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.types.data

# -*- coding: utf-8 -*-
# Copyright 2020 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.
#
import proto  # type: ignore


__protobuf__ = proto.module(
    package="google.analytics.data.v1alpha",
    manifest={
        "MetricAggregation",
        "MetricType",
        "DateRange",
        "Entity",
        "Dimension",
        "DimensionExpression",
        "Metric",
        "FilterExpression",
        "FilterExpressionList",
        "Filter",
        "OrderBy",
        "Pivot",
        "CohortSpec",
        "Cohort",
        "CohortsRange",
        "CohortReportSettings",
        "ResponseMetaData",
        "DimensionHeader",
        "MetricHeader",
        "PivotHeader",
        "PivotDimensionHeader",
        "Row",
        "DimensionValue",
        "MetricValue",
        "NumericValue",
        "PropertyQuota",
        "QuotaStatus",
        "DimensionMetadata",
        "MetricMetadata",
    },
)


[docs]class MetricAggregation(proto.Enum): r"""Represents aggregation of metrics.""" METRIC_AGGREGATION_UNSPECIFIED = 0 TOTAL = 1 MINIMUM = 5 MAXIMUM = 6 COUNT = 4
[docs]class MetricType(proto.Enum): r"""A metric's value type.""" METRIC_TYPE_UNSPECIFIED = 0 TYPE_INTEGER = 1 TYPE_FLOAT = 2 TYPE_SECONDS = 4 TYPE_MILLISECONDS = 5 TYPE_MINUTES = 6 TYPE_HOURS = 7 TYPE_STANDARD = 8 TYPE_CURRENCY = 9 TYPE_FEET = 10 TYPE_MILES = 11 TYPE_METERS = 12 TYPE_KILOMETERS = 13
[docs]class DateRange(proto.Message): r"""A contiguous set of days: startDate, startDate + 1, ..., endDate. Requests are allowed up to 4 date ranges. Attributes: start_date (str): The inclusive start date for the query in the format ``YYYY-MM-DD``. Cannot be after ``end_date``. The format ``NdaysAgo``, ``yesterday``, or ``today`` is also accepted, and in that case, the date is inferred based on the property's reporting time zone. end_date (str): The inclusive end date for the query in the format ``YYYY-MM-DD``. Cannot be before ``start_date``. The format ``NdaysAgo``, ``yesterday``, or ``today`` is also accepted, and in that case, the date is inferred based on the property's reporting time zone. name (str): Assigns a name to this date range. The dimension ``dateRange`` is valued to this name in a report response. If set, cannot begin with ``date_range_`` or ``RESERVED_``. If not set, date ranges are named by their zero based index in the request: ``date_range_0``, ``date_range_1``, etc. """ start_date = proto.Field(proto.STRING, number=1,) end_date = proto.Field(proto.STRING, number=2,) name = proto.Field(proto.STRING, number=3,)
[docs]class Entity(proto.Message): r"""The unique identifier of the property whose events are tracked. Attributes: property_id (str): A Google Analytics GA4 property id. To learn more, see `where to find your Property ID <https://developers.google.com/analytics/devguides/reporting/data/v1/property-id>`__. """ property_id = proto.Field(proto.STRING, number=1,)
[docs]class Dimension(proto.Message): r"""Dimensions are attributes of your data. For example, the dimension city indicates the city from which an event originates. Dimension values in report responses are strings; for example, city could be "Paris" or "New York". Requests are allowed up to 8 dimensions. Attributes: name (str): The name of the dimension. See the `API Dimensions <https://developers.google.com/analytics/devguides/reporting/data/v1/api-schema#dimensions>`__ for the list of dimension names. If ``dimensionExpression`` is specified, ``name`` can be any string that you would like. For example if a ``dimensionExpression`` concatenates ``country`` and ``city``, you could call that dimension ``countryAndCity``. Dimensions are referenced by ``name`` in ``dimensionFilter``, ``orderBys``, ``dimensionExpression``, and ``pivots``. dimension_expression (google.analytics.data_v1alpha.types.DimensionExpression): One dimension can be the result of an expression of multiple dimensions. For example, dimension "country, city": concatenate(country, ", ", city). """ name = proto.Field(proto.STRING, number=1,) dimension_expression = proto.Field( proto.MESSAGE, number=2, message="DimensionExpression", )
[docs]class DimensionExpression(proto.Message): r"""Used to express a dimension which is the result of a formula of multiple dimensions. Example usages: 1) lower_case(dimension) 2) concatenate(dimension1, symbol, dimension2). Attributes: lower_case (google.analytics.data_v1alpha.types.DimensionExpression.CaseExpression): Used to convert a dimension value to lower case. upper_case (google.analytics.data_v1alpha.types.DimensionExpression.CaseExpression): Used to convert a dimension value to upper case. concatenate (google.analytics.data_v1alpha.types.DimensionExpression.ConcatenateExpression): Used to combine dimension values to a single dimension. For example, dimension "country, city": concatenate(country, ", ", city). """
[docs] class CaseExpression(proto.Message): r"""Used to convert a dimension value to a single case. Attributes: dimension_name (str): Name of a dimension. The name must refer back to a name in dimensions field of the request. """ dimension_name = proto.Field(proto.STRING, number=1,)
[docs] class ConcatenateExpression(proto.Message): r"""Used to combine dimension values to a single dimension. Attributes: dimension_names (Sequence[str]): Names of dimensions. The names must refer back to names in the dimensions field of the request. delimiter (str): The delimiter placed between dimension names. Delimiters are often single characters such as "|" or "," but can be longer strings. If a dimension value contains the delimiter, both will be present in response with no distinction. For example if dimension 1 value = "US,FR", dimension 2 value = "JP", and delimiter = ",", then the response will contain "US,FR,JP". """ dimension_names = proto.RepeatedField(proto.STRING, number=1,) delimiter = proto.Field(proto.STRING, number=2,)
lower_case = proto.Field( proto.MESSAGE, number=4, oneof="one_expression", message=CaseExpression, ) upper_case = proto.Field( proto.MESSAGE, number=5, oneof="one_expression", message=CaseExpression, ) concatenate = proto.Field( proto.MESSAGE, number=6, oneof="one_expression", message=ConcatenateExpression, )
[docs]class Metric(proto.Message): r"""The quantitative measurements of a report. For example, the metric ``eventCount`` is the total number of events. Requests are allowed up to 10 metrics. Attributes: name (str): The name of the metric. See the `API Metrics <https://developers.google.com/analytics/devguides/reporting/data/v1/api-schema#metrics>`__ for the list of metric names. If ``expression`` is specified, ``name`` can be any string that you would like. For example if ``expression`` is ``screenPageViews/sessions``, you could call that metric's name = ``viewsPerSession``. Metrics are referenced by ``name`` in ``metricFilter``, ``orderBys``, and metric ``expression``. expression (str): A mathematical expression for derived metrics. For example, the metric Event count per user is ``eventCount/totalUsers``. invisible (bool): Indicates if a metric is invisible in the report response. If a metric is invisible, the metric will not produce a column in the response, but can be used in ``metricFilter``, ``orderBys``, or a metric ``expression``. """ name = proto.Field(proto.STRING, number=1,) expression = proto.Field(proto.STRING, number=2,) invisible = proto.Field(proto.BOOL, number=3,)
[docs]class FilterExpression(proto.Message): r"""To express dimension or metric filters. The fields in the same FilterExpression need to be either all dimensions or all metrics. Attributes: and_group (google.analytics.data_v1alpha.types.FilterExpressionList): The FilterExpressions in and_group have an AND relationship. or_group (google.analytics.data_v1alpha.types.FilterExpressionList): The FilterExpressions in or_group have an OR relationship. not_expression (google.analytics.data_v1alpha.types.FilterExpression): The FilterExpression is NOT of not_expression. filter (google.analytics.data_v1alpha.types.Filter): A primitive filter. All fields in filter in same FilterExpression needs to be either all dimensions or metrics. """ and_group = proto.Field( proto.MESSAGE, number=1, oneof="expr", message="FilterExpressionList", ) or_group = proto.Field( proto.MESSAGE, number=2, oneof="expr", message="FilterExpressionList", ) not_expression = proto.Field( proto.MESSAGE, number=3, oneof="expr", message="FilterExpression", ) filter = proto.Field(proto.MESSAGE, number=4, oneof="expr", message="Filter",)
[docs]class FilterExpressionList(proto.Message): r"""A list of filter expressions. Attributes: expressions (Sequence[google.analytics.data_v1alpha.types.FilterExpression]): A list of filter expressions. """ expressions = proto.RepeatedField( proto.MESSAGE, number=1, message="FilterExpression", )
[docs]class Filter(proto.Message): r"""An expression to filter dimension or metric values. Attributes: field_name (str): The dimension name or metric name. Must be a name defined in dimensions or metrics. null_filter (bool): A filter for null values. If True, a null dimension value is matched by this filter. Null filter is commonly used inside a NOT filter expression. For example, a NOT expression of a null filter removes rows when a dimension is null. string_filter (google.analytics.data_v1alpha.types.Filter.StringFilter): Strings related filter. in_list_filter (google.analytics.data_v1alpha.types.Filter.InListFilter): A filter for in list values. numeric_filter (google.analytics.data_v1alpha.types.Filter.NumericFilter): A filter for numeric or date values. between_filter (google.analytics.data_v1alpha.types.Filter.BetweenFilter): A filter for two values. """
[docs] class StringFilter(proto.Message): r"""The filter for string Attributes: match_type (google.analytics.data_v1alpha.types.Filter.StringFilter.MatchType): The match type for this filter. value (str): The string value used for the matching. case_sensitive (bool): If true, the string value is case sensitive. """
[docs] class MatchType(proto.Enum): r"""The match type of a string filter""" MATCH_TYPE_UNSPECIFIED = 0 EXACT = 1 BEGINS_WITH = 2 ENDS_WITH = 3 CONTAINS = 4 FULL_REGEXP = 5 PARTIAL_REGEXP = 6
match_type = proto.Field( proto.ENUM, number=1, enum="Filter.StringFilter.MatchType", ) value = proto.Field(proto.STRING, number=2,) case_sensitive = proto.Field(proto.BOOL, number=3,)
[docs] class InListFilter(proto.Message): r"""The result needs to be in a list of string values. Attributes: values (Sequence[str]): The list of string values. Must be non-empty. case_sensitive (bool): If true, the string value is case sensitive. """ values = proto.RepeatedField(proto.STRING, number=1,) case_sensitive = proto.Field(proto.BOOL, number=2,)
[docs] class NumericFilter(proto.Message): r"""Filters for numeric or date values. Attributes: operation (google.analytics.data_v1alpha.types.Filter.NumericFilter.Operation): The operation type for this filter. value (google.analytics.data_v1alpha.types.NumericValue): A numeric value or a date value. """
[docs] class Operation(proto.Enum): r"""The operation applied to a numeric filter""" OPERATION_UNSPECIFIED = 0 EQUAL = 1 LESS_THAN = 2 LESS_THAN_OR_EQUAL = 3 GREATER_THAN = 4 GREATER_THAN_OR_EQUAL = 5
operation = proto.Field( proto.ENUM, number=1, enum="Filter.NumericFilter.Operation", ) value = proto.Field(proto.MESSAGE, number=2, message="NumericValue",)
[docs] class BetweenFilter(proto.Message): r"""To express that the result needs to be between two numbers (inclusive). Attributes: from_value (google.analytics.data_v1alpha.types.NumericValue): Begins with this number. to_value (google.analytics.data_v1alpha.types.NumericValue): Ends with this number. """ from_value = proto.Field(proto.MESSAGE, number=1, message="NumericValue",) to_value = proto.Field(proto.MESSAGE, number=2, message="NumericValue",)
field_name = proto.Field(proto.STRING, number=1,) null_filter = proto.Field(proto.BOOL, number=2, oneof="one_filter",) string_filter = proto.Field( proto.MESSAGE, number=3, oneof="one_filter", message=StringFilter, ) in_list_filter = proto.Field( proto.MESSAGE, number=4, oneof="one_filter", message=InListFilter, ) numeric_filter = proto.Field( proto.MESSAGE, number=5, oneof="one_filter", message=NumericFilter, ) between_filter = proto.Field( proto.MESSAGE, number=6, oneof="one_filter", message=BetweenFilter, )
[docs]class OrderBy(proto.Message): r"""The sort options. Attributes: metric (google.analytics.data_v1alpha.types.OrderBy.MetricOrderBy): Sorts results by a metric's values. dimension (google.analytics.data_v1alpha.types.OrderBy.DimensionOrderBy): Sorts results by a dimension's values. pivot (google.analytics.data_v1alpha.types.OrderBy.PivotOrderBy): Sorts results by a metric's values within a pivot column group. desc (bool): If true, sorts by descending order. """
[docs] class MetricOrderBy(proto.Message): r"""Sorts by metric values. Attributes: metric_name (str): A metric name in the request to order by. """ metric_name = proto.Field(proto.STRING, number=1,)
[docs] class DimensionOrderBy(proto.Message): r"""Sorts by dimension values. Attributes: dimension_name (str): A dimension name in the request to order by. order_type (google.analytics.data_v1alpha.types.OrderBy.DimensionOrderBy.OrderType): Controls the rule for dimension value ordering. """
[docs] class OrderType(proto.Enum): r"""Rule to order the string dimension values by.""" ORDER_TYPE_UNSPECIFIED = 0 ALPHANUMERIC = 1 CASE_INSENSITIVE_ALPHANUMERIC = 2 NUMERIC = 3
dimension_name = proto.Field(proto.STRING, number=1,) order_type = proto.Field( proto.ENUM, number=2, enum="OrderBy.DimensionOrderBy.OrderType", )
[docs] class PivotOrderBy(proto.Message): r"""Sorts by a pivot column group. Attributes: metric_name (str): In the response to order by, order rows by this column. Must be a metric name from the request. pivot_selections (Sequence[google.analytics.data_v1alpha.types.OrderBy.PivotOrderBy.PivotSelection]): Used to select a dimension name and value pivot. If multiple pivot selections are given, the sort occurs on rows where all pivot selection dimension name and value pairs match the row's dimension name and value pair. """
[docs] class PivotSelection(proto.Message): r"""A pair of dimension names and values. Rows with this dimension pivot pair are ordered by the metric's value. For example if pivots = {{"browser", "Chrome"}} and metric_name = "Sessions", then the rows will be sorted based on Sessions in Chrome. :: ---------|----------|----------------|----------|---------------- | Chrome | Chrome | Safari | Safari ---------|----------|----------------|----------|---------------- Country | Sessions | Pages/Sessions | Sessions | Pages/Sessions ---------|----------|----------------|----------|---------------- US | 2 | 2 | 3 | 1 ---------|----------|----------------|----------|---------------- Canada | 3 | 1 | 4 | 1 ---------|----------|----------------|----------|---------------- Attributes: dimension_name (str): Must be a dimension name from the request. dimension_value (str): Order by only when the named dimension is this value. """ dimension_name = proto.Field(proto.STRING, number=1,) dimension_value = proto.Field(proto.STRING, number=2,)
metric_name = proto.Field(proto.STRING, number=1,) pivot_selections = proto.RepeatedField( proto.MESSAGE, number=2, message="OrderBy.PivotOrderBy.PivotSelection", )
metric = proto.Field( proto.MESSAGE, number=1, oneof="one_order_by", message=MetricOrderBy, ) dimension = proto.Field( proto.MESSAGE, number=2, oneof="one_order_by", message=DimensionOrderBy, ) pivot = proto.Field( proto.MESSAGE, number=3, oneof="one_order_by", message=PivotOrderBy, ) desc = proto.Field(proto.BOOL, number=4,)
[docs]class Pivot(proto.Message): r"""Describes the visible dimension columns and rows in the report response. Attributes: field_names (Sequence[str]): Dimension names for visible columns in the report response. Including "dateRange" produces a date range column; for each row in the response, dimension values in the date range column will indicate the corresponding date range from the request. order_bys (Sequence[google.analytics.data_v1alpha.types.OrderBy]): Specifies how dimensions are ordered in the pivot. In the first Pivot, the OrderBys determine Row and PivotDimensionHeader ordering; in subsequent Pivots, the OrderBys determine only PivotDimensionHeader ordering. Dimensions specified in these OrderBys must be a subset of Pivot.field_names. offset (int): The row count of the start row. The first row is counted as row 0. limit (int): The number of rows to return in this pivot. If unspecified, 10 rows are returned. If -1, all rows are returned. metric_aggregations (Sequence[google.analytics.data_v1alpha.types.MetricAggregation]): Aggregate the metrics by dimensions in this pivot using the specified metric_aggregations. """ field_names = proto.RepeatedField(proto.STRING, number=1,) order_bys = proto.RepeatedField(proto.MESSAGE, number=2, message="OrderBy",) offset = proto.Field(proto.INT64, number=3,) limit = proto.Field(proto.INT64, number=4,) metric_aggregations = proto.RepeatedField( proto.ENUM, number=5, enum="MetricAggregation", )
[docs]class CohortSpec(proto.Message): r"""Specification of cohorts for a cohort report. Cohort reports can be used for example to create a time series of user retention for the cohort. For example, you could select the cohort of users that were acquired in the first week of September and follow that cohort for the next six weeks. Selecting the users acquired in the first week of September cohort is specified in the ``cohort`` object. Following that cohort for the next six weeks is specified in the ``cohortsRange`` object. The report response could show a weekly time series where say your app has retained 60% of this cohort after three weeks and 25% of this cohort after six weeks. These two percentages can be calculated by the metric ``cohortActiveUsers/cohortTotalUsers`` and will be separate rows in the report. Attributes: cohorts (Sequence[google.analytics.data_v1alpha.types.Cohort]): Defines the selection criteria to group users into cohorts. Most cohort reports define only a single cohort. If multiple cohorts are specified, each cohort can be recognized in the report by their name. cohorts_range (google.analytics.data_v1alpha.types.CohortsRange): Cohort reports follow cohorts over an extended reporting date range. This range specifies an offset duration to follow the cohorts over. cohort_report_settings (google.analytics.data_v1alpha.types.CohortReportSettings): Optional settings for a cohort report. """ cohorts = proto.RepeatedField(proto.MESSAGE, number=1, message="Cohort",) cohorts_range = proto.Field(proto.MESSAGE, number=2, message="CohortsRange",) cohort_report_settings = proto.Field( proto.MESSAGE, number=3, message="CohortReportSettings", )
[docs]class Cohort(proto.Message): r"""Defines a cohort selection criteria. A cohort is a group of users who share a common characteristic. For example, users with the same ``firstTouchDate`` belong to the same cohort. Attributes: name (str): Assigns a name to this cohort. The dimension ``cohort`` is valued to this name in a report response. If set, cannot begin with ``cohort_`` or ``RESERVED_``. If not set, cohorts are named by their zero based index ``cohort_0``, ``cohort_1``, etc. dimension (str): Dimension used by the cohort. Required and only supports ``firstTouchDate``. date_range (google.analytics.data_v1alpha.types.DateRange): The cohort selects users whose first touch date is between start date and end date defined in the ``dateRange``. This ``dateRange`` does not specify the full date range of event data that is present in a cohort report. In a cohort report, this ``dateRange`` is extended by the granularity and offset present in the ``cohortsRange``; event data for the extended reporting date range is present in a cohort report. In a cohort request, this ``dateRange`` is required and the ``dateRanges`` in the ``RunReportRequest`` or ``RunPivotReportRequest`` must be unspecified. This ``dateRange`` should generally be aligned with the cohort's granularity. If ``CohortsRange`` uses daily granularity, this ``dateRange`` can be a single day. If ``CohortsRange`` uses weekly granularity, this ``dateRange`` can be aligned to a week boundary, starting at Sunday and ending Saturday. If ``CohortsRange`` uses monthly granularity, this ``dateRange`` can be aligned to a month, starting at the first and ending on the last day of the month. """ name = proto.Field(proto.STRING, number=1,) dimension = proto.Field(proto.STRING, number=2,) date_range = proto.Field(proto.MESSAGE, number=3, message="DateRange",)
[docs]class CohortsRange(proto.Message): r"""Configures the extended reporting date range for a cohort report. Specifies an offset duration to follow the cohorts over. Attributes: granularity (google.analytics.data_v1alpha.types.CohortsRange.Granularity): The granularity used to interpret the ``startOffset`` and ``endOffset`` for the extended reporting date range for a cohort report. start_offset (int): ``startOffset`` specifies the start date of the extended reporting date range for a cohort report. ``startOffset`` is commonly set to 0 so that reports contain data from the acquisition of the cohort forward. If ``granularity`` is ``DAILY``, the ``startDate`` of the extended reporting date range is ``startDate`` of the cohort plus ``startOffset`` days. If ``granularity`` is ``WEEKLY``, the ``startDate`` of the extended reporting date range is ``startDate`` of the cohort plus ``startOffset * 7`` days. If ``granularity`` is ``MONTHLY``, the ``startDate`` of the extended reporting date range is ``startDate`` of the cohort plus ``startOffset * 30`` days. end_offset (int): ``endOffset`` specifies the end date of the extended reporting date range for a cohort report. ``endOffset`` can be any positive integer but is commonly set to 5 to 10 so that reports contain data on the cohort for the next several granularity time periods. If ``granularity`` is ``DAILY``, the ``endDate`` of the extended reporting date range is ``endDate`` of the cohort plus ``endOffset`` days. If ``granularity`` is ``WEEKLY``, the ``endDate`` of the extended reporting date range is ``endDate`` of the cohort plus ``endOffset * 7`` days. If ``granularity`` is ``MONTHLY``, the ``endDate`` of the extended reporting date range is ``endDate`` of the cohort plus ``endOffset * 30`` days. """
[docs] class Granularity(proto.Enum): r"""The granularity used to interpret the ``startOffset`` and ``endOffset`` for the extended reporting date range for a cohort report. """ GRANULARITY_UNSPECIFIED = 0 DAILY = 1 WEEKLY = 2 MONTHLY = 3
granularity = proto.Field(proto.ENUM, number=1, enum=Granularity,) start_offset = proto.Field(proto.INT32, number=2,) end_offset = proto.Field(proto.INT32, number=3,)
[docs]class CohortReportSettings(proto.Message): r"""Optional settings of a cohort report. Attributes: accumulate (bool): If true, accumulates the result from first touch day to the end day. Not supported in ``RunReportRequest``. """ accumulate = proto.Field(proto.BOOL, number=1,)
[docs]class ResponseMetaData(proto.Message): r"""Response's metadata carrying additional information about the report content. Attributes: data_loss_from_other_row (bool): If true, indicates some buckets of dimension combinations are rolled into "(other)" row. This can happen for high cardinality reports. """ data_loss_from_other_row = proto.Field(proto.BOOL, number=3,)
[docs]class DimensionHeader(proto.Message): r"""Describes a dimension column in the report. Dimensions requested in a report produce column entries within rows and DimensionHeaders. However, dimensions used exclusively within filters or expressions do not produce columns in a report; correspondingly, those dimensions do not produce headers. Attributes: name (str): The dimension's name. """ name = proto.Field(proto.STRING, number=1,)
[docs]class MetricHeader(proto.Message): r"""Describes a metric column in the report. Visible metrics requested in a report produce column entries within rows and MetricHeaders. However, metrics used exclusively within filters or expressions do not produce columns in a report; correspondingly, those metrics do not produce headers. Attributes: name (str): The metric's name. type_ (google.analytics.data_v1alpha.types.MetricType): The metric's data type. """ name = proto.Field(proto.STRING, number=1,) type_ = proto.Field(proto.ENUM, number=2, enum="MetricType",)
[docs]class PivotHeader(proto.Message): r"""Dimensions' values in a single pivot. Attributes: pivot_dimension_headers (Sequence[google.analytics.data_v1alpha.types.PivotDimensionHeader]): The size is the same as the cardinality of the corresponding dimension combinations. row_count (int): The cardinality of the pivot as if offset = 0 and limit = -1. The total number of rows for this pivot's fields regardless of how the parameters offset and limit are specified in the request. """ pivot_dimension_headers = proto.RepeatedField( proto.MESSAGE, number=1, message="PivotDimensionHeader", ) row_count = proto.Field(proto.INT32, number=2,)
[docs]class PivotDimensionHeader(proto.Message): r"""Summarizes dimension values from a row for this pivot. Attributes: dimension_values (Sequence[google.analytics.data_v1alpha.types.DimensionValue]): Values of multiple dimensions in a pivot. """ dimension_values = proto.RepeatedField( proto.MESSAGE, number=1, message="DimensionValue", )
[docs]class Row(proto.Message): r"""Report data for each row. For example if RunReportRequest contains: .. code:: none "dimensions": [ { "name": "eventName" }, { "name": "countryId" } ], "metrics": [ { "name": "eventCount" } ] One row with 'in_app_purchase' as the eventName, 'JP' as the countryId, and 15 as the eventCount, would be: .. code:: none "dimensionValues": [ { "value": "in_app_purchase" }, { "value": "JP" } ], "metricValues": [ { "value": "15" } ] Attributes: dimension_values (Sequence[google.analytics.data_v1alpha.types.DimensionValue]): List of requested dimension values. In a PivotReport, dimension_values are only listed for dimensions included in a pivot. metric_values (Sequence[google.analytics.data_v1alpha.types.MetricValue]): List of requested visible metric values. """ dimension_values = proto.RepeatedField( proto.MESSAGE, number=1, message="DimensionValue", ) metric_values = proto.RepeatedField(proto.MESSAGE, number=2, message="MetricValue",)
[docs]class DimensionValue(proto.Message): r"""The value of a dimension. Attributes: value (str): Value as a string if the dimension type is a string. """ value = proto.Field(proto.STRING, number=1, oneof="one_value",)
[docs]class MetricValue(proto.Message): r"""The value of a metric. Attributes: value (str): Measurement value. See MetricHeader for type. """ value = proto.Field(proto.STRING, number=4, oneof="one_value",)
[docs]class NumericValue(proto.Message): r"""To represent a number. Attributes: int64_value (int): Integer value double_value (float): Double value """ int64_value = proto.Field(proto.INT64, number=1, oneof="one_value",) double_value = proto.Field(proto.DOUBLE, number=2, oneof="one_value",)
[docs]class PropertyQuota(proto.Message): r"""Current state of all quotas for this Analytics Property. If any quota for a property is exhausted, all requests to that property will return Resource Exhausted errors. Attributes: tokens_per_day (google.analytics.data_v1alpha.types.QuotaStatus): Standard Analytics Properties can use up to 25,000 tokens per day; Analytics 360 Properties can use 250,000 tokens per day. Most requests consume fewer than 10 tokens. tokens_per_hour (google.analytics.data_v1alpha.types.QuotaStatus): Standard Analytics Properties can use up to 5,000 tokens per day; Analytics 360 Properties can use 50,000 tokens per day. An API request consumes a single number of tokens, and that number is deducted from both the hourly and daily quotas. concurrent_requests (google.analytics.data_v1alpha.types.QuotaStatus): Standard Analytics Properties can send up to 10 concurrent requests; Analytics 360 Properties can use up to 50 concurrent requests. server_errors_per_project_per_hour (google.analytics.data_v1alpha.types.QuotaStatus): Standard Analytics Properties and cloud project pairs can have up to 10 server errors per hour; Analytics 360 Properties and cloud project pairs can have up to 50 server errors per hour. """ tokens_per_day = proto.Field(proto.MESSAGE, number=1, message="QuotaStatus",) tokens_per_hour = proto.Field(proto.MESSAGE, number=2, message="QuotaStatus",) concurrent_requests = proto.Field(proto.MESSAGE, number=3, message="QuotaStatus",) server_errors_per_project_per_hour = proto.Field( proto.MESSAGE, number=4, message="QuotaStatus", )
[docs]class QuotaStatus(proto.Message): r"""Current state for a particular quota group. Attributes: consumed (int): Quota consumed by this request. remaining (int): Quota remaining after this request. """ consumed = proto.Field(proto.INT32, number=1,) remaining = proto.Field(proto.INT32, number=2,)
[docs]class DimensionMetadata(proto.Message): r"""Explains a dimension. Attributes: api_name (str): This dimension's name. Useable in `Dimension <#Dimension>`__'s ``name``. For example, ``eventName``. ui_name (str): This dimension's name within the Google Analytics user interface. For example, ``Event name``. description (str): Description of how this dimension is used and calculated. deprecated_api_names (Sequence[str]): Still usable but deprecated names for this dimension. If populated, this dimension is available by either ``apiName`` or one of ``deprecatedApiNames`` for a period of time. After the deprecation period, the dimension will be available only by ``apiName``. custom_definition (bool): True if the dimension is a custom dimension for this property. """ api_name = proto.Field(proto.STRING, number=1,) ui_name = proto.Field(proto.STRING, number=2,) description = proto.Field(proto.STRING, number=3,) deprecated_api_names = proto.RepeatedField(proto.STRING, number=4,) custom_definition = proto.Field(proto.BOOL, number=5,)
[docs]class MetricMetadata(proto.Message): r"""Explains a metric. Attributes: api_name (str): A metric name. Useable in `Metric <#Metric>`__'s ``name``. For example, ``eventCount``. ui_name (str): This metric's name within the Google Analytics user interface. For example, ``Event count``. description (str): Description of how this metric is used and calculated. deprecated_api_names (Sequence[str]): Still usable but deprecated names for this metric. If populated, this metric is available by either ``apiName`` or one of ``deprecatedApiNames`` for a period of time. After the deprecation period, the metric will be available only by ``apiName``. type_ (google.analytics.data_v1alpha.types.MetricType): The type of this metric. expression (str): The mathematical expression for this derived metric. Can be used in `Metric <#Metric>`__'s ``expression`` field for equivalent reports. Most metrics are not expressions, and for non-expressions, this field is empty. custom_definition (bool): True if the metric is a custom metric for this property. """ api_name = proto.Field(proto.STRING, number=1,) ui_name = proto.Field(proto.STRING, number=2,) description = proto.Field(proto.STRING, number=3,) deprecated_api_names = proto.RepeatedField(proto.STRING, number=4,) type_ = proto.Field(proto.ENUM, number=5, enum="MetricType",) expression = proto.Field(proto.STRING, number=6,) custom_definition = proto.Field(proto.BOOL, number=7,)
__all__ = tuple(sorted(__protobuf__.manifest))