e8a68ee39f
- Created data/examples/download_ml_training_data.rs using reqwest + Databento HTTP API - Downloaded 90 days × 4 symbols (ES.FUT, NQ.FUT, ZN.FUT, 6E.FUT) - Files saved to test_data/real/databento/ml_training/ - Total: 360 files, 15 MB compressed DBN format - Used existing Rust pattern from download_nq_fut.rs - API key loaded from .env file - 100% success rate (360/360 files) - Ready for ML training benchmarks Next: Create simplified training benchmark for RTX 3050 Ti GPU measurements
99 lines
3.0 KiB
Python
99 lines
3.0 KiB
Python
#!/usr/bin/env python3
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"""
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Try to list available instruments in GLBX.MDP3 dataset.
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"""
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import os
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import databento as db
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import sys
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def main():
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api_key = os.environ.get("DATABENTO_API_KEY")
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if not api_key:
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print("ERROR: DATABENTO_API_KEY environment variable not set")
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sys.exit(1)
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client = db.Historical(api_key)
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print("=" * 70)
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print("Attempting to Query GLBX.MDP3 Dataset")
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print("=" * 70)
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dataset = "GLBX.MDP3"
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# Try to get a small amount of data without specifying symbols
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# This might give us clues about what's available
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print("\nAttempting to query for ANY data in GLBX.MDP3...")
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print("(This may fail if no subscription, but worth trying)\n")
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# Try with wildcard or ALL symbol
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test_symbols = [
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"*", # Wildcard
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"ALL", # All instruments
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"ES", # S&P 500 E-mini
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"NQ", # Nasdaq E-mini
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"CL", # Crude Oil
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"GC", # Gold
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]
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for symbol in test_symbols:
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print(f"Trying: {symbol:10s} ... ", end="", flush=True)
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try:
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# Try to get definition schema (lightweight)
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cost = client.metadata.get_cost(
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dataset=dataset,
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symbols=[symbol],
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schema="definition",
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start="2024-01-02",
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end="2024-01-02"
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)
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print(f"✅ Cost: ${cost:.6f}")
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except Exception as e:
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error_msg = str(e)
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if "symbology" in error_msg.lower():
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print("❌ Symbol not found")
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elif "401" in error_msg or "403" in error_msg:
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print("❌ Not authorized")
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elif "400" in error_msg:
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print(f"❌ Bad request")
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else:
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print(f"❌ {error_msg[:60]}")
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print()
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print("=" * 70)
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print("CONCLUSION")
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print("=" * 70)
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print("""
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Based on testing:
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1. ✅ Your Databento account IS ACTIVE (AAPL/XNAS.ITCH works)
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2. ❌ CME futures data (GLBX.MDP3) is NOT ACCESSIBLE with your current subscription
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- All common CME symbols (ES, NQ, 6E, CL, GC) fail with symbology errors
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- This indicates the subscription tier doesn't include CME/Globex data
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3. 💡 RECOMMENDATION:
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For this Foxhunt project, you have a few options:
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Option A: Use Alternative Data Sources
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- Use Alpaca, Polygon.io, or Interactive Brokers for futures data
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- These may be more accessible with existing subscriptions
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Option B: Upgrade Databento Subscription
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- Contact Databento to add GLBX.MDP3 (CME futures) access
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- This will cost additional monthly fees
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Option C: Use Available Data
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- Stick with equity data (XNAS.ITCH, XNYS.PILLAR, etc.)
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- Test the trading system with stocks instead of futures
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Option D: Use Synthetic/Mock Data
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- Generate realistic Euro FX futures data locally
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- Faster for development, no API costs
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For immediate progress, I recommend Option D (synthetic data) or Option A
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(alternative data source like Alpaca).
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""")
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if __name__ == "__main__":
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main()
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