Air Monitors — client.monitors

Air quality monitors and their sensor readings.

from sjvair import SJVAirClient

with SJVAirClient() as client:
    monitor = client.monitors.get('utYTsexeRT-08jcNDLeM3w')
    print(monitor)

{
    "id": "utYTsexeRT-08jcNDLeM3w",
    "name": "AQ-101 Downtown Fresno",
    "type": "PurpleAir",
    "device": "PA-II",
    "grade": "lcs",
    "is_active": True,
    "is_sjvair": True,
    "position": {"type": "Point", "coordinates": [-119.7726, 36.7468]},
    "last_active_limit": "2026-07-08T12:00:00Z",
    "location": "outside",
    "county": "Fresno",
    "data_source": "purpleair",
    "data_providers": ["SJVAir"],
}

Methods

Method	Description
list(**params)	Iterate all monitors. Filter by region_id, is_sjvair, etc.
get(monitor_id)	Get a single monitor by ID.
meta()	Field metadata: entry types, units, level thresholds, default_pollutant.
entries(monitor_id, entry_type, **params)	Paginated entry records for one monitor.
export(monitor_id, start_date, end_date, scope)	Bulk export up to 180 days at once.
summaries(monitor_id, entry_type, resolution, start_date, end_date)	Aggregated summaries at hourly / daily / monthly / quarterly / seasonal / yearly resolution. Rows are tagged with monitor_id.
closest(entry_type, lat, lon, **params)	Up to 3 nearest active monitors with distance and latest entry. Pass device to filter by device type.
current(entry_type, **params)	All active monitors with their most recent entry. Pass device to filter by device type.
current_at(entry_type, timestamp, region=None, bbox=None, **params)	Like current(), but as of a historical timestamp. Optionally scope to one or more region IDs, a (west, south, east, north) bbox, or device.

Entries and summaries

entries() returns paginated raw readings for one pollutant:

for entry in client.monitors.entries('utYTsexeRT-08jcNDLeM3w', 'pm25'):
    print(entry)

{
    "timestamp": "2026-07-08T11:55:00Z",
    "value": 12.4,
    "monitor_id": "utYTsexeRT-08jcNDLeM3w",
}

summaries() aggregates readings over a resolution — each row is tagged with the monitor_id it belongs to, so results from multiple monitors can be flattened into one table:

rows = list(client.monitors.summaries(
    monitor_id='utYTsexeRT-08jcNDLeM3w',
    entry_type='pm25',
    resolution='daily',
    start_date='2026-07-01',
    end_date='2026-07-07',
))

{
    "date": "2026-07-01",
    "monitor_id": "utYTsexeRT-08jcNDLeM3w",
    "mean": 10.8,
    "min": 4.2,
    "max": 22.1,
    "count": 288,
}

Filtering by device

list(), closest(), current(), and current_at() all accept a device filter, matching one of the platform’s monitor types:

cimis_stations = list(client.monitors.current('temperature', device='CIMIS'))

Confirmed device values: PurpleAir, AirNow, AQview, BAM1022, AQLite, AirGradient, CIMIS, VOZBox. This list grows as new integrations land on the platform.

Meteorological entry types

CIMIS weather stations report several meteorological entry types beyond the usual pollutant fields, usable with entries(), current(), and summaries() like any other entry_type: temperature, humidity, pressure, dewpoint, soiltemperature, windspeed, winddirection, precipitation, solarradiation, netradiation, vaporpressure, eto, etr.