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from typing import Literal
CODE_SERVICES = Literal[
"characteristicgroup",
"characteristics",
"counties",
"countries",
"observedproperty",
"samplemedia",
"sitetype",
"states",
]
METADATA_COLLECTIONS = Literal[
"agency-codes",
"altitude-datums",
"aquifer-codes",
"aquifer-types",
"coordinate-accuracy-codes",
"coordinate-datum-codes",
"coordinate-method-codes",
"counties",
"hydrologic-unit-codes",
"medium-codes",
"national-aquifer-codes",
"parameter-codes",
"reliability-codes",
"site-types",
"states",
"statistic-codes",
"topographic-codes",
"time-zone-codes",
]
SERVICES = Literal[
"activities",
"locations",
"organizations",
"projects",
"results",
]
# OGC API time-series/monitoring collections queryable via ``get_cql``.
# Keep in sync with ``utils._OUTPUT_ID_BY_SERVICE`` (same keys): that dict maps
# each service to its user-facing ``id`` column and is the runtime source of
# truth ``get_cql`` validates against.
WATERDATA_SERVICES = Literal[
"channel-measurements",
"combined-metadata",
"continuous",
"daily",
"field-measurements",
"field-measurements-metadata",
"latest-continuous",
"latest-daily",
"monitoring-locations",
"peaks",
"time-series-metadata",
]
PROFILES = Literal[
"actgroup",
"actmetric",
"basicbio",
"basicphyschem",
"count",
"fullbio",
"fullphyschem",
"labsampleprep",
"narrow",
"organization",
"project",
"projectmonitoringlocationweight",
"resultdetectionquantitationlimit",
"sampact",
"site",
]
PROFILE_LOOKUP = {
"activities": ["sampact", "actmetric", "actgroup", "count"],
"locations": ["site", "count"],
"organizations": ["organization", "count"],
"projects": ["project", "projectmonitoringlocationweight"],
"results": [
"fullphyschem",
"basicphyschem",
"fullbio",
"basicbio",
"narrow",
"resultdetectionquantitationlimit",
"labsampleprep",
"count",
],
}