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Snapshots all four versioned Docusaurus sections at v6.1.0. Built on top of the version-cutting tooling work in chore/docs-cut-6.1.0-versions so the snapshot benefits from: - Auto-gen refresh before snapshotting (database pages from engine spec metadata, API reference from openapi.json, component pages from Storybook stories) — captured at the SHA we cut from rather than whatever happened to be on disk. - Data-import freeze: country list, feature flag table, database diagnostics, and component metadata are copied into snapshot-local `_versioned_data/` dirs so the historical version doesn't silently mutate when the source files change. - Depth-aware import-path rewriter that handles deeply-nested component MDX files referencing `../../../src/` from the snapshot. Versioning behavior: `lastVersion` stays at `current` for every section, so the canonical URLs (`/docs/...`, `/admin-docs/...`, `/developer-docs/...`, `/components/...`) continue to render content from master. The `current` version is consistently labeled "Next" with an `unreleased` banner, and `6.1.0` is a historical pin accessible only via its explicit version segment. Component playground: previously `disabled: true` in versions-config.json, now enabled and versioned. The plugin block in docusaurus.config.ts was already gated only by the `disabled` flag, so no other code changes were needed to bring it back online. The frozen `databases.json` in the snapshot is the canonical 80-database artifact from the latest committed state in master (preserved by the generator's input-hash cache), not a fallback regenerated from a local Flask environment.
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1.7 KiB
JSON
2 lines
1.7 KiB
JSON
{"schema":{"properties":{"aggregate":{"description":"Aggregation operator.Only required for simple expression types.","enum":["AVG","COUNT","COUNT_DISTINCT","MAX","MIN","SUM"],"type":"string"},"column":{"properties":{"column_name":{"description":"The name of the target column","example":"mycol","type":"string"},"type":{"description":"Type of target column","example":"BIGINT","type":"string"}},"type":"object","title":"ChartDataColumn"},"expressionType":{"description":"Simple or SQL metric","enum":["SIMPLE","SQL"],"example":"SQL","type":"string"},"hasCustomLabel":{"description":"When false, the label will be automatically generated based on the aggregate expression. When true, a custom label has to be specified.","example":true,"type":"boolean"},"isExtra":{"description":"Indicates if the filter has been added by a filter component as opposed to being a part of the original query.","type":"boolean"},"label":{"description":"Label for the metric. Is automatically generated unlesshasCustomLabel is true, in which case label must be defined.","example":"Weighted observations","type":"string"},"optionName":{"description":"Unique identifier. Can be any string value, as long as all metrics have a unique identifier. If undefined, a random namewill be generated.","example":"metric_aec60732-fac0-4b17-b736-93f1a5c93e30","type":"string"},"sqlExpression":{"description":"The metric as defined by a SQL aggregate expression. Only required for SQL expression type.","example":"SUM(weight * observations) / SUM(weight)","type":"string"},"timeGrain":{"description":"Optional time grain for temporal filters","example":"PT1M","type":"string"}},"required":["expressionType"],"type":"object","title":"ChartDataAdhocMetricSchema"},"schemaType":"response"}
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