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
108 lines
2.4 KiB
Markdown
108 lines
2.4 KiB
Markdown
# Data Quality Validation
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## Quick Reference
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### Validate Data
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```bash
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# Single symbol
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cargo run -p backtesting_service --bin validate_dbn_data -- --symbol ES.FUT
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# All symbols
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cargo run -p backtesting_service --bin validate_dbn_data -- --all
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# With HTML report
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./scripts/validate_data_quality.sh --all --output reports/
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```
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### CI/CD Integration
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```bash
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# Run validation in CI/CD (exits 1 on failure)
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./scripts/validate_data_quality.sh --all --fail-on-poor-quality --min-quality 70
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```
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### Pre-commit Hook
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```bash
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# Install validation hook
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git config core.hooksPath .githooks
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# Now new DBN files will be validated before commit
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git add test_data/real/databento/ES.FUT_new.dbn
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git commit -m "Add new data" # ← Validation runs automatically
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```
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## Quality Standards
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| Score | Rating | Status |
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|-------|--------|--------|
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| 90-100 | EXCELLENT | ✅ Production Ready |
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| 75-89 | GOOD | ✅ Production Ready |
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| 60-74 | ACCEPTABLE | ⚠️ Review Recommended |
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| 40-59 | POOR | ❌ Not Production Ready |
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| 0-39 | CRITICAL | ❌ Data Corrupted |
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## Validation Checks
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- ✅ OHLCV relationship validation
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- ✅ Price range sanity checks
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- ✅ Volume validation (>0, realistic ranges)
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- ✅ Timestamp continuity (no gaps, correct ordering)
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- ✅ Anomaly detection (spikes, duplicates, corruption)
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- ✅ Data completeness metrics
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## Documentation
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See [DATA_VALIDATION_GUIDE.md](docs/DATA_VALIDATION_GUIDE.md) for:
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- Detailed usage instructions
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- CI/CD integration guide
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- Troubleshooting tips
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- Performance benchmarks
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- Best practices
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## Files
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```
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services/backtesting_service/
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src/bin/validate_dbn_data.rs # Validation tool (binary)
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scripts/
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validate_data_quality.sh # CI/CD integration script
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.githooks/
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pre-commit-data-validation # Git pre-commit hook
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.github/workflows/
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data-quality-validation.yml # GitHub Actions workflow
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docs/
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DATA_VALIDATION_GUIDE.md # Complete documentation
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```
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## Status
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**Production Ready** ✅
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- Comprehensive validation suite
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- Multiple report formats (text, JSON, HTML)
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- CI/CD integration with exit codes
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- Pre-commit hook for data integrity
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- Automated anomaly detection
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## Quick Test
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```bash
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# Test validation tool
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--symbol ES.FUT \
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--format html \
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--output /tmp/validation_report.html
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# View report
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xdg-open /tmp/validation_report.html
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```
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---
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**Agent 18 Complete** - Comprehensive data quality validation tools deployed
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