Reject missing nearest-observation targets - #431
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Follow-up review changes on top of the missing-target fix (DOI-USGS#430): - targets: report how many entries are missing and where the first is, listing every missing form (NaT, None, NaN, ''); ask for a timestamp rather than suggesting removal when nothing valid remains; reject numbers (read by pandas as epoch nanoseconds) with TypeError naming the units to convert from; rewrap pandas parse errors to name targets instead of suggesting a format= the getter does not accept. - window: reject missing, negative, and unparseable windows with ValueError, and bare numbers with TypeError. A negative window used to invert every bound and return an empty frame; a missing one crashed with AttributeError. Zero remains an exact-match query. - Messages follow the repo convention: parameter names bare, caller values as (got ...), and a remedy that works when pasted back. - Docstring: describe window as how far either side of each target to search; document every raise. - Tests grouped into targets and window validation sections; each suggested remedy is applied literally and must succeed. - NEWS entry.
thodson-usgs
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Reviewed and extended with input validation for targets and window; CI green.
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Missing target timestamps passed to
get_nearest_continuousbecome invalidtime >= 'nan'/time <= 'nan'CQL bounds, including when only one entry in a list is missing. Reject these targets with an actionableValueErrorbefore callingget_continuous.The change adds a missing-value check after timestamp normalization and documents the input requirement. Seven regression cases exercise scalar and supported container inputs and verify that the underlying getter is never called for missing targets.
Validation on Windows with Python 3.12.14 and pandas 3.0.1:
nearest.py. Per the contributor guide, the Windows result is recorded with--fail-under=0; the Linux CI job still evaluates its 98.90% ratchet.These API-boundary tests make no live USGS request.
Closes #430.