kelp.models.metric_view¶

Reference for the metric_view configuration model.

kelp.models.metric_view.MetricView `pydantic-model` ¶

Bases: BaseModel

Metric View definition for Databricks.

The dimensions key (the spec synonym for fields) is canonicalized to fields on construction, so local YAML and remote-fetched state always compare and render consistently — Unity Catalog currently returns stored definitions with dimensions even when created with fields.

Attributes:

Name	Type	Description
`name`	`str`	The name of the metric view.
`catalog`	`str \| None`	The catalog where the metric view will be created.
`schema_`	`str \| None`	The schema where the metric view will be created.
`definition`	`dict[str, Any]`	The metric view specification as a dictionary, following the Databricks metric view YAML reference (`version`, `source`, `comment`, `filter`, `joins`, `fields`, `measures`, …).
`tags`	`dict[str, str]`	Optional tags for the metric view.
`origin_file_path`	`SkipJsonSchema[str] \| None`	Path to the source YAML file (internal use).
`raw_config`	`SkipJsonSchema[dict]`	Preserve original, unparsed config (including placeholder vars).

Show JSON schema:

{
  "description": "Metric View definition for Databricks.\n\nThe ``dimensions`` key (the spec synonym for ``fields``) is canonicalized\nto ``fields`` on construction, so local YAML and remote-fetched state\nalways compare and render consistently \u2014 Unity Catalog currently returns\nstored definitions with ``dimensions`` even when created with ``fields``.\n\nAttributes:\n    name: The name of the metric view.\n    catalog: The catalog where the metric view will be created.\n    schema_: The schema where the metric view will be created.\n    definition: The metric view specification as a dictionary, following\n                the Databricks metric view YAML reference (``version``,\n                ``source``, ``comment``, ``filter``, ``joins``,\n                ``fields``, ``measures``, \u2026).\n    tags: Optional tags for the metric view.\n    origin_file_path: Path to the source YAML file (internal use).\n    raw_config: Preserve original, unparsed config (including placeholder vars).",
  "properties": {
    "name": {
      "title": "Name",
      "type": "string"
    },
    "catalog": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Catalog"
    },
    "schema": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Schema"
    },
    "definition": {
      "additionalProperties": true,
      "description": "The metric view specification following the Databricks metric view YAML reference, passed through to DDL verbatim (plus optional Kelp-managed 'tags' on field/measure entries)",
      "title": "Definition",
      "type": "object"
    },
    "tags": {
      "additionalProperties": {
        "type": "string"
      },
      "title": "Tags",
      "type": "object"
    },
    "meta": {
      "additionalProperties": true,
      "description": "Generic user-defined metadata for filtering and grouping",
      "title": "Meta",
      "type": "object"
    }
  },
  "required": [
    "name"
  ],
  "title": "MetricView",
  "type": "object"
}

Config:

validate_by_name: True
validate_by_alias: True
serialize_by_alias: True

Fields:

origin_file_path (SkipJsonSchema[str] | None)
name (str)
catalog (str | None)
schema_ (str | None)
definition (dict[str, Any])
tags (dict[str, str])
meta (dict[str, Any])
raw_config (SkipJsonSchema[dict])

Validators:

_canonicalize_fields_key → definition

origin_file_path `pydantic-field` ¶

origin_file_path = None

name `pydantic-field` ¶

name

catalog `pydantic-field` ¶

catalog = None

schema_ `pydantic-field` ¶

schema_ = None

definition `pydantic-field` ¶

definition

The metric view specification following the Databricks metric view YAML reference, passed through to DDL verbatim (plus optional Kelp-managed 'tags' on field/measure entries)

tags `pydantic-field` ¶

tags

meta `pydantic-field` ¶

meta

Generic user-defined metadata for filtering and grouping

raw_config `pydantic-field` ¶

raw_config

model_config `class-attribute` `instance-attribute` ¶

model_config = ConfigDict(
    validate_by_name=True,
    validate_by_alias=True,
    serialize_by_alias=True,
)

get_qualified_name ¶

get_qualified_name()

Get the fully qualified metric view name including catalog/schema if applicable.

Source code in src/kelp/models/metric_view.py

def get_qualified_name(self) -> str:
    """Get the fully qualified metric view name including catalog/schema if applicable."""
    parts = []
    if self.catalog:
        parts.append(self.catalog)
    if self.schema_:
        parts.append(self.schema_)
    parts.append(self.name)
    return ".".join(parts)

kelp.models.metric_view¶