o yjd?Z d.ed@ed+e!fdAdBZ"dCZ#dDZ$dEZ%dFZ&dGZ'dHZ(dIZ)dJe*dKedLedMedNe*dOed+efdPdQZ+ ' ' R ' 'd\d(ed.edSedTedUd&dVedWedOed+efdXdYZ,d'S)]a! stream_features.py [SIMULATION-ONLY 2026-09-05] Pure computation layer over stream.py's rolling buffers (1-min bars, 30s-default sub-bars with tick counters, latest quote) producing one normalized StreamFeatures snapshot per symbol. NOT consumed anywhere in the live bot yet -- see config.json's stream_features._note. This is the foundation trend_engine.py / regime_engine.py / prediction_engine.py will build on next. No state, no file I/O, no network calls -- a pure function of whatever bars/bars_sub/quote/prior are handed to it, same contract as intraday_health.compute_health(). Nearly every calculation here is a thin wrapper over indicators.py functions that already exist and are already used elsewhere in this project (vwap, ema_series, atr, rsi, normalized_slope_pct, consolidation_tightness, spread_pct) -- this module's job is assembling them into the richer feature set the prediction engine needs, not inventing new math. TWO DIFFERENT KINDS OF "ACCELERATION" -- deliberately kept separate: 1. Cross-horizon comparison (slope.* below): slope_30s vs slope_1m vs slope_3m vs slope_5m computed from the SAME snapshot of bars, no history required. If shorter horizons show a progressively stronger move in the same direction than longer horizons, that's "accelerating"; the reverse pattern is "decelerating." This is what the project's original design brief's worked examples (5m +0.20%, 3m +0.35%, 1m +0.50%, 30s +0.70% => accelerating) actually describe -- a shape comparison at one instant, not a time derivative. See acceleration.momentum_acceleration. 2. True time-derivative (acceleration.velocity_acceleration / slope_acceleration): this reading's velocity/slope minus the PRIOR reading's, normalized by elapsed time. Needs the caller to hold and pass in the previous StreamFeatures for this symbol (`prior` param) -- this module stays stateless; state ownership lives with the caller, same pattern as intraday_health.compute_health()/update_health_state()'s `persisted` dict. ) dataclassfield)datetimetimezone) get_config) vwap vwap_series vwap_slopeextension_from_vwap_pct ema_seriesatrrsinormalized_slope_pctconsolidation_tightness spread_pctclassify_slope min_bars_1m min_bars_subslope_sub_lookback_bucketsvwap_time_window_bars ema9_period ema20_periodema_slope_lookback_bars rsi_period atr_periodrange_expansion_lookback_bars#pressure_velocity_scale_pct_per_secg?pressure_weightsg?gffffff?g?)uptickvelocityvolumevwap_min_hold_bars_for_supportvwap_min_rejections_for_failurevwap_max_extension_atrg@vwap_flat_slope_threshold_pctg{Gz?c@s&eZdZUeed<eed<dZeed<ee dZ e ed<ee dZ e ed<ee dZ e ed<ee dZe ed <ee dZe ed <ee dZe ed <ee dZe ed <ee dZe ed <ee dZe ed<ee dZe ed<ee dZe ed<ee dZe ed<ee dZe ed<ee dZe ed<dS)StreamFeaturessymbol computed_atFinsufficient_data)default_factorymissingmetapricer'slope accelerationr(rema volatilityr quote trade_flowpressureN)__name__ __module__ __qualname__str__annotations__rr0boolrlistr2dictr3r4r'r5r6r(rr7r8r r9r:r;rDrDstream_features.pyr-Is$  r-Nr.r2r/returncCst||p ttjd|dS)NT)r.r/r0r2)r-rnowrutc)r.r2r/rDrDrE _insufficient_srIbarscCsdd|DS)NcSg|]}|dqS)crD.0brDrDrE gz_closes..rD)rJrDrDrE_closesfsrRn_barscCst||kr || dS|SN)len)rJrSrDrDrE_windowjsrVrGthencCs|dkrdS|||dS)NrY@rD)rGrWrDrDrE _pct_changensrZN@ bar_secondscCs8t|t|d}t|dkrdStt|}|d|S)a7normalized_slope_pct() over the last n_bars closes, converted to a %-per-MINUTE basis via (60 / bar_seconds) -- 'slope over an N-bar window,' the same standard interpretation intraday_health.py already uses for its own slope_lookback_bars (documented there as roughly an N-minute window at 1-min bars). [BUGFIX 2026-09-05] normalized_slope_pct() returns %-change PER BAR, not per unit time -- comparing that raw value between a 60s-bar series and a 30s-bar series is comparing different units (a "slope of 8 per bar" on 30s bars is a FASTER underlying rate than "8 per bar" on 60s bars, since each 30s bar covers half the time). Confirmed live in this module's own testing: an explicitly accelerating synthetic price series produced a NEGATIVE momentum_acceleration (the cross-horizon waterfall read as decelerating) purely because slope_sub (30s bars) was being compared unscaled against slope_1m/ 3m/5m (60s bars). Every horizon must be expressed on the same per-minute basis before any cross-horizon comparison (this function's output, and everything downstream: acceleration.momentum_acceleration here and trend_engine.py's flat-threshold classification) is meaningful. Floors the window at 2 bars: a regression line through a single point is undefined and normalized_slope_pct() correctly returns 0.0 for it per its own guard -- silently reading that 0.0 as "flat" would be indistinguishable from an actual flat reading. n_bars=1 ("slope over the last 1 minute") is inherently meaningless as a fitted line; the last 2 bars is the smallest window that has an actual slope, and for exactly 2 points a least-squares fit reduces to the plain two-point slope anyway, so this doesn't quietly change behavior for any n_bars >= 2 call site.rrXr[)rVmaxrUrrR)rJrSr\windowper_barrDrDrE_horizon_slope_pctts    r`bar_abar_bcCst|d|ddS)Nt?)r] total_seconds)rarbrDrDrE_bucket_seconds_betweensrf window_barscstd}ttdddD]}|d|kr!|d7}qtdt|}tfddt|tD}||fS)a hold_duration_bars: current consecutive streak of closes above the running VWAP, counted backward from the latest bar (0 if the latest close is at/below VWAP right now). rejection_count: within the last `window_bars`, how many bars had their HIGH reach or cross the running VWAP but still CLOSED below it -- an intrabar rejection, distinct from simply trading below VWAP the whole bar. rrLc3s@|]}|d|kr|dkrnndVqdS)rLhrhNrD)rNirJseriesrDrE s,z,_vwap_hold_and_rejections..)rrangerUr]sum)rJrg hold_durationrkstartrejection_countrDrlrE_vwap_hold_and_rejectionss   rtSTRONG_VWAP_SUPPORT VWAP_RECLAIM VWAP_HOLDVWAP_EXTENSION VWAP_FAILURE VWAP_FLATVWAP_DECLININGabove slope_classrqrsextendedcfgcCsd|r|rtS|r|dkrtS|r||dkrtS|r |dkr tS|r$tS|dks.||dkr0tStS)a Exhaustive, priority-ordered, mutually exclusive classification -- see module docstring / config.json's stream_features._note_vwap_classes for the full reasoning behind each branch. A symbol repeatedly holding above a positively-sloped VWAP (STRONG_VWAP_SUPPORT) should read as meaningfully more confident than one merely above a flat VWAP this instant (VWAP_HOLD) -- that's the whole point of this classification existing on top of the raw price_vs_vwap_pct/slope fields. negativer)rr*)rxr{VWAP_STRONG_SUPPORTrvrwryrzr|r}rqrsr~rrDrDrE_classify_vwaps   rbars_subavg_vol_baselinepriorsub_bucket_secondsas_ofc Ts it|p tdi}|pttj} g} t||dkr(t|gd| dS|d} | d} d| i} |dd }|| d <|rH| ||d nd | d <dD]!\}}t||kr`|d|dnd | |<| |d uro| |qNt|dkr|dd| d<n d | d<| di}t|dkr|d}t || }t | |d||d<n d |d<| dt|dkr|d}t |d}t | |d||d<n d |d<| dt |dt |dt |dd}t||dkrttt||d}|dt |d|d<n d |d<| d|d|d|dg}|dd ur#| |d|ddkr,dn |ddkr5dnd}|dkrF|d|d|n|d|d}dt|di}|d ur|jst|jtrot | |jd nd }|d}|jr|jdnd }|d ur|d urt|||d!|d"<nd |d"<|d}|jr|jdnd }|d ur|d urt|||d!|d#<n d |d#<nd |d"<d |d#<| d$td%d&t|dDtd'd&t|dDd(} t|dkr|dd$| d)<nd | d)<d*d+|D}!t|!dkr9t|!d}"t|!d |"|"p d,}#t|!|"d t|!|"}$t|$|#d| d-<n d | d-<| d-|rQtt|!|d| d.<nd | d.<t|t|dkrmt|tdt|dd/nd0}%t||d1}&tfd2d&|&Dt|&d }'tdt|%dtt| dt|'dtd |'dd3}(t|})t|)|d4}*t|)|d5}+|*r|*dnd },t|d6t|*}-|-dkrt|*|- d nd0}.|,d urt|,dnd |+rt|+ddnd t|.d|,rtt | |,dnd d7}/t|t|d8t dt|dd9}0| r|0| d nd0}1t|tdt|d/}2|d:}3t|d tdt| p;||3d/}4|4dkoK|2|4|4d }5t|0dt|1d|0r`t| |0dnd |5d;urkt|5dnd d<}6|0r|,d urt| |,|0dnd |/d=<t ||d1\}7}8r|%d nd0}9t!|9|d>}:|6d?};|;d uot"|;|d@k}<|7|(dA<|8|(dB<t#| k|:|7|8|<|dC|(dD<|dE}=t$||=d9}>t||=dk}?|?s| dFt|>d|?dG}@|r|\}A}B}C|A|Bt|B|Adtt%|A|BddH}Dn d d d d dH}D| dI|rM|d}E|EdJd}F|EdKd}G|EdLd}H|Ft|Ft |dd|Fr=t|G|Fdnd |FrHt|H|Fdnd dM}In d d d d dM}I| dN|dOi|IdP|IdQ}J}K|Jd ur|Kd urt dRtd |J|KdS<|d}L|Ld ur|dTpd,}Mt dRtd |L|MdU<| d-}N|Nd urt dRtd |Nd dV<rtfdWd&D}OttfdXd&D|Od d}Pnd }P| dYd }Q|Pd ur|d ur|js|j&r|j&dZ}R|Rd urt|P|Rd}Q|P|Qd[}St'diid\|d]| d^d;d_| d`da|idb| dU|dc|dd|dV| de|(df|/dg|6dh|@dI|DdN|IdY|SS)ja  bars: 1-min bars, oldest first (stream.StreamManager.get_bars()). bars_sub: sub-minute bars, oldest first, forming bucket included (stream.StreamManager.get_bars_sub()) -- each carries tick_count/upticks/downticks alongside o/h/l/c/v. quote: (bid, ask, timestamp) or None. avg_vol_baseline: same "expected normal volume" baseline entry_engine/intraday_health already take -- used for relative_volume-style comparisons. None is handled (volume.relative_volume simply omitted from output). prior: this symbol's previous StreamFeatures reading, or None on the first call -- see module docstring's two-kinds-of- acceleration note. Caller-held; this function never stores anything itself. sub_bucket_seconds: must match whatever streaming. sub_minute_bucket_seconds actually is, so time-normalized calculations (velocity, acceleration) use the real elapsed time rather than an assumed 30. as_of: [FEATURE 2026-09-05] the moment this reading is "as of," used for computed_at (and therefore the elapsed-time base for acceleration vs `prior`). Defaults to real wall-clock time (datetime.now()), correct for live use where a bar really does arrive at roughly the same real-world instant it's timestamped. A REPLAY/BACKTEST caller MUST pass the bar's own timestamp here instead -- otherwise computed_at would be the real time the backtest script happens to execute, completely unrelated to the simulated market time being replayed, which would corrupt every acceleration calculation that compares consecutive readings' elapsed time. stream_featuresr) r4r'r5r(rr7r8r r:)r/rirLlastroopenrYNextension_from_open_pct))price_1mrh)price_3mr)price_5mrr price_sub velocity_1mrh velocity_subrr)slope_1mslope_3mslope_5mrr[ slope_subrrrmomentum_accelerationrrdr#velocity_accelerationslope_accelerationvcs|]}|dVqdSrNrDrMrDrDrErn}z#compute_features..csrrrDrMrDrDrErn~r) volume_1m volume_3m volume_5m volume_subcSrK)rrDrMrDrDrErPrQz$compute_features..g& .>volume_accelerationrelative_volume)lookbackrXrc3s |] }|dkrdVqdS)rLrhNrDrM)v_waprDrErn)valuer5price_vs_vwap_pcttime_above_pcttime_below_pctrrr)ema9ema20 ema9_slopeprice_vs_ema9_pctr!)periodr"F)r atr_pctvwap_distance_atrrange_expansion_pctprice_vs_ema9_atrr,rr+hold_duration_barsrsrclassificationrzFrsi (insufficient history -- neutral 50.0 default, not a real reading))rhas_full_history)bidaskspreadrr9 tick_countupticks downticks)tick_count_subtrades_per_second uptick_ratiodowntick_ratior:r%rrgr&r$r'r(c3s|]}|VqdSrTrDrNk)pwrDrErnrc3s |] }||VqdSrTrDr) componentsrrDrErnrr;score)rr5r.r/r0r2r3rr4r5r6rr7r8r rD)(DEFAULT_CONFIGrgetrrGrrHrUrIappendrfrZr]r`rrRrVroundr0 isinstancer/rer'r5rprr minr r r rrtrabsrr rr;r-)Tr.rJrr9rrrrrnow_tsr2now_bar last_pricer4 session_openlabelnr'prev_barelapsedprev_sub elapsed_subr5 per_bucket horizon_chainlong_horizon_signrr6v_nowv_prevs_nows_prevr(vols_1mmidearlyrecentv_sloperg time_abovevwap_out closes_all ema9_series ema20_seriesema9_now ema_lookbackrema_outartightness_recenttightness_lookbacktightness_earlierrange_expansionr8rqrsvwap_slope_pctr} vwap_atr_distr~r rsi_valuersi_has_full_historyrsi_outrr_ts quote_out current_subrrrr:uptick_r downtick_rv_subscale vol_accel weight_sumpressure_scorepressure_slope prior_score pressure_outrD)rrrrEcompute_featuress$   $           (       ,"   $                  ( $   rrT)r[)NNrNN)-__doc__ dataclassesrrrr config_loaderr indicatorsrrr r r r r rrrrrr-r?rBrIrRintrVfloatrZr`rCrftuplertrrvrwrxryrzr{rArrrDrDrDrEs) 4    &