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
89 lines
2.7 KiB
Python
89 lines
2.7 KiB
Python
#!/usr/bin/env python3
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"""
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Find available 6E (Euro FX) contract symbols in Databento.
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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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# Check for API key
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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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# Create client
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client = db.Historical(api_key)
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print("=" * 70)
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print("Searching for 6E (Euro FX) contract symbols")
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print("=" * 70)
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# CME Euro FX Futures contracts for Jan 2024
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# Contract months: H=Mar, M=Jun, U=Sep, Z=Dec
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# For Jan 2024, we want:
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# - 6EH24 (Mar 2024 expiry) - active in Jan
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# - 6EM24 (Jun 2024 expiry) - may have volume
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# - 6EU24 (Sep 2024 expiry) - may have volume
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test_symbols = [
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"6EH24", # March 2024 expiry (most active for Jan 2024)
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"6EM24", # June 2024 expiry
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"6EU24", # September 2024 expiry
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"6EZ23", # December 2023 expiry (may still be active early Jan)
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"6E", # Continuous contract
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"6E.c.0", # Front month continuous
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]
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print("\nTesting symbols:")
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for symbol in test_symbols:
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print(f" - {symbol}")
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print()
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# Try to resolve each symbol
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dataset = "GLBX.MDP3"
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schema = "ohlcv-1m"
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start_date = "2024-01-02"
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end_date = "2024-01-05" # Just 3 days for testing
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working_symbols = []
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for symbol in test_symbols:
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try:
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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=schema,
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start=start_date,
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end=end_date
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)
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print(f"✅ {symbol:12s} - Cost: ${cost:.4f} (for 3 days)")
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working_symbols.append((symbol, cost))
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except Exception as e:
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print(f"❌ {symbol:12s} - Error: {str(e)[:60]}")
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if working_symbols:
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print()
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print("=" * 70)
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print("RECOMMENDED SYMBOLS FOR FULL DOWNLOAD (30 days)")
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print("=" * 70)
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for symbol, cost_3days in working_symbols:
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# Extrapolate cost for 30 days
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estimated_cost_30days = cost_3days * (30 / 3)
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print(f"{symbol:12s} - Estimated cost for 30 days: ${estimated_cost_30days:.4f}")
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# Recommend best option
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print()
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best_symbol = min(working_symbols, key=lambda x: x[1])
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print(f"💡 RECOMMENDED: Use {best_symbol[0]} (lowest cost)")
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print(f" Estimated 30-day cost: ${best_symbol[1] * 10:.4f}")
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else:
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print()
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print("❌ No working symbols found!")
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print("Try checking Databento documentation for correct symbology.")
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if __name__ == "__main__":
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main()
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