AIS Intelligence Python SDK

Single-file wrapper around httpx. No build step. Drop it into your project.

Quickstart

pip install httpx
# Drop ais_intelligence.py in your project, then:

from ais_intelligence import AISClient

client = AISClient("ais_live_YOUR_KEY")

# Live vessels in SE Alaska
vessels = client.live_vessels(bbox="54,-137,60,-128")
print(f"{len(vessels['vessels'])} vessels active")

# Dark ships (gone quiet > 6 hours)
dark = client.dark_ships(silent_minutes=360)
for v in dark['vessels'][:5]:
    print(v['ship_name'], "dark for", v['silent_hours'], "hrs")

# GeoJSON for Leaflet/Mapbox - paste into geojson.io
geo = client.live_geojson()

# ETA from current position to port
eta = client.eta("338234916", "ketchikan")
print(f"ETA: {eta['eta_hours']:.1f} hours, {eta['distance_nm']:.0f} nm away")

# Port congestion score 0-100
c = client.congestion("ketchikan")
print(f"Ketchikan: {c['congestion_score']}/100 ({c['interpretation']})")

# Named fleet tracking
fleet = client.create_fleet("My Tugs", ["338234916", "367654000"])
pos = client.fleet_positions(fleet['id'])

All methods

client.health()
client.live_vessels(bbox, minutes, type_code)   # JSON
client.live_geojson(bbox, minutes)              # GeoJSON FeatureCollection
client.vessel(mmsi)
client.track(mmsi, hours)
client.voyages(mmsi)
client.search(name)
client.dark_ships(silent_minutes, active_hours, bbox)
client.anchored(port, min_minutes)
client.anomalies(hours)
client.gaps(mmsi, days, min_gap_hours)
client.congestion(port)
client.eta(mmsi, port)
client.fishing_effort(hours, lat_min, lat_max, lng_min, lng_max, grid_size)
client.proximity(mmsi1, mmsi2, alert_nm)
client.heatmap(bbox, resolution, hours)         # JSON
client.heatmap_geojson(bbox, resolution, hours) # GeoJSON
client.area_traffic(bbox, hours)
client.port_report(port, days)
client.fleets()
client.create_fleet(name, mmsis)
client.fleet_positions(fleet_id)
client.add_fleet_mmsis(fleet_id, mmsis)
client.rotate_key()
client.usage_breakdown(days)

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