## Get Evaluation Dashboard `evaluation_dashboards.retrieve(strdashboard_id, EvaluationDashboardRetrieveParams**kwargs) -> EvaluationDashboard` **get** `/v5/evaluation-dashboards/{dashboard_id}` Fetch a single dashboard by ID within the caller's account. By default only the dashboard's own fields are returned. Pass `views=widgets` and/or `views=widget_results` to eagerly load the dashboard's widgets and their last-computed results as nested relationships; without those views the `widgets` and `widget_results` fields are omitted from the response entirely. Set `include_archived=true` to retrieve a soft-deleted dashboard. Returns a not-found error if no matching dashboard exists in the account. ### Parameters - `dashboard_id: str` - `include_archived: Optional[bool]` - `views: Optional[List[Literal["widgets", "widget_results"]]]` Optional relationships to include: 'widgets', 'widget_results' - `"widgets"` - `"widget_results"` ### Returns - `class EvaluationDashboard: …` - `id: str` Unique identifier of the dashboard - `account_id: str` Account that owns this dashboard - `created_at: datetime` When the dashboard was created - `created_by: Identity` The identity that created the entity. - `id: str` - `type: Literal["user", "service_account"]` - `"user"` - `"service_account"` - `object: Optional[Literal["identity"]]` - `"identity"` - `name: str` Dashboard name - `tags: Optional[List[str]]` The tags associated with the entity - `updated_at: datetime` When the dashboard was last updated - `archived_at: Optional[datetime]` When the dashboard was archived (soft-deleted) - `description: Optional[str]` Dashboard description - `error_message: Optional[str]` Error message if computation failed - `evaluation_group_id: Optional[str]` Evaluation group ID - `evaluation_id: Optional[str]` Evaluation ID - `object: Optional[Literal["evaluation_dashboard"]]` - `"evaluation_dashboard"` - `widget_order: Optional[List[str]]` Ordered array of widget IDs - `widget_results: Optional[List[EvaluationDashboardWidgetResult]]` Widget results for this dashboard. Populated with 'widget_results' view. - `id: str` Unique identifier of the widget result - `account_id: str` Account that owns this widget result - `computation_status: Literal["pending", "completed", "failed"]` Status of the computation - `"pending"` - `"completed"` - `"failed"` - `created_at: datetime` When the widget result was created - `widget_id: str` Unique identifier of the widget - `computation_job_id: Optional[str]` Temporal workflow ID or job ID for async computation tracking - `computed_at: Optional[datetime]` Timestamp when computation completed successfully - `computed_result: Optional[Dict[str, object]]` Cached computation results - `error_message: Optional[str]` Error message if computation failed - `evaluation_group_id: Optional[str]` FK to evaluation_groups. Null if result is for a single evaluation. - `evaluation_id: Optional[str]` FK to evaluations. Null if result is for an evaluation group. - `object: Optional[Literal["evaluation_dashboard_widget_result"]]` - `"evaluation_dashboard_widget_result"` - `widget: Optional[EvaluationDashboardWidget]` Widget that this result is for - `id: str` Unique identifier of the widget - `account_id: str` Account that owns this widget - `created_at: datetime` When the widget was created - `title: str` Widget title - `type: EvaluationWidgetTypeEnum` Widget type - `"bar"` - `"histogram"` - `"donut"` - `"scatter"` - `"metric"` - `"table"` - `"markdown"` - `"heading"` - `"timeseries"` - `archived_at: Optional[datetime]` When the widget was archived (soft-deleted) - `config: Optional[Dict[str, object]]` Chart-specific display configuration - `object: Optional[Literal["evaluation_dashboard_widget"]]` - `"evaluation_dashboard_widget"` - `query: Optional[Query]` Structured query AST for metric computation (SeriesQuery or MetricQuery) - `class SeriesQuery: …` Query that returns a series of records (used for table/bar/histogram/donut/scatter widgets). Used for widget types: table, bar, histogram, donut, scatter. Returns: {"type": "series", "data": [...]} Example SQL equivalent: SELECT category, AVG(score) as avg_score, COUNT(*) as count FROM evaluation_items WHERE score > 0.5 AND category = 'test' GROUP BY category ORDER BY avg_score DESC LIMIT 100 - `select: List[SelectItem]` - `expression: Expression` Reference to a column from evaluation_items.data Example: {"type": "COLUMN", "column": "category"} - `class ExpressionColumn: …` Reference to a column from evaluation_items.data Example: {"type": "COLUMN", "column": "category"} - `column: str` Column name from evaluation_items.data - `source: Optional[str]` Column source: 'data' or 'task_result_cache' - `type: Optional[Literal["COLUMN"]]` - `"COLUMN"` - `class ExpressionAggregation: …` Aggregation function to apply Examples: {"type": "AGGREGATION", "function": "AVG", "column": "score"} {"type": "AGGREGATION", "function": "COUNT", "column": "*"} {"type": "AGGREGATION", "function": "PERCENTILE", "column": "score", "params": {"percentile": 95}} - `column: str` Column to aggregate, or '*' for COUNT(*) - `function: Literal["COUNT", "SUM", "AVG", 7 more]` Supported aggregation functions - `"COUNT"` - `"SUM"` - `"AVG"` - `"MIN"` - `"MAX"` - `"STDDEV"` - `"VARIANCE"` - `"PERCENTILE"` - `"COUNT_DISTINCT"` - `"PERCENTAGE"` - `evaluation_ids: Optional[List[str]]` Optional subset of evaluation IDs for per-aggregation filtering in evaluation group dashboards. - `params: Optional[Dict[str, object]]` Function parameters (e.g., {'percentile': 95} for PERCENTILE, {'percentage_filters': Filter} for PERCENTAGE) - `source: Optional[str]` Column source: 'data' or 'task_result_cache' - `type: Optional[Literal["AGGREGATION"]]` - `"AGGREGATION"` - `alias: Optional[str]` Optional alias for the selected item - `evaluation_ids: Optional[List[str]]` Optional subset of evaluation IDs to compute on. Only applicable for evaluation group dashboards. If omitted, computes on all evaluations in the group. - `filter: Optional[Filter]` Filter conditions (WHERE clause) - `conditions: List[Condition]` - `column: str` Column name to filter on - `operator: Literal["=", "!=", ">", 9 more]` Comparison operator - `"="` - `"!="` - `">"` - `"<"` - `">="` - `"<="` - `"IN"` - `"NOT IN"` - `"LIKE"` - `"NOT LIKE"` - `"IS NULL"` - `"IS NOT NULL"` - `source: Optional[str]` Column source: 'data' or 'task_result_cache' - `value: Optional[Union[str, float, bool, 2 more]]` Value to compare against. Not required for IS NULL / IS NOT NULL operators. - `str` - `float` - `bool` - `List[object]` - `logical_operators: Optional[List[Literal["AND", "OR"]]]` Logical operators connecting conditions. Length must be len(conditions) - 1 - `"AND"` - `"OR"` - `group_by: Optional[List[str]]` Columns to group by - `latest_only: Optional[bool]` When True, the widget computes against rows from only the most recent active evaluation in the group (by EvaluationORM.created_at). Only applicable for evaluation group dashboards. Composes with evaluation_ids (latest within the subset). Cannot be combined with per-aggregation evaluation_ids; the use case enforces these rules. - `limit: Optional[int]` Max rows to return - `order_by: Optional[List[OrderBy]]` Sort order - `column: str` Column name to sort by - `direction: Optional[Literal["ASC", "DESC"]]` Sort direction - `"ASC"` - `"DESC"` - `source: Optional[str]` Column source: 'data' or 'task_result_cache' - `class MetricQuery: …` Query that returns a single metric value (used for metric widgets). Used for widget type: metric. Enforces exactly 1 aggregation in select. Returns: {"type": "metric", "data": ...} Example SQL equivalent: SELECT AVG(score) as average_score FROM evaluation_items - `select: List[SelectItem]` - `expression: Expression` Reference to a column from evaluation_items.data Example: {"type": "COLUMN", "column": "category"} - `alias: Optional[str]` Optional alias for the selected item - `evaluation_ids: Optional[List[str]]` Optional subset of evaluation IDs to compute on. Only applicable for evaluation group dashboards. If omitted, computes on all evaluations in the group. - `filter: Optional[Filter]` Filter conditions (WHERE clause) - `latest_only: Optional[bool]` When True, the widget computes against rows from only the most recent active evaluation in the group (by EvaluationORM.created_at). Only applicable for evaluation group dashboards. Composes with evaluation_ids (latest within the subset). Cannot be combined with per-aggregation evaluation_ids; the use case enforces these rules. - `widgets: Optional[List[EvaluationDashboardWidget]]` Widgets associated with this dashboard. Populated with 'widgets' view. - `id: str` Unique identifier of the widget - `account_id: str` Account that owns this widget - `created_at: datetime` When the widget was created - `title: str` Widget title - `type: EvaluationWidgetTypeEnum` Widget type - `archived_at: Optional[datetime]` When the widget was archived (soft-deleted) - `config: Optional[Dict[str, object]]` Chart-specific display configuration - `object: Optional[Literal["evaluation_dashboard_widget"]]` - `query: Optional[Query]` Structured query AST for metric computation (SeriesQuery or MetricQuery) ### Example ```python import os from scale_gp_beta import SGPClient client = SGPClient( api_key=os.environ.get("SGP_API_KEY"), # This is the default and can be omitted ) evaluation_dashboard = client.evaluation_dashboards.retrieve( dashboard_id="dashboard_id", ) print(evaluation_dashboard.id) ``` #### Response ```json { "id": "id", "account_id": "account_id", "created_at": "2019-12-27T18:11:19.117Z", "created_by": { "id": "id", "type": "user", "object": "identity" }, "name": "name", "tags": [ "string" ], "updated_at": "2019-12-27T18:11:19.117Z", "archived_at": "2019-12-27T18:11:19.117Z", "description": "description", "error_message": "error_message", "evaluation_group_id": "evaluation_group_id", "evaluation_id": "evaluation_id", "object": "evaluation_dashboard", "widget_order": [ "string" ], "widget_results": [ { "id": "id", "account_id": "account_id", "computation_status": "pending", "created_at": "2019-12-27T18:11:19.117Z", "widget_id": "widget_id", "computation_job_id": "computation_job_id", "computed_at": "2019-12-27T18:11:19.117Z", "computed_result": { "foo": "bar" }, "error_message": "error_message", "evaluation_group_id": "evaluation_group_id", "evaluation_id": "evaluation_id", "object": "evaluation_dashboard_widget_result", "widget": { "id": "id", "account_id": "account_id", "created_at": "2019-12-27T18:11:19.117Z", "title": "title", "type": "bar", "archived_at": "2019-12-27T18:11:19.117Z", "config": { "foo": "bar" }, "object": "evaluation_dashboard_widget", "query": { "select": [ { "expression": { "column": "column", "source": "source", "type": "COLUMN" }, "alias": "alias" } ], "evaluation_ids": [ "string" ], "filter": { "conditions": [ { "column": "column", "operator": "=", "source": "source", "value": "string" } ], "logicalOperators": [ "AND" ] }, "groupBy": [ "string" ], "latest_only": true, "limit": 1, "orderBy": [ { "column": "column", "direction": "ASC", "source": "source" } ] } } } ], "widgets": [ { "id": "id", "account_id": "account_id", "created_at": "2019-12-27T18:11:19.117Z", "title": "title", "type": "bar", "archived_at": "2019-12-27T18:11:19.117Z", "config": { "foo": "bar" }, "object": "evaluation_dashboard_widget", "query": { "select": [ { "expression": { "column": "column", "source": "source", "type": "COLUMN" }, "alias": "alias" } ], "evaluation_ids": [ "string" ], "filter": { "conditions": [ { "column": "column", "operator": "=", "source": "source", "value": "string" } ], "logicalOperators": [ "AND" ] }, "groupBy": [ "string" ], "latest_only": true, "limit": 1, "orderBy": [ { "column": "column", "direction": "ASC", "source": "source" } ] } } ] } ```