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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
295959111 MDU6SXNzdWUyOTU5NTkxMTE= 1900 Representing & checking Dataset schemas max-sixty 5635139 open 0     15 2018-02-09T18:06:08Z 2022-07-14T11:28:37Z   MEMBER      

What would be the best way to canonically describe a dataset, which could be read by both humans and machines?

For example, frequently in our code we have docstrings which look something like:

``` def get_returns(security_ids): """ Retuns mega-dimensional dataset which gives recent returns for a set of securities by: - Date - Return (raw / economic / smoothed / etc) - Scaling (constant / risk_scaled) - Span - Hedged vs Unhedged

Dataset keys are security ids. All dimensions have coords.
"""

```

This helps when attempting to understand what code is doing while only reading it. But this isn't consistent between docstrings and can't be read or checked by a machine. Has anyone solved this problem / have any suggestions for resources out there?

Tangentially related to https://github.com/python/typing/issues/513 (but our issues are less about the type, dimension sizes, and more about the arrays within a dataset, their dimensions, and their names)

 
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     xarray 13221727 issue

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