o A%j@s`dZddlZddlZddlZddlmZmZddlmZddlm Z ddl m Z ddl m Z e dZeejZd d Zd d Zd dZdefddZdefddZdedefddZe defddZd6dedefddZded efd!d"Zd efd#d$Zd%efd&d'Z d(efd)d*Z!d+efd,d-Z"d efd.d/Z#defd0d1Z$d7d3d4Z%Gd5d2d2Z&dS)8a data_store.py Persistence for this project: ranked candidate lists, open/closed position state, trade records, and a full per-cycle indicator dump for every candidate monitor.py evaluates (not just the ones that trade) -- per explicit instruction to log every indicator through a symbol's whole lifecycle, same reasoning as sip_bot's append_fast_engine_ decision(): the point is being able to load a day's file into pandas afterward and see exactly what the engine saw, whether or not it ever became a real trade. Same atomic-write pattern (write to .tmp, then os.replace) and the same fcntl-based singleton lock as screener/premarket's data_store.py. N)datedatetime)Path)contextmanager) get_config) get_logger data_storecCs8td}t|dt|dt|dt|ddS)N data_storagecandidates_dir trades_dir decisions_dir state_dir) candidatestrades decisionsstate)rBASE_DIR)cfgr&/var/www/screener/trade1/data_store.py_dirs s     rcCs"tD] }|jdddqdS)NTparentsexist_ok)rvaluesmkdir)drrr ensure_dirs*srcCs tSN)rtoday isoformatrrrr _today_str/ r!pathcCsl|jjddd||jd}t|d}tj||dtdWdn1s)wYt ||dS)NTrz.tmpw)indentdefault) parentr with_suffixsuffixopenjsondumpstrosreplace)r#datatmpfrrr_atomic_write_json3s  r4c Cs|s|Szt|d}t|WdWS1swYWdStjtfyG}ztd|d|d|WYd}~Sd}~ww)NrzFailed to read z: z. Returning default.)existsr+r,loadJSONDecodeErrorOSErrorlogwarning)r#r'r3errr _read_json;s (r=recordcCsX|jjdddt|d}|tj|tddWddS1s%wYdS)NTra)r' )r(rr+writer,dumpsr.)r#r>r3rrr _append_jsonlFs "rC lock_pathc csz|jjdddt|d%}t|tjz dVWt|tjnt|tjwWddS1s6wYdS)NTrr$)r(rr+fcntlflockLOCK_EXLOCK_UN)rDlfrrr _file_lockLs ""rJrr*cCsDtdtd|d}t||tdt|d|dS)a/This project's own ranked candidate list -- data/candidates/ {date}_scanner{suffix}.json. Date-stamped so a day's runs can be reviewed and compared later. [2026-09-23] Intraday rescans pass a suffix (e.g. "_1030") so they never overwrite the opening scan, which simulate.py replays from.r_scannerz.jsonz [DATA] Wrote z candidates to N)rr!r4r:infolen)rr*r#rrrwrite_candidatesWs rOnamereturncCstd|S)Nr)r)rPrrr _state_pathfrRcCsttdiS)Npositions.json)r=rRrrrrload_positionsjrSrU positionscCs@ttdttd|WddS1swYdS)Nzpositions.json.lockrT)rJrRr4)rVrrrsave_positionsns"rWtradecCs$tdtd}t||dS)zBOne line per closed round trip -- data/trades/{date}_trades.jsonl.r _trades.jsonlN)rr!rC)rXr#rrrappend_trade_recordssrZrcCs$tdtd}t||dS)Nrz _summary.json)rr!r4)rr#rrrwrite_trades_summaryysr[c Cstdtd}|sgSg}t|d1}|D]%}|}|s$qz |t|Wqtjy@t d|YqwWd|S1sLwY|S)NrrYr5z(Skipping malformed trade record line in ) rr!r6r+stripappendr,loadsr8r:r;)r#rr3linerrrload_today_trades~s&    r`cCs8tdtd}dti|}t||dS)aOne JSON line per rule decision -- data/decisions/{date}.jsonl (monitor.py writes one when a symbol's decision state/reason changes). Carries whatever metrics the rule module returned, not just the classified state, so a day's file can be loaded into pandas and show exactly what the engine saw for every symbol at every poll -- whether or not it ever became a real trade.rz.jsonl timestampN)rr!rutcnowr rC)r>r#rrrappend_decision_recordsrc SingletonLockcCs ttdS)Nzmonitor.pid.lock)rdrRrrrracquire_singleton_lockr"rec@s*eZdZdefddZddZddZdS) rdr#cCs||_d|_dSr)r#_fh)selfr#rrr__init__s zSingletonLock.__init__cCst|jjjdddt|jd|_z t|jtjtjBWn t y(t dw|j t t |j|S)NTrr$z{Another monitor.py instance already holds the singleton lock. Refusing to start a second instance against the same account.)r#r(rr+rfrErFrGLOCK_NBBlockingIOError RuntimeErrorrAr.r/getpidflush)rgrrr __enter__s  zSingletonLock.__enter__cCs(|jrt|jtj|jdSdSr)rfrErFrHclose)rgexc_typeexc_valexc_tbrrr__exit__szSingletonLock.__exit__N)__name__ __module__ __qualname__rrhrnrsrrrrrds )rK)rQrd)'__doc__rEr,r/rrpathlibr contextlibr config_loaderr logger_setuprr:__file__resolver(rrrr!r4r=dictrCrJlistr.rOrRrUrWrZr[r`rcrerdrrrrs: