You need a reliable, developer-friendly way to fetch the EIA-sourced Gulf Coast gasoline metric for financial models, budgeting, and hedging dashboards. By the end of this tutorial, you will be able to authenticate, call the FreightPulse Finance endpoint that serves Gulf Coast gasoline data, parse the response you care about, and embed it into cost models or monitoring jobs with production-grade guardrails.
What you get from this Finance feed (and what you don’t)
The FreightPulse Finance fuel endpoint returns gasoline and diesel information sourced from the U.S. Energy Information Administration (EIA). Values are in USD per gallon, wrapped in a JSON envelope, and timestamped in ISO 8601 with timezone. The metric of interest here is Gulf Coast Gasoline. You will see gasoline grades alongside aggregates such as 30-day and 90-day averages. Do not treat any of these as a national freight rate or a live market quote; they are EIA-level fuel benchmarks intended for finance and planning workflows.
Important constraints and facts you should keep in mind:
- Auth: set header X-API-Key: YOUR_API_KEY. Guest access without a key is allowed at 100 requests/day per IP.
- Envelope: every payload follows {"success": true, "data": {...}} with optional "meta".
- Units/currency: USD per gallon.
- Timestamps: ISO 8601 with timezone (e.g., 2026-10-03T00:00:19+00:00).
- Historical framing: a request may return aggregates (e.g., 30d and 90d averages). Treat these as period statistics, not tick-by-tick series.
- Port congestion data on FreightPulse comes from IMF PortWatch and is lagged about 6–7 days (7-day average vs 90-day baseline). It is not live AIS and is separate from fuel prices; don’t conflate these sourcing and latency characteristics with the fuel feed.
Authentication and request limits
For production, pass an API key in the header X-API-Key. If you don’t yet have a key, you can still test the Finance endpoint as a guest with a limit of 100 requests/day per IP. To obtain a key for sustained workloads or higher limits, use the registration link at the end of this post.
- Header: X-API-Key: YOUR_API_KEY
- Guest without key: 100 requests/day per IP
The exact curl you can run
The following sample shows a historical query for the EIA Gulf Coast gasoline metric. Copy it verbatim to validate your connectivity and confirm field names and units. Note that the response is wrapped in an envelope with success and data at the root.
curl -H "X-API-Key: YOUR_API_KEY" "https://freightpulsehq.com/api/v1/historical?metric=fuel_price_gasoline_gulf_coast&period=30d"Official JSON example and what to read from it
This is the official sample response. Use it to map fields in your client code. Do not substitute different field names, and do not assume unsourced values beyond what is present.
{
"success": true,
"data": {
"timestamp": "2026-10-03T00:00:19+00:00",
"source": "EIA (U.S. Energy Information Administration)",
"currency": "USD",
"unit": "gallon",
"data": {
"diesel": {
"national_average": 6.382,
"change_week": -0.147,
"change_percent": -2.25,
"updated_at": "2026-09-28",
"regions": {
"east_coast": 6.137,
"midwest": 6.526,
"gulf_coast": 5.955,
"rocky_mountain": 6.407,
"west_coast": 7.357,
"california": 8.181
}
},
"gasoline": {
"national_average": 4.465,
"change_week": -0.013,
"change_percent": -0.29,
"updated_at": "2026-09-28",
"grades": {
"regular": 4.465,
"midgrade": 5.073,
"premium": 5.482
}
},
"bunker_fuel": {
"available": false,
"note": "No known free source (Rotterdam/Singapore/Houston) — requires a paid provider (e.g. Ship & Bunker, Argus)."
}
},
"historical": {
"diesel_30d_avg": 6.291,
"diesel_90d_avg": 5.561,
"diesel_yoy_change": 72,
"gasoline_30d_avg": 4.355,
"gasoline_90d_avg": 4.111,
"gasoline_yoy_change": 42.9
}
},
"meta": {
"request_id": "95242e83-a30f-4767-bcd6-bc53e60d204e"
}
}Key fields you will typically use:
- data.timestamp: when the payload was generated (ISO 8601, includes timezone offset).
- data.source: the data provenance, here the EIA.
- data.currency and data.unit: USD and gallon; all cost computations should assume these.
- data.data.gasoline.grades: grade-level gasoline figures relevant to Gulf Coast budgeting. Treat values as EIA benchmark figures, not live transactional quotes.
- data.historical.gasoline_30d_avg and gasoline_90d_avg: rolling aggregates for downstream smoothing, anomaly checks, or budget baselines.
A minimal client in Python for finance workflows
The snippet below calls the same historical endpoint shown in the curl and extracts the timestamp, currency/unit, and grade-level gasoline values for use in a financial model. It also shows a simple guard to ensure the success flag is true before reading the envelope.
import os
import sys
import json
import urllib.request
API_URL = "https://freightpulsehq.com/api/v1/historical?metric=fuel_price_gasoline_gulf_coast&period=30d"
API_KEY = os.getenv("FREIGHTPULSE_API_KEY", "YOUR_API_KEY")
def fetch():
req = urllib.request.Request(API_URL, method="GET")
req.add_header("X-API-Key", API_KEY)
with urllib.request.urlopen(req, timeout=20) as resp:
body = resp.read().decode("utf-8")
return json.loads(body)
def parse(payload):
if not payload.get("success"):
raise RuntimeError("Request did not succeed")
data = payload.get("data", {})
ts = data.get("timestamp")
currency = data.get("currency")
unit = data.get("unit")
gasoline = (data.get("data") or {}).get("gasoline") or {}
grades = gasoline.get("grades") or {}
# Example fields your finance model might consume
regular = grades.get("regular")
midgrade = grades.get("midgrade")
premium = grades.get("premium")
hist = data.get("historical") or {}
g30 = hist.get("gasoline_30d_avg")
g90 = hist.get("gasoline_90d_avg")
return {
"timestamp": ts,
"currency": currency,
"unit": unit,
"regular": regular,
"midgrade": midgrade,
"premium": premium,
"gasoline_30d_avg": g30,
"gasoline_90d_avg": g90
}
if __name__ == "__main__":
payload = fetch()
out = parse(payload)
# Print as a compact line your ETL or model runner can pick up
print(json.dumps(out, separators=(",", ":")))How to wire this into budgeting and hedging models
In finance contexts, you want a consistent metric, stable units, and documented latency. For Gulf Coast gasoline from the EIA via FreightPulse, values are USD per gallon with a timestamped envelope. Most teams integrate these values into:
- Monthly and quarterly fuel expense accrual models.
- Scenario analysis keyed to gasoline_30d_avg and gasoline_90d_avg, to reduce model variance from week-to-week changes.
- Alerts when short-term changes deviate from rolling baselines.
Keep the following practices in mind:
- Do not hardcode a national average or reuse values from unrelated series. Read only what the endpoint returns.
- Record the timestamp field with each fetched snapshot. This is crucial for auditability in financial close.
- For budgeting UIs, show grade-level values with unit and currency. If you surface week-over-week changes, read them explicitly; do not compute deltas without storing prior snapshots.
Caching, frequency, and reliability notes
Unlike high-frequency markets, EIA-sourced figures do not change intraday like exchange-traded instruments. A practical polling cadence is daily or weekly, with a short cache (e.g., 6–24 hours) to avoid redundant calls and stay under guest rate limits if you do not have a key. Include a server-side cache keyed by the metric and period to reduce cold-start latency in dashboards.
Operational suggestions:
- HTTP timeouts: 10–20 seconds are adequate for this use case.
- Retries: at-most-once semantics are acceptable for nightly ETL. If you retry, back off with jitter.
- Schema stability: extract through the documented envelope {"success": true, "data": {...}} and guard against missing subtrees (use defaults).
- Audit trails: persist the raw JSON and request_id from meta when present to aid reconciliation.
Data interpretation and guardrails
Finance users often need to contextualize whether a change is structural or transient. The presence of rolling averages (30d/90d) helps smooth volatility for planning. Treat the per-gallon values as benchmarks. Do not label any figure as a transactional or live trade price; they are from the EIA and best used for planning, procurement targets, and hedge effectiveness assessments.
A few pitfalls to avoid:
- Do not quote or store a freight-rates USD fare as “today’s price” in this context. This is a fuel benchmark stream, not a freight fare feed.
- Do not conflate FreightPulse port congestion metrics with fuel prices. Congestion is IMF PortWatch-derived and lagged by about a week, while this feed concerns EIA fuel pricing. They are separate categories with different latencies and sources.
- Do not assume a separate national benchmark unless explicitly present in the payload. Use only fields provided by the response.
Error handling and envelope validation
Always verify the success field before dereferencing data. Maintain a fallback path if success is false or if data is missing. Log the meta.request_id when present, as it allows Support to locate a specific call if you need help. If the response changes shape or a field becomes temporarily unavailable, treat it as a soft failure and alert the team while keeping prior-cached values for user-facing dashboards.
Quick checklist for production readiness
- Authentication: header X-API-Key: YOUR_API_KEY; respect the 100 requests/day per IP limit if calling as a guest.
- Parsing: expect {"success": true, "data": {...}} and read timestamp, currency, unit, gasoline.grades, and historical aggregates you depend on.
- Units: USD per gallon; display these wherever end-users or spreadsheets see the values.
- Cadence: poll daily or weekly; cache results server-side.
- Observability: log request_id and keep raw payloads for audit.
Testing and lower environments
Before moving to production, run the official curl once in CI to assert connectivity and fail fast if authentication or networking regress. In staging, compare extracted values against prior snapshots to verify that your parsing and rolling-average logic are stable. When you switch from guest to keyed access, ensure your secret management is environment-specific and that your CI does not leak the key in logs.
Common questions
How do I authenticate and what happens if I don’t provide a key?
Provide your credential in the X-API-Key header. Without a key, you can still access the Finance fuel endpoint as a guest with 100 requests/day per IP. For higher volume or guaranteed throughput, provision a key.
What are the units and currency for Gulf Coast gasoline?
All values are denominated in USD per gallon. Read currency and unit from the top-level data fields to keep your model explicit and auditable.
Is this a live, tick-by-tick market price?
No. The data is sourced from the EIA and is appropriate for finance and planning—not a live trading quote. Use rolling aggregates and timestamps for budgeting, analytics, and hedge monitoring.
Does the historical request return a time series array?
The historical payload shown here presents rolling aggregates (e.g., gasoline_30d_avg, gasoline_90d_avg) and current grade-level values inside the envelope. Treat these as period statistics and benchmarks. Do not assume an array of point-in-time ticks unless documented.
Can I combine this with FreightPulse port congestion metrics to analyze total landed cost?
You can in your own modeling, but remember FreightPulse’s port congestion is IMF PortWatch-based and lagged by ~6–7 days (7-day average vs 90-day baseline). It is not live AIS. Keep sourcing and latency separate in your calculations.
Next steps
Get a key and wire this into your cost model or dashboard. Start with the official curl above, then drop in the Python client to parse the envelope and inject USD-per-gallon values into your finance pipeline. If you need endpoint specifics, parameters, or additional Finance models, see the docs, then register for production use: