SL: Roslagsbanan

Use it from code

Every day is a Parquet file at a fixed address. Read it straight from DuckDB, Polars or anything that reads Parquet over HTTP: only the columns and rows your query needs are downloaded. You need a free API token from an account.

Try it in your browser Developer guide

Source id

se-sl

Services

TripUpdate live delays: daily files from 28 Sep 2026 to 3 Nov 2026 (32 days)

VehiclePosition train positions: daily files from 5 Oct 2026 to 3 Nov 2026 (30 days)

Daily file

https://data.train-archive.eu/daily/provider=se-sl/service=TripUpdate/date=YYYY-MM-DD.parquet final delays per train and stop

Every update

https://data.train-archive.eu/provider=se-sl/service=SERVICE/date=YYYY-MM-DD/day.parquet

Today

Still being collected in 15-minute files. The day’s file is built after 02:15 UTC. The developer guide shows how to read the 15-minute files.

Timetables

Service static: 7 versions, listed in se-sl/static/latest.json

INSTALL httpfs; LOAD httpfs;

-- The most recent positions of the day
SELECT trip_tripId, vehicle_label, position_latitude, position_longitude, lastSeen
FROM read_parquet('https://data.train-archive.eu/provider=se-sl/service=VehiclePosition/date=2026-11-03/day.parquet?token=YOUR_TOKEN')
WHERE position_latitude IS NOT NULL
ORDER BY lastSeen DESC
LIMIT 20;

import polars as pl

token = "YOUR_TOKEN"
df = pl.read_parquet(f"https://data.train-archive.eu/provider=se-sl/service=VehiclePosition/date=2026-11-03/day.parquet?token={token}")

# The most recent positions of the day
print(
    df.filter(pl.col("position_latitude").is_not_null())
    .select("trip_tripId", "vehicle_label", "position_latitude", "position_longitude", "lastSeen")
    .sort("lastSeen", descending=True)
    .head(20)
)

curl -L -o se-sl-VehiclePosition-2026-11-03.parquet \
  'https://data.train-archive.eu/provider=se-sl/service=VehiclePosition/date=2026-11-03/day.parquet?token=YOUR_TOKEN'

Replace YOUR_TOKEN with one of your API tokens. Times are in UTC.

import json, urllib.request
import polars as pl

base, token = "https://data.train-archive.eu", "YOUR_TOKEN"
latest = json.load(urllib.request.urlopen(f"{base}/se-sl/static/latest.json?token={token}"))
stops = pl.read_parquet(f"{base}/{latest['tables']['stops']}?token={token}")
print(stops.select("stop_id", "stop_name"))

Also: every file of this source, listed, and asking an AI assistant to query it for you.