o ?jI<@sdZddlZddlZddlmZddlmZddlmZddlZe dddl m Z ddl mZedZejdeeddlmZddlZed Zed d Zed d d ZddZddZddZddZd0ddZddZddZ ddZ!edZ"d d!Z#d1d$d%Z$e%d&krd'ej&vrej&ej&'d'd(d)krd)nd"Z(d*ej&vZ)ej&d(d+kre(d)kre"ned d,Z*e+d-d.e*,d/DZ-nej&d(gZ-e-D] Z.e$e.e(e)qdSdS)2a analyze_trades.py -- [2026-09-30] The user: "evaluate each trade today, analyze how you could have made money on each one of them and add it to the play book". For every trade the bot made on a day: - official 1-min bars 9:30-16:00, VWAP, volume vs the 14-day normal for that minute - the bot's trade: entry/exit, best price reached after the buy (MFE) and worst (MAE), what holding to the close would have made - the RIGHT trade (hindsight), buying and selling on 1-min closes: (a) while the bot was watching the stock (its scanner windows) (b) at any time of the day - measured signals at the right entry and right exit (what the bot would need to see) - pattern labels for the entry and the exit Each trade becomes one CASE, appended to data/playbook/cases.jsonl (the playbook / case library the user wants the bot to learn from), plus a chart per trade. python3 analyze_trades.py 2026-09-30 the trade bot's trades that day python3 analyze_trades.py all --source sip --no-charts [2026-09-30] every day of the sip_bot's trades (/var/www/screener/premarket, READ ONLY); it logs no watch windows, so its "right trade" window is the hour around its buy 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