⚡ Bolt: Optimize trading simulation loop#4
⚡ Bolt: Optimize trading simulation loop#4google-labs-jules[bot] wants to merge 1 commit intomainfrom
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Replaced the slow `iterrows` and `.loc` based loop in `simulate_trading` with a numpy-based iteration. 💡 What: Used numpy arrays for state management (cash, btc, total_value) and iteration. 🎯 Why: `DataFrame.iterrows()` combined with `.loc` assignment is extremely slow for iterative processes. 📊 Impact: Reduced execution time for 10,000 simulated days from ~11.0s to ~0.05s (approx 200x speedup). 🔬 Measurement: Validated with a benchmark script and verified correctness by comparing output with the original implementation.
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Optimized the
simulate_tradingfunction by replacing the Pandasiterrowsloop with direct Numpy array manipulation. This change resulted in a significant performance improvement (approx 200x speedup for 10,000 iterations) while maintaining identical functionality and output. Also resolved aFutureWarningrelated to incompatible dtype assignment in Pandas.PR created automatically by Jules for task 9041770329086232914 started by @EiJackGH