Ë /¾ðiÞãót—dZddlmZddlmZmZddlZeGd„de««ZGd„d«Z Gd „d «Z y) u9 APEX V16 — Market data provider. The indicators pipeline (analysis/tech_snapshot.py) needs OHLCV bars to compute RSI, ATR, swing levels, candle patterns, etc. Rather than coupling indicators to TopstepX (or any specific broker), we depend on the MarketDataProvider Protocol — an async source of pandas DataFrames. Concrete implementations: * BrokerMarketDataProvider: forwards to broker.fetch_bars(...). NB: BrokerBase does NOT currently expose fetch_bars; the wrapper is duck-typed and will work as soon as the broker layer adds the method (TODO tracked in BACKLOG.md). Until then, use the Fake. * FakeMarketDataProvider: returns canned DataFrames keyed by (symbol, timeframe). Used by all unit tests so we never hit a network in CI. DataFrame contract (consumer-side): - columns: open, high, low, close, volume - 'time' column or DatetimeIndex (used for candle_time stamping) - sorted ascending by time, last row = most recent bar - V15 used 'tick_volume'; the broker adapter aliases it to 'volume', so V16 standardizes on 'volume'. é)Ú annotations)ÚProtocolÚruntime_checkableNcó(—eZdZdZ dd„Zy)ÚMarketDataProviderz>Async provider of OHLCV bars. Stateless from the caller's POV.cƒó K—y­w)ae Return the last `n` bars for `symbol` at `timeframe`. Args: symbol: instrument root (e.g. "MES", "6E"). timeframe: V16 standard strings: "5min" | "1hour" | "4hour". n: number of most-recent bars requested. Returns: DataFrame with columns [open, high, low, close, volume] and either a 'time' column (UTC) or a DatetimeIndex. len(df) <= n; may be smaller near session boundaries. Empty DataFrame returned when no bars are available (callers should treat empty == "skip computation"). N©©ÚselfÚsymbolÚ timeframeÚns ú+/home/work/apex_v16/analysis/market_data.pyÚget_barszMarketDataProvider.get_bars's èø€ð* ùs‚N©r Ústrr rrÚintÚreturnz pd.DataFrame)Ú__name__Ú __module__Ú __qualname__Ú__doc__rr órrr#s0„áHð àð ðð ð ð  ð ô  rrcó0—eZdZdZdd„Z dd„Zy)ÚBrokerMarketDataProvideraÇ Wrap a broker that exposes `async fetch_bars(symbol, timeframe, n)`. BrokerBase does not yet declare fetch_bars; this class therefore relies on duck-typing. When BACKLOG item "broker_base.fetch_bars" is implemented, this becomes a typed forwarder. Until then, instantiating it against a BrokerBase that lacks fetch_bars will raise AttributeError on the first get_bars call (intentional fail-loud, per V16 architecture). có—||_y©N)Úbroker)r rs rÚ__init__z!BrokerMarketDataProvider.__init__Ps €Øˆ rcƒóXK—|jj|||«ƒd{–—†S7Œ­wr)rÚ fetch_barsr s rrz!BrokerMarketDataProvider.get_barsSs'èø€ð—[‘[×+Ñ+¨F°I¸qÓA×AÐAÐAús ‚!*£(¤*N)rÚNoner©rrrrrrr rrrrCs<„ñ óðBàðBððBð ð Bð ô Brrcó0—eZdZdZdd„Z dd„Zy)ÚFakeMarketDataProvideruÎ Canned-bars provider for unit tests. Usage: bars = {("MES", "5min"): df_m5, ("MES", "1hour"): df_h1, ("MES", "4hour"): df_h4} provider = FakeMarketDataProvider(bars) await provider.get_bars("MES", "5min", 200) If a (symbol, timeframe) key is missing, get_bars returns an empty DataFrame — same contract as a broker mid-session gap. Tracks calls in `self.calls` for assertions. có —||_g|_yr)ÚbarsÚcalls)r r's rrzFakeMarketDataProvider.__init__qs€ØˆŒ Ø13ˆ rcƒóK—|jj|||f«|jj||f«}| |jrt j gd¢¬«S|j|«jd¬«S­w)N)ÚopenÚhighÚlowÚcloseÚvolume)ÚcolumnsT)Údrop) r(Úappendr'ÚgetÚemptyÚpdÚ DataFrameÚtailÚ reset_index)r r r rÚdfs rrzFakeMarketDataProvider.get_barsusoèø€ð ‰ ×ј6 9¨aÐ0Ô1Ø Y‰Y]‰]˜F IÐ.Ó /ˆØ ˆ:˜ŸšÜ—<‘<Ò(RÔSÐ Sàw‰wq‹z×%Ñ%¨4Ð%Ó0Ð0ùs‚BBN)r'z#dict[tuple[str, str], pd.DataFrame]rr"rr#r rrr%r%as7„ñ ó4ð 1àð 1ðð 1ð ð 1ð ô 1rr%) rÚ __future__rÚtypingrrÚpandasr4rrr%r rrúr<sFðñõ6#ç.ãðô ˜ó óð ÷>BñB÷<1ò1r