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_v1beta.services.beta_analytics_data.client
# -*- coding: utf-8 -*-
# Copyright 2022 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, Optional, Sequence, Tuple, Type, Union
import pkg_resources
from google.api_core import client_options as client_options_lib
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry as retries
from google.auth import credentials as ga_credentials # type: ignore
from google.auth.transport import mtls # type: ignore
from google.auth.transport.grpc import SslCredentials # type: ignore
from google.auth.exceptions import MutualTLSChannelError # type: ignore
from google.oauth2 import service_account # type: ignore
try:
OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault]
except AttributeError: # pragma: NO COVER
OptionalRetry = Union[retries.Retry, object] # type: ignore
from google.analytics.data_v1beta.types import analytics_data_api
from google.analytics.data_v1beta.types import data
from .transports.base import BetaAnalyticsDataTransport, DEFAULT_CLIENT_INFO
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: 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()))
[docs]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<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:
BetaAnalyticsDataClient: 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:
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
[docs] @staticmethod
def metadata_path(
property: str,
) -> str:
"""Returns a fully-qualified metadata string."""
return "properties/{property}/metadata".format(
property=property,
)
[docs] @staticmethod
def parse_metadata_path(path: str) -> Dict[str, str]:
"""Parses a metadata path into its component segments."""
m = re.match(r"^properties/(?P<property>.+?)/metadata$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_billing_account_path(
billing_account: str,
) -> str:
"""Returns a fully-qualified billing_account string."""
return "billingAccounts/{billing_account}".format(
billing_account=billing_account,
)
[docs] @staticmethod
def parse_common_billing_account_path(path: str) -> Dict[str, str]:
"""Parse a billing_account path into its component segments."""
m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", 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 variabel 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: Union[str, BetaAnalyticsDataTransport, None] = None,
client_options: Optional[client_options_lib.ClientOptions] = 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 (Union[str, BetaAnalyticsDataTransport]): The
transport to use. If set to None, a transport is chosen
automatically.
NOTE: "rest" transport functionality is currently in a
beta state (preview). We welcome your feedback via an
issue in this library's source repository.
client_options (google.api_core.client_options.ClientOptions): 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()
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, BetaAnalyticsDataTransport):
# transport is a BetaAnalyticsDataTransport 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_report(
self,
request: Union[analytics_data_api.RunReportRequest, dict] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> 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.
.. 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.RunReportResponse:
The response report table
corresponding to a request.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.RunReportRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def run_pivot_report(
self,
request: Union[analytics_data_api.RunPivotReportRequest, dict] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.RunPivotReportResponse:
The response pivot report table
corresponding to a pivot request.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.RunPivotReportRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def batch_run_reports(
self,
request: Union[analytics_data_api.BatchRunReportsRequest, dict] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> analytics_data_api.BatchRunReportsResponse:
r"""Returns multiple reports in a batch. All reports must
be for the same GA4 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.BatchRunReportsResponse:
The batch response containing
multiple reports.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.BatchRunReportsRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def batch_run_pivot_reports(
self,
request: Union[analytics_data_api.BatchRunPivotReportsRequest, dict] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> analytics_data_api.BatchRunPivotReportsResponse:
r"""Returns multiple pivot reports in a batch. All
reports must be for the same GA4 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.BatchRunPivotReportsResponse:
The batch response containing
multiple pivot reports.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.BatchRunPivotReportsRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def get_metadata(
self,
request: Union[analytics_data_api.GetMetadataRequest, dict] = None,
*,
name: str = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> 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 GA4 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 GA4
Property identifier. To learn more, see `where to find
your Property
ID <https://developers.google.com/analytics/devguides/reporting/data/v1/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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.Metadata:
The dimensions and metrics 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.
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.GetMetadataRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def run_realtime_report(
self,
request: Union[analytics_data_api.RunRealtimeReportRequest, dict] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> analytics_data_api.RunRealtimeReportResponse:
r"""The Google Analytics Realtime API returns a
customized report of realtime event data for your
property. These reports show events and usage from the
last 30 minutes.
.. 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.RunRealtimeReportResponse:
The response realtime report table
corresponding to a request.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.RunRealtimeReportRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def check_compatibility(
self,
request: Union[analytics_data_api.CheckCompatibilityRequest, dict] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> 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, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.analytics.data_v1beta.types.CheckCompatibilityResponse:
The compatibility response with the
compatibility of each dimension &
metric.
"""
# Create or coerce a protobuf request object.
# Minor optimization to avoid making a copy if the user passes
# in a analytics_data_api.CheckCompatibilityRequest.
# 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.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),)),
)
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
def __enter__(self):
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()
try:
DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
gapic_version=pkg_resources.get_distribution(
"google-analytics-data",
).version,
)
except pkg_resources.DistributionNotFound:
DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo()
__all__ = ("BetaAnalyticsDataClient",)
