oilpriceapi 1.4.0

Official Python SDK for OilPriceAPI - Real-time and historical oil prices

OilPriceAPI Python SDK

Real-time oil and commodity price data for Python - Professional-grade API at 98% less cost than Bloomberg Terminal

Get Free API Key • Documentation • Examples • Pricing

The official Python SDK for OilPriceAPI - Real-time and historical oil prices for Brent Crude, WTI, Natural Gas, and more.

Quick start:

pip install oilpriceapi

🚀 Quick Start

Installation

pip install oilpriceapi

Basic Usage

from oilpriceapi import OilPriceAPI

# Initialize client (uses OILPRICEAPI_KEY env var by default)
client = OilPriceAPI()

# Get latest Brent Crude price
brent = client.prices.get("BRENT_CRUDE_USD")
print(f"Brent Crude: ${brent.value:.2f}")
# Output: Brent Crude: $71.45

# Get multiple prices
prices = client.prices.get_multiple(["BRENT_CRUDE_USD", "WTI_USD", "NATURAL_GAS_USD"])
for price in prices:
    print(f"{price.commodity}: ${price.value:.2f}")

Historical Data with Pandas

# Get historical data as DataFrame
df = client.prices.to_dataframe(
    commodity="BRENT_CRUDE_USD",
    start="2024-01-01",
    end="2024-12-31",
    interval="daily"
)

# Add technical indicators
df = client.analysis.with_indicators(
    df,
    indicators=["sma_20", "sma_50", "rsi", "bollinger_bands"]
)

# Calculate spread between Brent and WTI
spread = client.analysis.spread("BRENT_CRUDE_USD", "WTI_USD", start="2024-01-01")

Diesel Prices (New in v1.3.0)

# Get state average diesel price (free tier)
ca_price = client.diesel.get_price("CA")
print(f"California diesel: ${ca_price.price:.2f}/gallon")
print(f"Source: {ca_price.source}")
print(f"Updated: {ca_price.updated_at}")

# Get nearby diesel stations (paid tiers)
result = client.diesel.get_stations(
    lat=37.7749,   # San Francisco
    lng=-122.4194,
    radius=8047    # 5 miles in meters
)

print(f"Regional average: ${result.regional_average.price:.2f}/gallon")
print(f"Found {len(result.stations)} stations")

# Find cheapest station
cheapest = min(result.stations, key=lambda s: s.diesel_price)
print(f"Cheapest: {cheapest.name} at {cheapest.formatted_price}")
print(f"Savings: ${abs(cheapest.price_delta):.2f}/gal vs average")

# Get diesel prices as DataFrame
df = client.diesel.to_dataframe(states=["CA", "TX", "NY", "FL"])
print(df[["state", "price", "updated_at"]])

# Station data as DataFrame
df_stations = client.diesel.to_dataframe(
    lat=34.0522,   # Los Angeles
    lng=-118.2437,
    radius=5000
)
print(df_stations[["name", "diesel_price", "price_vs_average"]])

Price Alerts (New in v1.4.0)

# Create a price alert with webhook notification
alert = client.alerts.create(
    name="Brent High Alert",
    commodity_code="BRENT_CRUDE_USD",
    condition_operator="greater_than",
    condition_value=85.00,
    webhook_url="https://your-server.com/webhook",  # Optional
    enabled=True,
    cooldown_minutes=60  # Min time between triggers
)

print(f"Alert created: {alert.id}")
print(f"Monitoring: {alert.commodity_code}")
print(f"Condition: {alert.condition_operator} ${alert.condition_value}")

# List all alerts
alerts = client.alerts.list()
for alert in alerts:
    print(f"{alert.name}: {alert.enabled} ({alert.trigger_count} triggers)")

# Update an alert
updated = client.alerts.update(
    alert.id,
    condition_value=90.00,
    enabled=False
)

# Test webhook endpoint
test_result = client.alerts.test_webhook("https://your-server.com/webhook")
if test_result.success:
    print(f"Webhook OK: {test_result.status_code} in {test_result.response_time_ms}ms")
else:
    print(f"Webhook failed: {test_result.error}")

# Delete an alert
client.alerts.delete(alert.id)

# Get alerts as DataFrame
df = client.alerts.to_dataframe()
print(df[["name", "commodity_code", "condition_value", "trigger_count"]])

Supported operators:

• greater_than - Price exceeds threshold
• less_than - Price falls below threshold
• equals - Price matches threshold
• greater_than_or_equal - Price meets or exceeds threshold
• less_than_or_equal - Price meets or falls below threshold

Webhook Payload:

{
  "alert_id": "550e8400-e29b-41d4-a716-446655440000",
  "alert_name": "Brent High Alert",
  "commodity_code": "BRENT_CRUDE_USD",
  "current_price": 86.50,
  "condition_operator": "greater_than",
  "condition_value": 85.00,
  "triggered_at": "2025-12-15T10:30:00Z"
}

📊 Features

• ✅ Simple API - Intuitive methods for all endpoints
• ✅ Type Safe - Full type hints for IDE autocomplete
• ✅ Pandas Integration - First-class DataFrame support
• ✅ Price Alerts - Automated monitoring with webhook notifications 🔔 NEW
• ✅ Diesel Prices - State averages + station-level pricing ⛽
• ✅ Async Support - High-performance async client
• ✅ Smart Caching - Reduce API calls automatically
• ✅ Rate Limit Handling - Automatic retries with backoff
• ✅ Technical Indicators - Built-in SMA, RSI, MACD, etc.
• ✅ CLI Tool - Command-line interface included

📚 Documentation

Complete SDK Documentation → | Online Docs →

Authentication

# Method 1: Environment variable (recommended)
export OILPRICEAPI_KEY="your_api_key"
client = OilPriceAPI()

# Method 2: Direct initialization
client = OilPriceAPI(api_key="your_api_key")

# Method 3: With configuration
client = OilPriceAPI(
    api_key="your_api_key",
    timeout=30,
    max_retries=3,
    cache="memory",
    cache_ttl=300
)

Available Commodities

• BRENT_CRUDE_USD - Brent Crude Oil
• WTI_USD - West Texas Intermediate
• NATURAL_GAS_USD - Natural Gas
• DIESEL_USD - Diesel
• GASOLINE_USD - Gasoline
• HEATING_OIL_USD - Heating Oil
• View all commodities

Error Handling

from oilpriceapi.exceptions import OilPriceAPIError, RateLimitError, DataNotFoundError

try:
    price = client.prices.get("INVALID_CODE")
except DataNotFoundError as e:
    print(f"Commodity not found: {e}")
except RateLimitError as e:
    print(f"Rate limited. Resets in {e.seconds_until_reset}s")
except OilPriceAPIError as e:
    print(f"API error: {e}")

⚡ Async Support

import asyncio
from oilpriceapi import AsyncOilPriceAPI

async def get_prices():
    async with AsyncOilPriceAPI() as client:
        prices = await asyncio.gather(
            client.prices.get("BRENT_CRUDE_USD"),
            client.prices.get("WTI_USD"),
            client.prices.get("NATURAL_GAS_USD")
        )
        return prices

# Run async function
prices = asyncio.run(get_prices())

🛠️ CLI Tool

# Get current price
oilprice get BRENT_CRUDE_USD

# Export historical data
oilprice export WTI_USD --start 2024-01-01 --format csv -o wti_2024.csv

# Watch prices in real-time
oilprice watch BRENT_CRUDE_USD --interval 60

🧪 Testing

The SDK includes utilities for testing your applications:

from oilpriceapi.testing import MockClient

def test_my_strategy():
    client = MockClient()
    client.set_price("BRENT_CRUDE_USD", 75.50)

    result = my_trading_strategy(client)
    assert result.action == "BUY"

📈 Examples

Real-World Use Cases

See EXAMPLES.md for comprehensive examples including:

• 📊 Trading Strategies - Moving averages, spread analysis, risk management
• 📈 Data Analysis - Seasonal patterns, correlations, forecasting
• 💻 Web Applications - Dashboards, REST APIs, monitoring systems
• 📤 Data Export - Excel reports, database integration, alerts

Code Samples

Check out the examples/ directory for:

• Quickstart Notebook
• Data Analysis
• Trading Signals
• Async Operations

🔧 Development

# Clone repository
git clone https://github.com/oilpriceapi/python-sdk
cd python-sdk

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black .

# Type checking
mypy oilpriceapi

📝 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please see our Contributing Guide for details.

💬 Support

• 📧 Email: [e-mail]
• 🐛 Issues: GitHub Issues
• 📖 Docs: Documentation

🔗 Links

• OilPriceAPI Website
• API Documentation
• Pricing
• Status Page

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🌟 Why OilPriceAPI?

OilPriceAPI provides professional-grade commodity price data at 98% less cost than Bloomberg Terminal ($24,000/year vs $45/month). Trusted by energy traders, financial analysts, and developers worldwide.

Key Benefits

• ⚡ Real-time data updated every 5 minutes
• 📊 Historical data for trend analysis and backtesting
• 🔒 99.9% uptime with enterprise-grade reliability
• 🚀 5-minute integration with this Python SDK
• 💰 Free tier with 100 requests (lifetime) to get started

Start Free → | View Pricing → | Read Docs →

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Made with ❤️ by the OilPriceAPI Team