Home → Blog

You need a dependable way to tell stakeholders what “congestion” at Ningbo (CNNBO) actually means right now, without confusing it with live AIS wait times. By the end of this post you’ll be able to query FreightPulse for Ningbo’s latest PortWatch-backed congestion snapshot, understand the 7-day average vs 90-day baseline method, parse the response fields you need (congestion, ratio_vs_baseline, as_of), and ship a production-safe integration.

What “congestion” means here (and what it doesn’t)

The congestion label you’ll fetch for Ningbo is not a measure of vessel wait time or anchorage delays from live AIS. Instead, it is an activity classification derived from port-call volumes: a 7-day average compared to a 90-day baseline at the same port. Lower-than-usual calls can still coincide with real-world waiting offshore; the metric is about throughput, not queue length.

Illustration: Ningbo Congestion Today

FreightPulse exposes this as an easy-to-read congestion/activity tag, alongside the actual numeric series in the payload (recent and baseline average port calls per day) so you can compute and log your own thresholds if needed. If you need live anchorage or queueing estimates, you would need a different data product; this endpoint intentionally reports PortWatch-based activity.

Data source and lag: IMF PortWatch

Ningbo’s congestion/activity in FreightPulse comes from IMF PortWatch, which aggregates UN Global Platform AIS data. The series is republished weekly, so there is a built-in lag. Plan around a ~6–7 day delay between “today” and the last as_of date, though the dataset’s metadata can vary within a broader 4–11 day range. Always check as_of in the API response before displaying a “today” badge in your UI.

Because of this lag, the label is a recent-history snapshot, not a live signal. If you have an on-call workflow or alerts, schedule updates on a weekly cadence and cache results to avoid treating the dataset as real-time telemetry.

How to query Ningbo (CNNBO)

Use the authenticated GET endpoint with the port code CNNBO. Authentication is a simple header with your API key.

Copy-pasteable curl:

curl -H "X-API-Key: YOUR_API_KEY" "https://freightpulsehq.com/api/v1/port-congestion?port=CNNBO"

Official JSON response example for CNNBO:

{
    "success": true,
    "data": {
        "results": [
            {
                "port": "Ningbo",
                "locode": "CN NBO",
                "country": "China",
                "activity": "moderate",
                "congestion": "moderate",
                "as_of": "2026-11-06",
                "metrics": {
                    "recent_avg_portcalls_per_day": 48.9,
                    "baseline_avg_portcalls_per_day": 46.5,
                    "ratio_vs_baseline": 1.05
                }
            }
        ],
        "global_summary": {
            "ports_high_activity": 0,
            "ports_moderate_activity": 1,
            "ports_low_activity": 0,
            "ports_high_congestion": 0,
            "ports_moderate": 1,
            "ports_low": 0
        },
        "meta": {
            "source": "IMF PortWatch (portwatch.imf.org) - UN Global Platform AIS data",
            "data_lag_days": "4-11 (PortWatch republishes the daily series once a week; check as_of)",
            "methodology": "activity is port-call volume, not congestion: last 7 days' avg calls vs a 90-day baseline for the same port. low means fewer calls than usual, which can be a closure or ships waiting offshore. It does not measure vessel wait or anchorage time. congestion is a deprecated alias of activity."
        }
    },
    "meta": {
        "request_id": "b3f4da66-d18f-402a-a7f2-689d4e5aefb8"
    }
}

What to read from this payload:

Reading congestion fields in code

The example below fetches Ningbo’s record, checks the envelope, finds the first result, and emits the three fields you’ll likely present: congestion, as_of, and ratio_vs_baseline. It also shows a simple guard around missing fields and a basic cache hint.

Python example

import os
import time
import json
import requests

API_KEY = os.environ.get("FREIGHTPULSE_API_KEY", "YOUR_API_KEY")
URL = "https://freightpulsehq.com/api/v1/port-congestion"
PARAMS = {"port": "CNNBO"}
HEADERS = {"X-API-Key": API_KEY}

def fetch_ningbo_congestion():
r = requests.get(URL, params=PARAMS, headers=HEADERS, timeout=20)
r.raise_for_status()
payload = r.json()
if not payload.get("success"):
raise RuntimeError("API returned success=false")
data = payload.get("data", {})
results = data.get("results", [])
if not results:
raise RuntimeError("No results for CNNBO")
row = results[0]

congestion = row.get("congestion") or row.get("activity")
as_of = row.get("as_of")
metrics = row.get("metrics", {})
ratio = metrics.get("ratio_vs_baseline")

# Basic validation
if congestion is None or as_of is None or ratio is None:
raise RuntimeError("Missing expected fields (congestion/as_of/ratio_vs_baseline)")

return {
"congestion": congestion,
"as_of": as_of,
"ratio_vs_baseline": ratio,
"recent_avg": metrics.get("recent_avg_portcalls_per_day"),
"baseline_avg": metrics.get("baseline_avg_portcalls_per_day"),
}

def main():
# Example: naive in-memory cache for ~12 hours, aligned with PortWatch weekly cadence
cache_path = "/tmp/cnnbo_congestion.json"
max_age_seconds = 12 * 3600

use_cache = False
if os.path.exists(cache_path):
age = time.time() - os.path.getmtime(cache_path)
use_cache = age < max_age_seconds

if use_cache:
with open(cache_path, "r") as f:
result = json.load(f)
else:
result = fetch_ningbo_congestion()
with open(cache_path, "w") as f:
json.dump(result, f)

# Display concise status for a UI widget
status = (
f"Ningbo congestion: {result['congestion']} | "
f"ratio_vs_baseline: {result['ratio_vs_baseline']} | "
f"as_of: {result['as_of']}"
)
print(status)

if __name__ == "__main__":
main()

Interpreting the 7-day vs 90-day comparison for CNNBO

The key metric is the ratio of recent average port calls per day (7-day window) to the port’s own 90-day baseline. A ratio around 1.0 means activity is near its typical level for the last quarter. A value above 1.0 suggests higher-than-baseline call activity; below 1.0 suggests fewer calls than usual.

In the sample, metrics.ratio_vs_baseline is 1.05 for Ningbo. That’s roughly +5% above baseline activity as of 2026-11-06. Whether you treat 1.05 as “moderate” depends on your alerting thresholds. The categorical congestion label already maps this into a human-friendly bucket, but many teams display both: a badge for at-a-glance consumption and the exact ratio for power users.

Practical integration details that prevent drift

UI patterns that work for Ningbo status

Field-by-field notes for CNNBO

End-to-end flow you can ship this week

  1. Fetch CNNBO once daily using your API key and the endpoint shown above.
  2. Verify success, parse results[0], extract congestion, as_of, and metrics.ratio_vs_baseline.
  3. Cache for 12–24 hours. If as_of hasn’t advanced, keep the current UI state and postpone alerts.
  4. Render: “Ningbo: moderate” and “as_of 2026-11-06; 7d/90d ratio 1.05.”
  5. Surface an info tooltip explaining PortWatch lag and that this is not live AIS wait time.

FAQ

Is this live congestion or queue time for Ningbo?
No. It’s a PortWatch activity snapshot: a 7-day average of port calls versus a 90-day baseline. It does not measure anchorage or berth waiting time.

How fresh is the Ningbo data?
Expect a ~6–7 day lag, with PortWatch’s metadata indicating a 4–11 day window depending on the weekly republication. Always display the as_of date.

What fields should I store for analytics?
Store as_of, congestion, metrics.recent_avg_portcalls_per_day, metrics.baseline_avg_portcalls_per_day, and metrics.ratio_vs_baseline. Keep the raw JSON for audit if your retention policy allows.

Do I need pagination or additional parameters for CNNBO?
Not for this use case. The provided endpoint takes port=CNNBO and returns a concise result set for Ningbo.

Can I call this without an API key?
Yes, but guests are limited to 100 requests per day per IP. For production services, use the X-API-Key header.

Next steps: create an API key and wire the CNNBO call into your job queue. The docs cover additional fields and context you might want to expose in your UI. Register for access and start integrating today: Register. For implementation details and field references, see the Documentation.