Representing & checking Dataset schemas

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)

Start by reviewing the proposed dataset docstring example and the related Python typing issue linked in the discussion. Determine whether the desired outcome is a schema representation, machine-checking support, or both; done would require an agreed canonical format and an implementation plan, neither of which this issue currently specifies.