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cbcfd9599f
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.
2 lines
1.5 KiB
JSON
2 lines
1.5 KiB
JSON
{"schema":{"properties":{"center":{"description":"Should the label be at the center of the window.Default: `false`","example":false,"type":"boolean"},"min_periods":{"description":"The minimum amount of periods required for a row to be included in the result set.","example":7,"type":"integer"},"rolling_type":{"description":"Type of rolling window. Any numpy function will work.","enum":["average","argmin","argmax","cumsum","cumprod","max","mean","median","nansum","nanmin","nanmax","nanmean","nanmedian","nanpercentile","min","percentile","prod","product","std","sum","var"],"example":"percentile","type":"string"},"rolling_type_options":{"description":"Optional options to pass to rolling method. Needed for e.g. quantile operation.","example":{},"type":"object"},"win_type":{"description":"Type of window function. See [SciPy window functions](https://docs.scipy.org/doc/scipy/reference /signal.windows.html#module-scipy.signal.windows) for more details. Some window functions require passing additional parameters to `rolling_type_options`. For instance, to use `gaussian`, the parameter `std` needs to be provided.","enum":["boxcar","triang","blackman","hamming","bartlett","parzen","bohman","blackmanharris","nuttall","barthann","kaiser","gaussian","general_gaussian","slepian","exponential"],"type":"string"},"window":{"description":"Size of the rolling window in days.","example":7,"type":"integer"}},"required":["rolling_type","window"],"type":"object","title":"ChartDataRollingOptionsSchema"},"schemaType":"response"}
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