Korean Air (London Heathrow Airport, LHR) Airports API

You need to surface reliable Korean Air (KE) schedules at London Heathrow (LHR), keep your app in sync as flights move from scheduled to en-route to arrived, and handle edge cases without guesswork. By the end of this guide, you’ll be able to query FlightLabs for KE schedules at LHR, consume the JSON, and build features like live status pages, delay monitors, and route summaries—using endpoints that return exactly the fields you need.

Korean Air at LHR: context for developers

Korean Air (IATA: KE) is the flag carrier of South Korea. It operates international services including long-haul flights that serve London Heathrow Airport (IATA: LHR). This article focuses on extracting Korean Air schedules and related operational data around LHR and turning that into practical features for your application.

Choosing your query strategy: airline vs airport

There are two common ways to anchor your queries for Korean Air at LHR:

• Query by airline to get all KE schedules, then filter in your app to LHR.
• Query by airport to get all LHR schedules, then filter to KE.

FlightLabs provides a schedules endpoint that supports both patterns via a single parameter switch. Use the same base path and swap the type parameter between airline and airport.

All endpoints are available from the FlightLabs API platform; explore them in the Documentation and test calls from the MCP.

Schedules for Korean Air and LHR: end-to-end example

Below are two complementary queries against the FlightLabs schedules endpoint. Use whichever aligns best with your internal filtering and caching strategy.

Option A: Query schedules by airline (KE)

This returns Korean Air schedules across its network. Filter for LHR in your application logic.

curl -G "https://api.goflightlabs.com/flights-schedules" \
--data-urlencode "iataCode=KE" \
--data-urlencode "type=airline" \
--data-urlencode "api_key=YOUR_API_KEY"

Illustrative JSON (fields shown follow the schedules example in the docs; values are for demonstration only):

{
"success": true,
"data": {
"schedules": [
{
"departure": {
"airport": "ICN",
"scheduled": "2024-11-10T12:30:00Z",
"terminal": "2"
},
"arrival": {
"airport": "LHR",
"scheduled": "2024-11-10T16:20:00Z",
"terminal": "4"
},
"aircraft": {
"type": "Boeing 777-300ER",
"registration": "HLXXXX"
},
"airline": {
"name": "Korean Air",
"iata": "KE"
}
},
{
"departure": {
"airport": "LHR",
"scheduled": "2024-11-12T18:40:00Z",
"terminal": "4"
},
"arrival": {
"airport": "ICN",
"scheduled": "2024-11-13T12:10:00Z",
"terminal": "2"
},
"aircraft": {
"type": "Boeing 787-9",
"registration": "HLYYYY"
},
"airline": {
"name": "Korean Air",
"iata": "KE"
}
}
]
}
}

What matters for a KE-at-LHR integration:

• Filter schedules where either arrival.airport or departure.airport equals "LHR".
• Use departure.scheduled and arrival.scheduled for time grids and to seed real-time polling windows.
• Surface terminal when provided (e.g., "4") in your UI; gate may appear on real-time endpoints closer to departure.
• Store airline.iata to ensure you’re consistently presenting KE flights only.

Option B: Query schedules by airport (LHR)

This returns Heathrow schedules across all airlines. Filter for KE in your logic.

curl -G "https://api.goflightlabs.com/flights-schedules" \
--data-urlencode "iataCode=LHR" \
--data-urlencode "type=airport" \
--data-urlencode "api_key=YOUR_API_KEY"

Then filter in code where schedule.airline.iata === "KE". This approach is useful if your product already centers on LHR operations and you want to carve out the Korean Air slice.

Code: fetch KE schedules and pick out LHR legs

The following Python example calls the airline-based schedules query, filters LHR, and extracts the times and terminals you’ll typically present. It uses only documented fields from the schedules example.

import os
import requests
from datetime import datetime, timezone

API_KEY = os.getenv("FLIGHTLABS_API_KEY", "YOUR_API_KEY")
BASE_URL = "https://api.goflightlabs.com/flights-schedules"

def iso_to_local(iso_str, tzinfo=timezone.utc):
if not iso_str:
return None
# API times are ISO 8601; this returns UTC for consistency.
dt = datetime.fromisoformat(iso_str.replace("Z", "+00:00"))
return dt.astimezone(tzinfo)

def get_ke_lhr_schedules():
params = {
"iataCode": "KE",
"type": "airline",
"api_key": API_KEY
}
r = requests.get(BASE_URL, params=params, timeout=30)
r.raise_for_status()
payload = r.json()

out = []
for item in payload.get("data", {}).get("schedules", []):
dep = item.get("departure", {})
arr = item.get("arrival", {})
airline = item.get("airline", {})

# Keep only legs that touch LHR
if dep.get("airport") == "LHR" or arr.get("airport") == "LHR":
out.append({
"airline_iata": airline.get("iata"),
"dep_airport": dep.get("airport"),
"dep_scheduled_utc": dep.get("scheduled"),
"dep_terminal": dep.get("terminal"),
"arr_airport": arr.get("airport"),
"arr_scheduled_utc": arr.get("scheduled"),
"arr_terminal": arr.get("terminal")
})
return out

if __name__ == "__main__":
schedules = get_ke_lhr_schedules()
for s in schedules:
print(
f"KE at LHR: {s['dep_airport']} -> {s['arr_airport']} | "
f"DEP {s['dep_scheduled_utc']} (T{s.get('dep_terminal')}) | "
f"ARR {s['arr_scheduled_utc']} (T{s.get('arr_terminal')})"
)

Notes:

• Times from the schedules endpoint are provided as ISO 8601 strings (e.g., 2024-11-10T12:30:00Z). Treat them as UTC for sorting and comparisons, then convert to local time zones for display.
• Terminal fields are present in the example schedules response; gates are typically available on real-time endpoints closer to departure/arrival.
• If you prefer to center the workflow on LHR, switch the query to iataCode=LHR&type=airport and filter airline.iata == "KE".

From schedules to live status: how to layer in day-of-flight updates

Schedules give you the backbone; live status provides truth-on-the-day. FlightLabs offers a real-time tracking category you can query around departure windows you discover via schedules. The real-time example response includes:

• flight.status (e.g., en-route)
• departure.scheduled and departure.actual
• arrival.scheduled and arrival.estimated
• terminal and gate
• position fields for maps (latitude, longitude, altitude, speed, heading)

Polling guidelines:

• Start polling real-time data about 2–3 hours before scheduled departure and continue until arrival. Use a backoff strategy when status indicates completion.
• Cache schedules for at least the schedule day and invalidate selectively when real-time indicates significant deviations.
• Store both scheduled and actual/estimated timestamps so you can present deltas and avoid recomputing delay on every request.

Practical use cases for KE at LHR

1) Flight status pages that keep passengers informed

Combine schedules (to list KE flights that include LHR) with real-time tracking (to show flight.status and gate/terminal when available). The critical fields you’ll present are:

• status from real-time
• departure.scheduled vs departure.actual
• arrival.scheduled vs arrival.estimated
• terminal and gate when those appear in the response

When status indicates the flight is complete, stop polling and display actual times. If the API returns a non-standard status, display a neutral label and rely on schedule times as a fallback.

2) Delay and disruption monitoring

Detect potential delays by comparing scheduled vs actual/estimated fields:

• Compute departure delay as actual minus scheduled when both exist.
• Compute arrival delay as estimated minus scheduled while in-flight.
• Highlight terminal changes by comparing scheduled vs current terminal fields when available across endpoints.

In your alerting logic, treat missing estimated or actual times as unknown rather than on time; fall back to scheduled values and retry the live endpoint.

3) Route and ops analysis for KE at LHR

Use the schedules endpoint to enumerate KE’s planned service touching LHR, then augment with the routes endpoint for a network-level view. Historical endpoints add a retroactive layer so analysts can compare planned vs realized operations.

• Schedules: baseline plan (departure/arrival airports and UTC times).
• Routes: which city pairs are served.
• Flights history: how those operations performed on prior dates.

This separation of concerns lets you build reliable dashboards without over-polling real-time data.

Airport detail for LHR (contextual data)

The airport information category can augment your KE-at-LHR experience with time zone, terminals, and basic weather context. A typical airport info example includes:

• airport.iata and airport.icao
• timezone and location
• terminals[] and runways[]
• weather snapshot (temp_c, visibility_km, wind)

Use timezone to convert UTC schedule times for user-facing displays, and terminals[] to validate gate/terminal fields surfaced in schedules or real-time responses.

Handling time zones, caching, and edge cases

• Time zones: Treat all timestamp fields as UTC by default; the examples show Z-suffixed ISO 8601 strings. Convert to local time zones for display using airport time zone metadata when available.
• Polling frequency: For live tracking, poll infrequently outside a 3-hour window from scheduled departure; increase frequency near scheduled time and while status indicates in-flight.
• Caching: Cache schedule results for the service day and partition by airline/airport keys. Invalidate cache entries when live endpoints show material changes to estimated/actual times or terminal/gate.
• Cancelled or diverted flights: Use flight.status to detect non-standard events; when present, prioritize actual/estimated fields and suppress gate/terminal if the data is missing or in flux.
• Pagination: The schedules endpoint can return many items, especially when querying by airport. Implement pagination as documented in the API and stream results to your data store in batches.

Security, keys, and environment setup

• Authentication: Supply your key using the api_key parameter as shown in the curl examples.
• Environments: Keep your key in environment variables in CI/CD and secrets managers; avoid hardcoding.
• Testing: Use the MCP to iterate queries before wiring them into your app.
• Trial and pricing: There’s a 7-day or 50-request trial, and a Starter plan at $24.99/month. Check the website for current details.

What to compare when evaluating your KE-at-LHR build

If you are planning how to structure your integration and internal services, focus on the following dimensions with FlightLabs’ endpoints:

• Coverage fit: Confirm that the schedules and real-time categories return the fields you need (status, terminals, gates) for KE at LHR.
• Data flow: Use schedules for breadth, and layer in real-time updates during operational windows only.
• Historical backfill: Use the history category to reconcile planned vs actual after operations conclude.
• Operational costs: Balance call frequency and caching to keep within your plan while preserving freshness.

See endpoint-specific details and examples in the Documentation.

Complete real-time example: fields you’ll use on the day

The real-time tracking example response contains the fields most apps rely on during operations. Here is the shape you should design around (values are illustrative and use the documented keys):

{
"success": true,
"data": {
"flight": {
"iata": "KE000",
"icao": "KAL000",
"number": "000",
"status": "en-route",
"departure": {
"airport": "LHR",
"scheduled": "2024-11-10T12:30:00Z",
"actual": "2024-11-10T12:42:00Z",
"terminal": "4",
"gate": "A10"
},
"arrival": {
"airport": "ICN",
"scheduled": "2024-11-11T07:10:00Z",
"estimated": "2024-11-11T07:28:00Z",
"terminal": "2",
"gate": "256"
},
"position": {
"latitude": 57.1000,
"longitude": 15.2000,
"altitude": 35000,
"speed": 495,
"heading": 110
}
}
}
}

Key implementation notes:

• Use status to drive your UI state machine: scheduled → boarding → departed → en-route → arrived (your exact mapping may vary based on values returned).
• Compare scheduled to actual/estimated to display delays and automatically highlight when a flight makes up time en route.
• Use terminal and gate from the day-of-flight response only; these can change from the schedule baseline.
• Map position to your flight tracker; speed is not in knots in the example, so label units clearly or hide them from end users.

Putting it together in your stack

• Data model: Persist schedule rows keyed by airline.iata, departure.airport, arrival.airport, and UTC schedule timestamps. Store live snapshots in a separate table keyed by a stable flight identifier where available.
• Sync loop: Refresh schedule baselines on a daily cadence. During operations windows, start a live updater that polls real-time endpoints at a modest interval and writes only changed fields.
• UI behavior: Always show scheduled times; overwrite with actual/estimated when present. Surface terminal and gate from live data and fall back to schedule when live fields are missing.
• Error handling: If an endpoint responds without certain fields, treat them as unknown and retry later. Do not infer gates or status from partial data.

Get your API key and start building

You can spin up your KE-at-LHR integration in minutes. Sign up for the trial and call the endpoints directly from your environment. To begin, visit Register and follow the quick start in the Documentation. You can also test requests interactively via the MCP.

FAQ

How do I restrict schedules to only Korean Air flights that touch LHR?
Call /flights-schedules with either iataCode=KE&type=airline and then filter for LHR in departure.airport or arrival.airport, or iataCode=LHR&type=airport and filter where airline.iata equals KE.

Which timestamps should I store for delay calculations?
From schedules: departure.scheduled and arrival.scheduled. From real-time: departure.actual and arrival.estimated. Compute differences in UTC and convert to local time zones only for display.

Where do terminals and gates come from?
Terminals may appear in both schedules and real-time responses; gates are typically in real-time near departure/arrival. Always prioritize real-time fields when present.

How often should I poll the live endpoint?
Poll at a lower frequency outside operational windows, then increase polling starting a few hours before scheduled departure until arrival. Cache results and avoid re-fetching unchanged flights.

Is there a trial, and how do I get an API key?
Yes—there’s a 7-day or 50-request trial and a Starter plan at $24.99/month. Create your account and obtain a key here: Register.