roboto.domain.metrics.record

Module Contents

class roboto.domain.metrics.record.AggregateMetricRecord(/, **data)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:

data (Any)

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

A dictionary containing metadata about generic Pydantic models. The origin and args items map to the [__origin__][genericalias.__origin__] and [__args__][genericalias.__args__] attributes of [generic aliases][types-genericalias], and the parameter item maps to the __parameter__ attribute of generic classes.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

end_time: int

Exclusive end of this period bucket, in Unix-epoch nanoseconds (UTC).

metric_id: str

Identifier of the aggregated metric definition.

name: str

Name of the aggregated metric.

period: AggregationPeriod

Calendar bucket size used for this aggregation.

start_time: int

Inclusive start of this period bucket, in Unix-epoch nanoseconds (UTC).

total: int

Number of raw observations that contributed to this bucket.

class roboto.domain.metrics.record.AggregateMetricsRequest(/, **data)

Bases: pydantic.BaseModel

Request payload for a numeric metric aggregation.

Parameters:

data (Any)

aggregation: NumericAggregation

Aggregation function to apply to the values in each bucket.

condition: roboto.query.ConditionType | None = None

Condition, or nested group of conditions, narrowing which data points are aggregated.

Applied to individual data points rather than to bucket results, so it changes each bucket’s value and total. A period whose data points are all filtered out yields no bucket at all, so a filtered aggregation can return fewer buckets than an unfiltered one over the same window. See condition for the accepted fields and the treatment of data points published without a device.

end_time_ns: int

Exclusive end of the aggregation window, in Unix-epoch nanoseconds (UTC). Built from aggregate()’s end_time parameter the same way.

include_device_ids: list[str] | roboto.sentinels.NotSetType | None

Filter to observations from specific device IDs, None for null device_id only.

include_invocation_ids: list[str] | roboto.sentinels.NotSetType | None

Filter to observations from specific invocation IDs, None for null invocation_id only.

include_session_ids: list[str] | roboto.sentinels.NotSetType

Filter to observations for specific session IDs. None is not a valid value: metrics.session_id is non-nullable, so there is no “null session” subset to filter on. Omit (leave as NotSet) for no filter, or pass a list of IDs.

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

Name of the metric to aggregate.

period: AggregationPeriod

Calendar bucket size to group observations by.

start_time_ns: int

Inclusive start of the aggregation window, in Unix-epoch nanoseconds (UTC). Built by aggregate() from its start_time parameter via to_epoch_nanoseconds().

time_filter: MetricTimeFilter

Whether to filter by session start time or end time.

class roboto.domain.metrics.record.AggregationPeriod

Bases: roboto.compat.StrEnum

Calendar bucket size used when grouping metric observations.

All aggregation start/end times are based on UTC time.

Daily = 'daily'

One bucket per calendar day.

Monthly = 'monthly'

One bucket per calendar month.

Quarterly = 'quarterly'

One bucket per calendar quarter (three months).

Weekly = 'weekly'

One bucket per calendar week.

Yearly = 'yearly'

One bucket per calendar year.

class roboto.domain.metrics.record.CreateMetricDefinitionRequest(/, **data)

Bases: pydantic.BaseModel

Request payload to create a metric definition.

Parameters:

data (Any)

description: str | None = None

Human-readable description of what the metric measures.

name: str

Unique metric name.

unit: MetricUnit | None = None

Unit of measure for values recorded under this metric, e.g. "%", "ms". Capped at 63 characters. None means unitless.

roboto.domain.metrics.record.MAX_METRIC_LIST_RESULTS: int = 10000

Upper bound on the page size accepted by metric query and list calls.

query() auto-paginates with this value as the default page size, so total result-set size is unbounded. Callers can request smaller pages by setting max_results.

get_by_session() does not paginate and is still capped at this many rows; sessions with more data points should use the paginated query() instead.

class roboto.domain.metrics.record.MetricDefinitionRecord(/, **data)

Bases: pydantic.BaseModel

A wire-transmissible representation of a metric definition.

Parameters:

data (Any)

created: datetime.datetime

Timestamp when this metric definition was created.

created_by: str

User or service account that created this metric definition.

description: str | None = None

Human-readable description of what the metric measures.

metric_id: str

Unique identifier for this metric definition.

modified: datetime.datetime

Timestamp when this metric definition was last modified.

modified_by: str

User or service account that last modified this metric definition.

name: str

Unique name for this metric.

org_id: str

Organization that owns this metric definition.

unit: str | None = None

Unit of measure for every value recorded under this metric, e.g. "%", "ms", "m/s". Free-form and unvalidated; None means unitless.

class roboto.domain.metrics.record.MetricEntry(/, **data)

Bases: pydantic.BaseModel

A single name+value pair within a bulk metric publish.

Parameters:

data (Any)

name: str

Name of the metric definition to record a value for. If the definition does not exist, it is auto-created.

value: float

Observed numeric value.

class roboto.domain.metrics.record.MetricRecord(/, **data)

Bases: pydantic.BaseModel

A wire-transmissible representation of a metric data point.

Parameters:

data (Any)

device_id: str | None = None

Device that produced the data.

invocation_id: str | None = None

Action invocation that produced this data point, if any.

max_timestamp_ns: int | None = None

Upper bound of the source session’s aggregate timestamps, in Unix-epoch nanoseconds. None until the session has at least one file contribution. Mirrors max_timestamp_ns.

metric_id: str

Identifier of the metric definition this data point belongs to.

min_timestamp_ns: int | None = None

Lower bound of the source session’s aggregate timestamps, in Unix-epoch nanoseconds. None until the session has at least one file contribution. Mirrors min_timestamp_ns.

name: str

Human-readable name of the metric definition this data point belongs to. Resolved server-side from the parent MetricDefinitionRecord so callers do not need a second lookup to display the metric name alongside the value.

org_id: str

Organization that owns this metric data point.

published: datetime.datetime

Timestamp when this data point was published to the platform.

published_by: str

User or service account that published this data point.

session_id: str

Session this metric is associated with.

unit: str | None = None

Unit of measure for value. Resolved server-side from the parent MetricDefinitionRecord, like name, so callers can label a value without a second lookup. None means unitless.

value: float

Observed numeric value.

class roboto.domain.metrics.record.MetricTimeFilter

Bases: roboto.compat.StrEnum

Enum where members are also (and must be) strings

EndTime = 'end_time'

StartTime = 'start_time'

roboto.domain.metrics.record.MetricUnit

class roboto.domain.metrics.record.NumericAggregateMetricRecord(/, **data)

Bases: AggregateMetricRecord

A wire-transmissible representation of one period bucket in a numeric metric aggregation.

Parameters:

data (Any)

aggregation: NumericAggregation

Aggregation function that was applied to produce this record.

unit: str | None = None

Unit of measure for value, resolved from the aggregated metric’s definition alongside name. None means unitless.

value: float

Aggregated result for this bucket.

class roboto.domain.metrics.record.NumericAggregateMetricsResponse(/, **data)

Bases: pydantic.BaseModel

Response payload for a numeric metric aggregation request.

Parameters:

data (Any)

aggregation: NumericAggregation

Aggregation function that was applied.

records: list[NumericAggregateMetricRecord]

Period buckets returned by the aggregation, sorted by start_time ascending.

class roboto.domain.metrics.record.NumericAggregation

Bases: roboto.compat.StrEnum

Aggregation function applied to numeric metric values within each period bucket.

Count = 'count'

Count of observations in the bucket.

Max = 'max'

Maximum value observed in the bucket.

Mean = 'mean'

Arithmetic mean of all values in the bucket.

Min = 'min'

Minimum value observed in the bucket.

Sum = 'sum'

Sum of all values in the bucket.

class roboto.domain.metrics.record.PublishMetricsError(/, **data)

Bases: pydantic.BaseModel

One failed item from a bulk metric publish.

Parameters:

data (Any)

error: str

Human-readable description of why the insert failed.

name: str

Name of the metric that failed to insert.

class roboto.domain.metrics.record.PublishMetricsRequest(/, **data)

Bases: pydantic.BaseModel

Request payload to insert multiple metric data points in a single call.

Parameters:

data (Any)

device_id: roboto.sentinels.NotSetType | str | None

Device that produced the data. When absent (NotSet), the server infers the device from the session’s attached devices: the request succeeds if exactly one device is attached and is rejected otherwise. Pass an explicit device ID or None to skip inference.

metrics: list[MetricEntry]

Metric data points to insert.

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

session_id: str

Session all metrics in this batch will be attached to.

class roboto.domain.metrics.record.PublishMetricsResponse(/, **data)

Bases: pydantic.BaseModel

Server response from a bulk metric publish.

May contain a mix of successes and per-item failures if some metric values are invalid.

Parameters:

data (Any)

failed: list[PublishMetricsError]

succeeded: list[MetricRecord]

class roboto.domain.metrics.record.QueryMetricsRequest(/, **data)

Bases: pydantic.BaseModel

Request payload to query raw metric data points.

Parameters:

data (Any)

condition: roboto.query.ConditionType | None = None

Condition, or nested group of conditions, narrowing which data points are returned.

Every field must be prefixed with the entity it filters on, singular or plural; a bare field name such as name is rejected. The available fields are:

• session.<field>: session_id (alias id), name, min_timestamp_ns (alias start_time), max_timestamp_ns (alias end_time), duration, created, created_by, modified, modified_by, tags. The two timestamp bounds accept anything to_epoch_nanoseconds() converts; duration takes an integer count of nanoseconds.

• device.<field>: device_id (alias id), tags, created, created_by, modified, modified_by, metadata (including dotted paths beneath it). Reads the device that published the data point, not the devices attached to its session.

• session.custom.<name> / device.custom.<name> / collection.custom.<name>: a custom field in the Ready state.

• collection.collection_id (alias collection.id): the data point’s session belongs to that collection. Equals and NotEquals only.

A session belongs to any number of collections, so a collection.* condition quantifies over that set: a data point matches when its session belongs to at least one collection satisfying the condition. A negated comparator (NotEquals, NotContains, NotLike) means the session belongs to no collection satisfying the positive form, so a session in no collection at all matches every negated collection condition. IsNull and NotExists likewise mean no collection the session belongs to carries a value for the field.

A data point published without a device matches a device.* condition only under IsNull and NotExists. Every other comparator asks what the device’s field holds, NotEquals, NotContains, and NotLike included, so a data point with no device, or a device carrying no value for the field, is excluded. Write device.<field> NotEquals x OR device.<field> IsNull to match both.

Any other field, a comparator the field’s type does not accept, a value the field cannot convert, or a Not group raises RobotoIllegalArgumentException.

descending: bool = False

Return the most recent data points first, instead of the oldest first.

Ordering is by the column selected by time_filter, with session_id as a deterministic tiebreaker. A page token is bound to the direction that issued it: replaying one with a different descending value is rejected with RobotoInvalidRequestException, because the keyset cursor is only meaningful in the direction it was emitted from.

end_time_ns: int | None = None

Exclusive end of the query window, in Unix-epoch nanoseconds (UTC). Built from query()’s end_time parameter the same way. Defaults to None (now).

include_device_ids: list[str] | roboto.sentinels.NotSetType | None

Filter to observations from specific device IDs, None for null device_id only.

include_invocation_ids: list[str] | roboto.sentinels.NotSetType | None

Filter to observations from specific invocation IDs, None for null invocation_id only.

include_session_ids: list[str] | roboto.sentinels.NotSetType

Filter to observations for specific session IDs. None is not a valid value: metrics.session_id is non-nullable, so there is no “null session” subset to filter on. Omit (leave as NotSet) for no filter, or pass a list of IDs.

max_results: int = None

Maximum number of data points to return. Must be between 1 and MAX_METRIC_LIST_RESULTS (10,000).

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

Name of the metric to query.

start_time_ns: int | None = None

Inclusive start of the query window, in Unix-epoch nanoseconds (UTC). Built by query() from its start_time parameter via to_epoch_nanoseconds(). Defaults to None (the Unix epoch).

time_filter: MetricTimeFilter

Whether to filter by session start time or end time.

class roboto.domain.metrics.record.UpdateMetricDefinitionRequest(/, **data)

Bases: pydantic.BaseModel

Request payload to update a metric definition.

Parameters:

data (Any)

description: roboto.sentinels.NotSetType | str | None

New description, None to clear, or NotSet to leave unchanged.

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

unit: roboto.sentinels.NotSetType | MetricUnit | None

New unit of measure (max 63 characters), None to clear, or NotSet to leave unchanged.