Caching & monitoring
Empty-list and zero-alert semantics: Error handling. Platform HTTP errors and retries: Error Handling.
Data freshness
| Endpoint | Update cadence | Recommended TTL | Notes |
|---|---|---|---|
GET /notams/{icao} | Continuous | 5 min max | NOTAMs are issued, amended, and cancelled at any time |
GET /delays/faa | Every 2–5 min (ATCSCC) | 2–5 min | Nationwide snapshot; ground stops can appear with no advance notice |
GET /delays/faa/{icao} | Every 2–5 min (ATCSCC) | 2–5 min | Airport-specific slice of the same feed |
Do not cache longer than the recommended TTL for either endpoint. A ground stop issued while a stale cache entry is served means your users see "no active delays" during an active program.
Caching
import os
import time
import requests
HEADERS = {
"X-RapidAPI-Key": os.getenv("RAPIDAPI_KEY", "YOUR_RAPIDAPI_KEY"),
"X-RapidAPI-Host": "skylink-api.p.rapidapi.com",
}
BASE = "https://skylink-api.p.rapidapi.com"
_cache: dict[str, tuple[dict, float]] = {}
NOTAM_TTL = 300 # 5 minutes
FAA_DELAY_TTL = 120 # 2 minutes
def cached_get(url: str, ttl_seconds: int) -> dict | None:
entry = _cache.get(url)
if entry and time.time() < entry[1]:
return entry[0]
r = requests.get(url, headers=HEADERS, timeout=(10, 15))
if r.status_code == 404:
return None
r.raise_for_status()
data = r.json()
_cache[url] = (data, time.time() + ttl_seconds)
return data
def get_notams(icao: str) -> dict | None:
"""Cached NOTAM fetch — 5-minute TTL."""
return cached_get(f"{BASE}/notams/{icao}", NOTAM_TTL)
def get_faa_delays_nationwide() -> dict | None:
"""Cached nationwide FAA delay snapshot — 2-minute TTL."""
return cached_get(f"{BASE}/delays/faa", FAA_DELAY_TTL)
# data = get_notams("KJFK")
# delays = get_faa_delays_nationwide()For production, replace the dict cache with a shared store (Redis, Memcached) so the cache is consistent across instances and survives restarts.
Rate limits
Every response includes rate-limit headers:
| Header | Value |
|---|---|
X-RateLimit-Requests-Limit | Your plan's monthly request quota |
X-RateLimit-Requests-Remaining | Requests left this month |
X-RateLimit-Requests-Reset | Seconds until the quota resets |
Plan quotas:
| Plan | Requests/month |
|---|---|
| Free | 1,000 |
| Basic | 5,000 |
| Pro | 50,000 |
| Ultra | 200,000 |
| Mega | 600,000 |
Monitoring and alerting
Log every NOTAM and FAA delay request, and set up active alerts for operationally significant changes:
import logging
import time
import requests
logger = logging.getLogger("alerts")
HEADERS = {
"X-RapidAPI-Key": os.getenv("RAPIDAPI_KEY", "YOUR_RAPIDAPI_KEY"),
"X-RapidAPI-Host": "skylink-api.p.rapidapi.com",
}
BASE = "https://skylink-api.p.rapidapi.com"
# Track previous counts to detect sudden changes
_prev_notam_counts: dict[str, int] = {}
_prev_faa_ground_stops: set[str] = set()
WATCHED_AIRPORTS = ["KJFK", "KLAX", "KORD"]
def check_notams_for_airport(icao: str) -> None:
start = time.monotonic()
r = requests.get(f"{BASE}/notams/{icao}", headers=HEADERS, timeout=(10, 15))
elapsed_ms = (time.monotonic() - start) * 1000
log_data = {
"endpoint": "notams",
"icao": icao,
"status": r.status_code,
"elapsed_ms": round(elapsed_ms),
"quota_remaining": r.headers.get("X-RateLimit-Requests-Remaining"),
}
if r.status_code == 200:
data = r.json()
count = data.get("total", len(data.get("notams", [])))
log_data["notam_count"] = count
logger.info("notam_fetch", extra=log_data)
prev = _prev_notam_counts.get(icao)
if prev is not None and abs(count - prev) >= 5:
logger.warning(
"notam_count_jump",
extra={"icao": icao, "prev": prev, "current": count},
)
_prev_notam_counts[icao] = count
elif r.status_code == 404:
logger.info("notam_not_found", extra=log_data)
else:
logger.warning("notam_error", extra=log_data)
r.raise_for_status()
def check_faa_ground_stops() -> None:
start = time.monotonic()
r = requests.get(f"{BASE}/delays/faa", headers=HEADERS, timeout=(10, 15))
elapsed_ms = (time.monotonic() - start) * 1000
log_data = {
"endpoint": "delays/faa",
"status": r.status_code,
"elapsed_ms": round(elapsed_ms),
"quota_remaining": r.headers.get("X-RateLimit-Requests-Remaining"),
}
if r.status_code == 200:
data = r.json()
total = data.get("total_alerts", 0)
log_data["total_alerts"] = total
logger.info("faa_delay_fetch", extra=log_data)
# Alert when a ground stop appears at a watched airport
current_gs = {
gs["airport"]
for gs in data.get("ground_stops", [])
if gs.get("airport") in WATCHED_AIRPORTS
}
new_gs = current_gs - _prev_faa_ground_stops
if new_gs:
logger.warning(
"ground_stop_appeared",
extra={"airports": sorted(new_gs)},
)
_prev_faa_ground_stops.clear()
_prev_faa_ground_stops.update(current_gs)
else:
logger.warning("faa_delay_error", extra=log_data)
r.raise_for_status()
# for icao in WATCHED_AIRPORTS:
# check_notams_for_airport(icao)
# check_faa_ground_stops()Alert on:
notam_count_jump— NOTAM count at a watched airport changes by 5 or more between polls; an unusual surge may indicate airspace restrictions or emergency noticesground_stop_appeared— a ground stop activates at any airport in your watch list; ground stops can block all departures with minutes of noticeelapsed_ms > 5000repeatedly — upstream latency issue; consider a timeout and fallback UIquota_remaining < 200— close to monthly limit; reduce poll frequency or upgrade planstatus == 429more than twice in a 5-minute window — your polling rate is too high
Runnable example
import os
import time
import requests
HEADERS = {
"X-RapidAPI-Key": os.getenv("RAPIDAPI_KEY", "YOUR_RAPIDAPI_KEY"),
"X-RapidAPI-Host": "skylink-api.p.rapidapi.com",
}
BASE = "https://skylink-api.p.rapidapi.com"
_cache: dict[str, tuple[list, float]] = {}
def get_notams(icao: str) -> list[dict]:
key = icao.upper()
hit = _cache.get(key)
if hit and time.time() < hit[1]:
return hit[0]
r = requests.get(f"{BASE}/notams/{key}", headers=HEADERS, timeout=(10, 15))
r.raise_for_status()
rows = r.json().get("notams") or []
_cache[key] = (rows, time.time() + 300)
return rows
if __name__ == "__main__":
rows = get_notams("KJFK")
print(f"KJFK NOTAMs: {len(rows)} (first call)")
print(f"Cached repeat: {len(get_notams('KJFK'))} NOTAMs")Related: NOTAMs · FAA delays · Error handling