) -> None:
"""Instantiates the alpha 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 (Union[str, AlphaAnalyticsDataTransport]): The
transport to use. 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. It won't take effect if a ``transport`` instance is provided.
(1) The ``api_endpoint`` property can be used to override the
default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT
environment variable can also be used to override the endpoint:
"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). However, the ``api_endpoint`` property takes
precedence if provided.
(2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
is "true", then the ``client_cert_source`` property can be used
to provide client certificate for mutual TLS 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.
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.
"""
if isinstance(client_options, dict):
client_options = client_options_lib.from_dict(client_options)
if client_options is None:
client_options = client_options_lib.ClientOptions()
client_options = cast(client_options_lib.ClientOptions, client_options)
api_endpoint, client_cert_source_func = self.get_mtls_endpoint_and_cert_source(
client_options
)
api_key_value = getattr(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.
if isinstance(transport, AlphaAnalyticsDataTransport):
# transport is a AlphaAnalyticsDataTransport instance.
if credentials or client_options.credentials_file or api_key_value:
raise ValueError(
"When providing a transport instance, "
"provide its credentials directly."
)
if client_options.scopes:
raise ValueError(
"When providing a transport instance, provide its scopes "
"directly."
)
self._transport = transport
else:
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 = type(self).get_transport_class(transport)
self._transport = Transport(
credentials=credentials,
credentials_file=client_options.credentials_file,
host=api_endpoint,
scopes=client_options.scopes,
client_cert_source_for_mtls=client_cert_source_func,
quota_project_id=client_options.quota_project_id,
client_info=client_info,
always_use_jwt_access=True,
api_audience=client_options.api_audience,
)
[docs] def run_funnel_report(
self,
request: Optional[
Union[analytics_data_api.RunFunnelReportRequest, dict]
] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> analytics_data_api.RunFunnelReportResponse:
r"""Returns a customized funnel report of your Google Analytics
event data. The data returned from the API is as a table with
columns for the requested dimensions and metrics.
Funnel exploration lets you visualize the steps your users take
to complete a task and quickly see how well they are succeeding
or failing at each step. For example, how do prospects become
shoppers and then become buyers? How do one time buyers become
repeat buyers? With this information, you can improve
inefficient or abandoned customer journeys. To learn more, see
`GA4 Funnel
Explorations <https://support.google.com/analytics/answer/9327974>`__.
This method is introduced at alpha stability with the intention
of gathering feedback on syntax and capabilities before entering
beta. To give your feedback on this API, complete the `Google
Analytics Data API Funnel Reporting
Feedback <https://docs.google.com/forms/d/e/1FAIpQLSdwOlQDJAUoBiIgUZZ3S_Lwi8gr7Bb0k1jhvc-DEg7Rol3UjA/viewform>`__.
.. 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_v1alpha
def sample_run_funnel_report():
# Create a client
client = data_v1alpha.AlphaAnalyticsDataClient()
# Initialize request argument(s)
request = data_v1alpha.RunFunnelReportRequest(
)
# Make the request
response = client.run_funnel_report(request=request)
# Handle the response
print(response)
Args:
request (Union[google.analytics.data_v1alpha.types.RunFunnelReportRequest, dict]):
The request object. The request for a funnel 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1alpha.types.RunFunnelReportResponse:
The funnel report response contains
two sub reports. The two sub reports are
different combinations of dimensions and
metrics.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.RunFunnelReportRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, analytics_data_api.RunFunnelReportRequest):
request = analytics_data_api.RunFunnelReportRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.run_funnel_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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def create_audience_list(
self,
request: Optional[
Union[analytics_data_api.CreateAudienceListRequest, dict]
] = None,
*,
parent: Optional[str] = None,
audience_list: Optional[analytics_data_api.AudienceList] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Creates an audience list for later retrieval. This method
quickly returns the audience list's resource name and initiates
a long running asynchronous request to form an audience list. To
list the users in an audience list, first create the audience
list through this method and then send the audience resource
name to the ``QueryAudienceList`` method.
An audience list is a snapshot of the users currently in the
audience at the time of audience list creation. Creating
audience lists 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 lists contain the users in each audience.
.. 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_v1alpha
def sample_create_audience_list():
# Create a client
client = data_v1alpha.AlphaAnalyticsDataClient()
# Initialize request argument(s)
audience_list = data_v1alpha.AudienceList()
audience_list.audience = "audience_value"
request = data_v1alpha.CreateAudienceListRequest(
parent="parent_value",
audience_list=audience_list,
)
# Make the request
operation = client.create_audience_list(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.analytics.data_v1alpha.types.CreateAudienceListRequest, dict]):
The request object. A request to create a new audience
list.
parent (str):
Required. The parent resource where this audience list
will be created. Format: ``properties/{propertyId}``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
audience_list (google.analytics.data_v1alpha.types.AudienceList):
Required. The audience list to
create.
This corresponds to the ``audience_list`` 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.analytics.data_v1alpha.types.AudienceList` An audience list is a list of users in an audience at the time of the list's
creation. One audience may have multiple audience
lists 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.
has_flattened_params = any([parent, audience_list])
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."
)
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.CreateAudienceListRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, analytics_data_api.CreateAudienceListRequest):
request = analytics_data_api.CreateAudienceListRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if audience_list is not None:
request.audience_list = audience_list
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.create_audience_list]
# 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),)),
)
# 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.AudienceList,
metadata_type=analytics_data_api.AudienceListMetadata,
)
# Done; return the response.
return response
[docs] def query_audience_list(
self,
request: Optional[
Union[analytics_data_api.QueryAudienceListRequest, 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]] = (),
) -> analytics_data_api.QueryAudienceListResponse:
r"""Retrieves an audience list of users. After creating an audience,
the users are not immediately available for listing. First, a
request to ``CreateAudienceList`` is necessary to create an
audience list of users, and then second, this method is used to
retrieve the users in 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.
.. 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_v1alpha
def sample_query_audience_list():
# Create a client
client = data_v1alpha.AlphaAnalyticsDataClient()
# Initialize request argument(s)
request = data_v1alpha.QueryAudienceListRequest(
)
# Make the request
response = client.query_audience_list(request=request)
# Handle the response
print(response)
Args:
request (Union[google.analytics.data_v1alpha.types.QueryAudienceListRequest, dict]):
The request object. A request to list users in an
audience list.
name (str):
The name of the audience list to retrieve users from.
Format:
``properties/{propertyId}/audienceLists/{audienceListId}``
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.analytics.data_v1alpha.types.QueryAudienceListResponse:
A list of users in an audience list.
"""
# 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."
)
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.QueryAudienceListRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, analytics_data_api.QueryAudienceListRequest):
request = analytics_data_api.QueryAudienceListRequest(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_list]
# 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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def get_audience_list(
self,
request: Optional[
Union[analytics_data_api.GetAudienceListRequest, 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]] = (),
) -> analytics_data_api.AudienceList:
r"""Gets configuration metadata about a specific audience
list. This method can be used to understand an audience
list after it has been created.
.. 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_v1alpha
def sample_get_audience_list():
# Create a client
client = data_v1alpha.AlphaAnalyticsDataClient()
# Initialize request argument(s)
request = data_v1alpha.GetAudienceListRequest(
name="name_value",
)
# Make the request
response = client.get_audience_list(request=request)
# Handle the response
print(response)
Args:
request (Union[google.analytics.data_v1alpha.types.GetAudienceListRequest, dict]):
The request object. A request to retrieve configuration
metadata about a specific audience list.
name (str):
Required. The audience list resource name. Format:
``properties/{propertyId}/audienceLists/{audienceListId}``
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.analytics.data_v1alpha.types.AudienceList:
An audience list is a list of users
in an audience at the time of the list's
creation. One audience may have multiple
audience lists 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.
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."
)
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.GetAudienceListRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, analytics_data_api.GetAudienceListRequest):
request = analytics_data_api.GetAudienceListRequest(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_list]
# 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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def list_audience_lists(
self,
request: Optional[
Union[analytics_data_api.ListAudienceListsRequest, 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.ListAudienceListsPager:
r"""Lists all audience lists for a property. This method
can be used for you to find and reuse existing audience
lists rather than creating unnecessary new audience
lists. The same audience can have multiple audience
lists that represent the list of users that were in an
audience on different days.
.. 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_v1alpha
def sample_list_audience_lists():
# Create a client
client = data_v1alpha.AlphaAnalyticsDataClient()
# Initialize request argument(s)
request = data_v1alpha.ListAudienceListsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_audience_lists(request=request)
# Handle the response
for response in page_result:
print(response)
Args:
request (Union[google.analytics.data_v1alpha.types.ListAudienceListsRequest, dict]):
The request object. A request to list all audience lists
for a property.
parent (str):
Required. All audience lists for this property will be
listed in the response. Format:
``properties/{propertyId}``
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.analytics.data_v1alpha.services.alpha_analytics_data.pagers.ListAudienceListsPager:
A list of all audience lists 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.
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."
)
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.ListAudienceListsRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, analytics_data_api.ListAudienceListsRequest):
request = analytics_data_api.ListAudienceListsRequest(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_lists]
# 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),)),
)
# 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.ListAudienceListsPager(
method=rpc,
request=request,
response=response,
metadata=metadata,
)
# Done; return the response.
return response
def __enter__(self) -> "AlphaAnalyticsDataClient":
return self
[docs] 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__
)
__all__ = ("AlphaAnalyticsDataClient",)
