How to Track Fuel Prices Programmatically in 2026

The Problem with Manual Fuel Price Tracking

If you're running a fleet, managing logistics, or calculating fuel surcharges, you know the pain of manual fuel price tracking:

• Time-consuming: Checking multiple websites daily for price updates
• Error-prone: Manual data entry leads to mistakes
• Delayed reactions: Price changes happen faster than you can update spreadsheets
• No historical data: Hard to analyze trends without systematic tracking

The Solution: API-Based Fuel Price Tracking

A fuel price tracking API solves all these problems by giving you programmatic access to real-time and historical fuel prices. Here's what you get:

Step-by-Step Tutorial: Python Integration

Let's build a simple fuel price tracker in Python. This will take about 10 minutes.

Step 1: Get Your API Key

Sign up for a free account at OilPriceAPI to get your API key. The free tier includes 50 requests per day.

Step 2: Install Dependencies

pip install requests

Step 3: Basic Fuel Price Fetcher

import requests

API_KEY = "your_api_key_here"
BASE_URL = "https://api.oilpriceapi.com/v1"

def get_fuel_prices():
    """Fetch current fuel prices"""
    headers = {"Authorization": f"Token {API_KEY}"}
    response = requests.get(f"{BASE_URL}/prices/latest", headers=headers)
    return response.json()

# Get current prices
data = get_fuel_prices()

# Extract specific fuel prices
diesel = data["data"].get("DIESEL_US_USD", {})
gasoline = data["data"].get("GASOLINE_US_USD", {})

print(f"Diesel: {diesel.get('price', 'N/A')} USD/gallon")
print(f"Gasoline: {gasoline.get('price', 'N/A')} USD/gallon")

Step 4: Automated Daily Tracking

import requests
import csv
from datetime import datetime

API_KEY = "your_api_key_here"
BASE_URL = "https://api.oilpriceapi.com/v1"

def track_and_save_prices():
    """Fetch prices and save to CSV for analysis"""
    headers = {"Authorization": f"Token {API_KEY}"}
    response = requests.get(f"{BASE_URL}/prices/latest", headers=headers)
    data = response.json()

    # Extract prices
    prices = {
        "date": datetime.now().isoformat(),
        "diesel": data["data"].get("DIESEL_US_USD", {}).get("price"),
        "gasoline": data["data"].get("GASOLINE_US_USD", {}).get("price"),
        "wti_crude": data["data"].get("WTI_USD", {}).get("price"),
        "brent_crude": data["data"].get("BRENT_CRUDE_USD", {}).get("price"),
    }

    # Append to CSV
    with open("fuel_prices.csv", "a", newline="") as f:
        writer = csv.DictWriter(f, fieldnames=prices.keys())
        if f.tell() == 0:  # Write header if file is empty
            writer.writeheader()
        writer.writerow(prices)

    return prices

# Run this daily with cron or scheduled task
prices = track_and_save_prices()
print(f"Saved prices: {prices}")

Step 5: Fuel Surcharge Calculator

def calculate_fuel_surcharge(base_rate: float,
                             baseline_diesel: float = 2.50) -> float:
    """
    Calculate fuel surcharge based on current diesel price.
    Common formula: (Current - Baseline) / Baseline * Base Rate
    """
    headers = {"Authorization": f"Token {API_KEY}"}
    response = requests.get(f"{BASE_URL}/prices/latest", headers=headers)
    data = response.json()

    current_diesel = data["data"].get("DIESEL_US_USD", {}).get("price", 0)

    if current_diesel <= baseline_diesel:
        return 0.0  # No surcharge if below baseline

    surcharge_pct = (current_diesel - baseline_diesel) / baseline_diesel
    surcharge = base_rate * surcharge_pct

    return round(surcharge, 2)

# Example: $1000 base freight rate
surcharge = calculate_fuel_surcharge(1000.00)
print(f"Fuel surcharge: {surcharge} USD")

Real-World Use Cases

Frequently Asked Questions