Modify scripts readme to add reclamm training section#82
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…s timestamps - scripts/download_data.py: force mpire WorkerPool to start_method='spawn' so binance_historical_data workers don't fork after JAX threads (macOS). - get_binance_vision_data: vectorize timestamp normalization with numpy; handles Binance Vision's 2025+ microsecond klines and runs ~20× faster. - forward_fill_ohlcv_data: cast date_range via datetime64[ms] before int64 — pandas 3.x switched pd.date_range default unit from [ns] to [ms]. - resample frequency "1H" → "1h" (pandas 3.x dropped uppercase alias). - NOTION_GUIDE.md: setup section now reflects venv path and training-pipeline branch checkout. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Agent-facing guide covering env/venv usage, data download caveats, do_run_on_historic_data + HODL baselines, Optuna tuning, and the continuous-vs-fresh-deposit pitfall. Drops NOTION_GUIDE.md (content now lives in the team Notion page). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Ignore .venv/, .claude/, results/, and optuna_studies/ created by the simulation/tuning workflow. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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Quickstart guide to train reclamm pools (docs only, no code).