**TUI v3**: Live event-driven observability terminal. All panels hooked to HZ entry listeners. Zero origin-system load.
### What changed since v6.0 (2026-06-08 — THIS VERSION)
| Area | Change |
|---|---|
| **PINK DITAv2 Kernel — Fee Sign Fix (DEFECT A)** | `bingx_user_stream.py:340` — `fee = -raw_fee`. BingX VST reports trading costs as **negative** "n" (commission) values. The kernel convention is **positive = cost**. The boundary was passing the sign through verbatim, causing the kernel to treat every cost as a maker rebate (+k_maker_rebates). Fixed at intake: `fee = -raw_fee`. Effect: k_taker_fees/k_maker_fees now accumulate correctly; k_maker_rebates stays 0 for normal fills. |
| **PINK DITAv2 Kernel — Opening Fill Fee (DEFECT B)** | `bingx_user_stream.py:343-345` — `fill_qty` now falls back to cumulative qty `z`/`cumFilledQty` when last-fill qty `l` is zero. BingX ENTER fills report qty only in `z`, not `l`. Previously `fill_qty=0` → `apply_predicted_fill()` computed zero opening fee → k_taker_fees missing one full leg per round trip. |
| **PINK DITAv2 Kernel — WARN Unfreeze (ARCH FIX)** | `_rust_kernel/src/lib.rs:730-731` — `_ => self.capital_frozen = false` (was `_ => {}` = keep-frozen). WARN (delta 0.01–20 VST) represents in-flight settlement, not an error. Keeping capital frozen during WARN permanently blocked ENTERs after the first trade because the ENTER's predicted fee briefly pushed delta into ERROR, then back to WARN. WARN is now tradeable. |
| **PINK Startup — reset_and_seed** | `pink_direct.py` — after restoring the persisted kernel snapshot, calls `kernel.reset_and_seed(live_capital)`. Zeros stale accumulators (k_realized_pnl, k_fees_paid, k_maker_rebates) and sets K=E=live BingX balance → delta=0 → capital_frozen=False at every clean start. Prevents stale snapshot capital from triggering a false ERROR freeze on restart. |
| **PINK vel_div_threshold env-override** | `launch_dolphin_pink.py` — `DOLPHIN_PINK_VEL_DIV_THRESHOLD` env var overrides the decision threshold (default `-0.02`). Useful for on-exchange debugging (e.g. `-0.005` to force ENTERs quickly). BLUE is unaffected. |
| **Accounting Math (ground truth)** | Two confirmed T-2 numbers: seed=103400.3358, realised=+53.66213, open_fee=-31.00711915, close_fee=-30.98028808. Correct k_capital=103392.0105 (matches BingX to <0.01VST).Buggyk_capitalwas103484.9782(+92.97gap→ERRORfreeze).|
---
### What changed since v5.0 (2026-04-05 — PREVIOUS)
| Area | Change |
|---|---|
| **NG8 Linux Scanner — NEW** | `- Dolphin NG8/ng8_scanner.py` — Linux-native eigenscan service replacing Windows NG7. Fixes double-output bug. Single `enhance()` call processes all 4 windows (w50/150/300/750) in one pass → exactly one Arrow file + one HZ write per scan_number. See §27. |
| **Arrow Writer Shim — NEW** | `- Dolphin NG8/arrow_writer.py` — thin re-export so `dolphin_correlation_arb512_with_eigen_tracking.py` imports correctly on Linux (Windows had this file natively). |
| **TUI v3 — NEW** | `Observability/TUI/dolphin_tui_v3.py` — full live observability terminal. All panels event-driven via HZ entry listeners. Zero origin-system load. Replaces mocked TUI v2. See §28. |
| **Test Footer CI Hook — NEW** | `run_logs/test_results_latest.json` + `write_test_results()` API in TUI v3. Test scripts push results; TUI footer displays live. See §28.4 and `TEST_REPORTING.md`. |
| **NG7 Double-Output — Root Cause Confirmed** | Windows NG7 ran two independent tracker cycles (fast w50/w150 + slow w300/w750) sharing the same scan_number counter → two Arrow files + two HZ writes per scan, second file arriving ~3 min late with stale prices. NG8 eliminates this by design. |
---
### What changed since v4.1 (2026-03-30 — PREVIOUS)
| Area | Change |
|---|---|
| **Process Manager: Systemd → Supervisord** | ALL dolphin services migrated exclusively to supervisord. No service is managed by both. `dolphin-supervisord.conf` is the single source of process truth. See §16, §26. |
| **"Random Killer" Root Cause Fixed** | `meta_health_daemon_v2.py` had been running under systemd for 4 days calling `systemctl restart` on supervisord-managed services every 5s. Dual-management race caused random service kills. Stopped + disabled. |
| **MHS v3 — Complete Rewrite** | `meta_health_service_v3.py` — product formula bug fixed (zero-collapse replaced by weighted sum), recovery via supervisorctl not systemctl, `RECOVERY_COOLDOWN_CRITICAL_S=10s` (was 600s), non-blocking daemon thread recovery. See §24.5. |
| **OBF Universe Service — NEW** | `obf_universe_service.py` — 540 USDT perp assets on 3 WebSocket connections, zero REST weight, 60s health snapshots → HZ `obf_universe_latest`. Supervisord `autostart=true`. See §26. |
| **OBF Retention Fix** | `obf_persistence.py``MAX_FILE_AGE_DAYS = 0` (was 7 — was deleting all backtesting data). Data now accumulates indefinitely for backtesting. |
| **Test Suite: MHS** | NEW `prod/tests/test_mhs_v3.py` — 111 tests: unit, live integration, E2E kill/revive, race conditions, 13 Hypothesis property tests. |
| **HZ Schema additions** | `DOLPHIN_FEATURES["obf_universe_latest"]`, `DOLPHIN_META_HEALTH["latest"]`. See §15. |
| **Multi-Speed Architecture** | NEW multi-layer frequency isolation: OBF (0.1s), Scan (5s), ExtF (varied), Health (5s), Daily batch. See §24. |
| **Event-Driven Nautilus** | NEW `nautilus_event_trader.py` — Hz entry listener for <1msscan-to-tradelatency.NotaPrefectflow—long-runningsystemddaemon.See§24.2.|
| **MHS v2** | ENHANCED `meta_health_daemon_v2.py` — Full 5-sensor monitoring (M1-M5), per-subsystem data freshness tracking, automated recovery. See §24.3. |
| **Resource Safety** | NEW systemd resource limits: MemoryMax=2G, CPUQuota=200%, TasksMax=50 per service. Prevents process explosion. |
| **Scan Bridge Hardening** | Deployment concurrency limit=1, work pool concurrency=1, cgroups integration. See §24.1. |
| **Systemd Service Mesh** | NEW services: `dolphin-nautilus-trader.service`, updated `meta_health_daemon.service`. Systemd-managed, not Prefect-managed. |
| **Incident Response** | Post-mortem: 2026-03-24 kernel deadlock from 60+ uncontrolled Prefect processes. Fixed via concurrency controls. |
### What changed since v3 (2026-03-22)
| Area | Change |
|---|---|
| **Clean Architecture** | NEW hexagonal architecture in `prod/clean_arch/` — Ports, Adapters, Core separation. Adapter-agnostic business logic. |
| **Hazelcast DataFeed** | NEW `HazelcastDataFeed` adapter implementing `DataFeedPort` — reads from DolphinNG6 via Hazelcast (single source of truth). |
| **Scan Bridge Service** | NEW `scan_bridge_service.py` — Linux Arrow file watcher that pushes to Hazelcast. Uses file mtime (not scan #) to handle NG6 restarts. **Phase 2: Prefect daemon integration complete** — auto-restart, health monitoring, unified logging. **18 unit tests** in `tests/test_scan_bridge_prefect_daemon.py`.
| **Paper Trading Engine** | NEW `paper_trade.py` — Clean architecture trading CLI with 23 round-trip trades executed in testing. |
| **Market Data** | Live data flowing: 50 assets, BTC @ $71,281.03, velocity divergence signals active. |
### What changed since v2 (2026-03-22)
| Area | Change |
|---|---|
| **Binance Futures** | Switched system focus from Spot to Perpetuals; updated API endpoints (`fapi.binance.com`); added `recvWindow` for signature stability. |
| **Friction Management** | **SP Bypass Logic**: Alpha engines now support disabling internal fees/slippage to allow Nautilus to handle costs natively. Prevents double-counting. |
| **Paper Trading** | NEW `launch_paper_portfolio.py` — uses Sandbox matching with live Binance data; includes realistic Tier 0 friction (0.02/0.05). |
| **Session Logging** | NEW `TradeLoggerActor` — independent CSV/JSON audit trails for every session. |
| Area | Change |
|---|---|
| **DolphinActor** | Refactored to step_bar() API (incremental, not batch); threading.Lock on ACB; _GateSnap stale-state detection; replay vs live mode; bar_idx tracking |
| **0.1s resolution** | Assessed: BLOCKED by 3 hard blockers (see §22) |
| **Capital Sync** | NEW — DolphinActor now syncs initial_capital with Nautilus Portfolio balance on_start. |
| **Verification** | NEW — `TODO_CHECK_SIGNAL_PATHS.md` systematic test spec for local agents. |
| **MC-Forewarner** | Now wired in `DolphinActor.on_start()` — both flows run full gold-performance stack; `_MC_BASE_CFG` + `_MC_MODELS_DIR_DEFAULT` as frozen module constants; empty-parquet early-return bug fixed in `on_bar` replay path |
27. [NG8 Linux Eigenscan Service (v6.0)](#27-ng8-linux-eigenscan-service)
28. [TUI v3 — Live Observability Terminal (v6.0)](#28-tui-v3-live-observability-terminal)
---
## 1. SYSTEM PHILOSOPHY
DOLPHIN-NAUTILUS is a **SHORT-only** (champion configuration) systematic trading engine targeting crypto perpetual futures on Binance.
**Core thesis**: When crypto market correlation matrices show accelerating eigenvalue-velocity divergence (`vel_div < -0.02`), the market is entering an instability regime. Shorting during early instability onset and exiting at fixed take-profit captures the mean-reversion from panic to normalization.
**Design constraints**:
- Zero signal re-implementation in the Nautilus layer. All alpha logic lives in `NDAlphaEngine`.
- 512-bit arithmetic for correlation matrix processing (separate NG3 pipeline; not in hot path of this engine).
- Champion parameters are FROZEN. They were validated via exhaustive VBT backtest on `dolphin_vbt_real.py`.
- The Nautilus actor is a thin wire, not a strategy. It routes parquet data → NDAlphaEngine → HZ result.
**Key invariant v2**: `DolphinActor.on_bar()` receives one synthetic bar per date in paper mode, which triggers `engine.begin_day()` then iterates through all parquet rows via `step_bar()`. In live mode, one real bar → one `step_bar()` call. The `_processed_dates` guard is replaced by date-boundary detection comparing `current_date` to the bar's timestamp date.
---
## 2a. CLEAN ARCHITECTURE LAYER (NEW v4)
### 2a.1 Overview
The Clean Architecture layer provides a **hexagonal** (ports & adapters) implementation for paper trading, ensuring core business logic is independent of infrastructure concerns.
**Dependency Rule**: Dependencies only point inward. Core knows nothing about Hazelcast, Arrow files, or Binance.
**Single Source of Truth**: All data comes from Hazelcast `DOLPHIN_FEATURES.latest_eigen_scan`, written atomically by DolphinNG6.
**File Timestamp vs Scan Number**: The Scan Bridge uses file modification time (mtime) instead of scan numbers because DolphinNG6 resets counters on restarts.
### 2a.3 Components
| Component | File | Purpose |
|-----------|------|---------|
| `DataFeedPort` | `ports/data_feed.py` | Abstract interface for market data |
| `HazelcastDataFeed` | `adapters/hazelcast_feed.py` | Hz implementation of DataFeedPort |
| `TradingEngine` | `core/trading_engine.py` | Pure business logic |
IRP = **Impulse Response Profiling**. Ranks all available assets by historical behavior over the last 50 bars in the regime direction. Selects the asset with the highest ARS (Asset Ranking Score) that passes all filters.
Blended taker/maker fee rates based on historical SP fill statistics. **IMPORTANT**: In production/paper sessions using Nautilus friction, these MUST be disabled via `use_sp_fees=False`.
Also disabled when `use_sp_slippage=False` is passed to the engine. These were used to "re-approximate" fills in low-fidelity simulations. In paper/live trading, the matching engine provides the fill price directly.
The OB layer is wired in via `engine.set_ob_engine(ob_engine)` which propagates to signal_gen, asset_selector, and exit_manager. It is OPTIONAL — the engine degrades gracefully to legacy Monte Carlo when `ob_engine=None`.
self._pending_acb = None # atomic consume under lock
if pending is not None and self.engine is not None:
boost = float(pending.get('boost', 1.0))
beta = float(pending.get('beta', 0.0))
self.engine.update_acb_boost(boost, beta)
```
**v2 vs v1**: v1 relied on GIL for safety (bare dict assignment). v2 uses explicit `threading.Lock` — correct even if GIL is removed in future Python versions. Lock hold time is minimized to a single pointer swap.
### 14.3 _GateSnap — Stale-State Detection
New in v2. Detects when ACB boost, posture, or MC gate changes between the pre-step and post-step snapshot:
- **`actor.log` is read-only** (Rust-backed Cython property). Never try to assign `actor.log = MagicMock()` in tests — use the real Nautilus logger instead.
- **`actor.posture`** is a regular Python attribute (writable in tests).
- **`actor.engine`** is set in `on_start()`. Tests can set directly after `__init__`.
---
## 15. HAZELCAST — FULL IMAP SCHEMA
Hazelcast is the **system memory**. All subsystem state flows through it. Every consumer must treat HZ maps as authoritative real-time sources.
| `DOLPHIN_PNL_BLUE` | `"YYYY-MM-DD"` | JSON daily result `{pnl, capital, trades, boost, beta, mc_status, posture, stale_state?}` | `paper_trade_flow`, `DolphinActor._write_result_to_hz`, `nautilus_prefect_flow` | Analytics | stale_state=True means DO NOT use for live orders |
| `DOLPHIN_PNL_GREEN` | `"YYYY-MM-DD"` | JSON daily result | `paper_trade_flow` (green) | Analytics | GREEN config only |
| `DOLPHIN_STATE_BLUE` | `"latest"` | JSON `{strategy, capital, date, pnl, trades, peak_capital, drawdown, engine_state, updated_at}` | `paper_trade_flow` | `paper_trade_flow` (capital restore) | Full engine_state for position continuity |
shard_idx = sum(ord(c) for c in symbol) % SHARD_COUNT
imap_name = f"DOLPHIN_FEATURES_SHARD_{shard_idx:02d}" # ..._00 through ..._09
```
Routing is **stable** (sum-of-ord, not `hash()`) — deterministic across Python versions and process restarts. 400+ assets distribute evenly across 10 shards.
No static asset list required — adapts automatically as OBF flow adds/removes assets.
### 15.5 CP Subsystem (ACB Processor)
`acb_processor_service.py` uses `HZ CP FencedLock` to prevent simultaneous ACB writes from multiple instances. CP Subsystem must be enabled in `docker-compose.yml`. All writers must use the same CP lock name to get protection.
### 15.6 OBF Circuit Breaker (HZ Push)
After 5 consecutive HZ push failures, OBF flow opens a circuit breaker and switches to file-only mode (`ob_cache/latest_ob_features.json`). Consumers should prefer the JSON file during HZ outages.
---
## 16. PRODUCTION DAEMON TOPOLOGY
> **v5.0 NOTE**: ALL services are managed exclusively by **supervisord**. No service is managed by systemd. The `meta_health_daemon.service`, `dolphin-nautilus-trader.service`, and `dolphin-scan-bridge.service` systemd units are stopped and disabled. Any attempt to re-enable them will create a dual-management race condition ("random killer" bug — see §26.1).
### 20.4 OBF Live Data Gap — KNOWN LIMITATION (2026-03-26)
> **CRITICAL DATA QUALITY CAVEAT**: `nautilus_event_trader.py` (live event trader) is currently wired to `MockOBProvider` with static per-asset imbalance biases (BTC=-0.086, ETH=-0.092, BNB=+0.05, SOL=+0.05). All four OBF functional dimensions compute and produce real outputs — but with frozen, market-unresponsive inputs. The OB cascade regime will always be CALM (no depth drain in mock data).
>
> `HZOBProvider` (`/mnt/dolphinng5_predict/nautilus_dolphin/nautilus_dolphin/nautilus/hz_ob_provider.py`) exists and is format-compatible with `obf_prefect_flow.py`'s HZ output, but `OBFeatureEngine` has no live streaming path — only `preload_date()` (batch/backtest). A `step_live()` method must be added before the switch.
`tests/test_obf_unit.py` — ~120 unit tests covering all hardening items:
- Circuit breaker state machine (CLOSED → OPEN → HALF-OPEN)
- Crossed-book guard triggers on malformed data
- Dark streak threshold detection
- Warmup period gating
- Background thread non-blocking behavior
- Asset discovery via HZ key scan
---
## 21. KNOWN RESEARCH TODOs
| ID | Description | Priority |
|----|-------------|----------|
| TODO-1 | Calibrate `vd_enabled` adverse-turn exits (currently disabled). Requires analysis of trade vel_div distribution at entry vs. subsequent bars. True invalidation threshold likely ~+0.02 sustained for N=3 bars. | MEDIUM |
| TODO-2 | Validate SUBDAY_ACB force-exit threshold (`old_boost >= 1.25 and boost < 1.10`). Currently ARBITRARY — agent-chosen, not backtest-derived. | MEDIUM |
| TODO-3 | MIG8: Binance live adapter (real order execution). OUT OF SCOPE until after 30-day paper trading validation. | LOW |
| TODO-4 | 48-hour chaos test with all daemons running simultaneously. Watch for: KeyError, stale-read anomalies, concurrent HZ writer collisions. | HIGH (before live capital) |
| TODO-5 | Memory profiler with IRP enabled at 400 assets (current 71 MB measurement was without IRP). Projected ~600 MB — verify. | LOW |
| TODO-6 | TF-spread recovery exits (`tf_enabled=False`). Requires sweep of tf_exhaust_ratio and tf_flip_ratio vs. champion backtest. | LOW |
| TODO-7 | GREEN (LONG) posture paper validation. LONG thresholds (long_threshold=0.01, long_extreme=0.04) not yet production-validated. | MEDIUM |
| TODO-8 | ~~ML-MC Forewarner injection into `nautilus_prefect_flow.py`.~~**DONE 2026-03-22** — wired in `DolphinActor.on_start()` for both flows. | CLOSED |
| TODO-9 | Live TradingNode integration (launcher.py exists; Binance adapter config incomplete). Requires 30-day clean paper run first. | LOW |
---
## 22. 0.1S RESOLUTION — READINESS ASSESSMENT
**Assessment date**: 2026-03-22. **Status: BLOCKED — 3 hard blockers.**
The current system processes 5s OHLCV bars. Upgrading to 0.1s tick resolution requires resolving all three blockers below before any code changes.
### 22.1 Blocker 1 — Async HZ Push
**Problem**: The OBF hot loop fires at ~100ms cadence. At 0.1s resolution, the per-bar HZ write latency (currently synchronous in feature compute path, despite fire-and-forget for the push itself) would exceed bar cadence, causing HZ write queue growth and eventual OOM.
**Required**: Full async HZ client (`hazelcast-python-client` async API or aiohazelcast). Currently all HZ operations are synchronous blocking calls. Estimated effort: 2–3 days of refactor + regression testing.
### 22.2 Blocker 2 — `get_depth` Timeout
**Problem**: `get_depth()` in `HZOBProvider` issues a synchronous HZ `IMap.get()` call with a 500ms timeout. At 0.1s resolution, each bar would wait up to 500ms for OB depth data — 5× the bar cadence. This makes 0.1s resolution impossible without an in-process depth cache.
**Required**: Pre-fetched depth cache (e.g., local dict refreshed by a background subscriber), making `get_depth()` a pure in-process read with <1µslatency.Estimatedeffort:1–2days.
### 22.3 Blocker 3 — Lookback Recalibration
**Problem**: All champion parameters that reference "bars" were validated against 5s bars:
-`lookback=100` (100 × 5s = 500s warmup)
-`max_hold_bars=120` (120 × 5s = 600s max hold)
-`dc_lookback_bars=7` (7 × 5s = 35s DC window)
At 0.1s resolution, the same bar counts would mean 10s warmup, 12s max hold, 0.7s DC window — **completely invalidating champion params**. All params must be re-validated from scratch via VBT backtest at 0.1s resolution.
**Required**: Full backtest sweep at 0.1s. Estimated effort: 1–2 weeks of compute + validation time. This is a research milestone, not an engineering task.
### 22.4 Assessment Summary
| Blocker | Effort | Dependency |
|---------|--------|------------|
| Async HZ push | 2–3 days engineering | None — can start now |
| `get_depth` cache | 1–2 days engineering | None — can start now |
| Lookback recalibration | 1–2 weeks research | Requires blockers 1+2 resolved first |
**Recommendation**: Do NOT attempt 0.1s resolution until after 30-day paper trading validation at 5s. The engineering blockers can be prototyped in parallel, but champion params cannot be certified until post-paper-run stability is confirmed.
## 23. SIGNAL PATH VERIFICATION SPECIFICATION
Testing the asynchronous, multi-scale signal path requires systematic validation of the data bridge and cross-layer trigger logic.
### 23.1 Verification Flow
A local agent (Prefect or standalone) should verify:
1.**Micro Ingestion**: 100ms OB features sharded across 10 HZ maps.
2.**Regime Bridge**: NG5 Arrow scan detection by `scan_hz_bridge.py` and push to `latest_eigen_scan`.
3.**Strategy Reactivity**: `DolphinActor.on_bar` (5s) pulling HZ data and verifying `scan_number` idempotency.
4.**Macro Safety**: Survival Stack Rm-computation pushing `APEX/STALKER/HIBERNATE` posture to `DOLPHIN_SAFETY`.
### 23.2 Reference Document
Full test instructions, triggers, and expected values are defined in:
`TODO_CHECK_SIGNAL_PATHS.md` (Project Root)
---
*End of DOLPHIN-NAUTILUS System Bible v3.0 — 2026-03-23*
*Champion: SHORT only (APEX posture, blue configuration)*
*Automation: Prefect-supervised paper trading active.*
*Status: Capital Sync enabled; Friction SP-bypass active; TradeLogger running.*
*Do NOT deploy real capital until 30-day paper run is clean.*
The DOLPHIN system has been re-architected from a **single-speed batch-oriented Prefect deployment** to a **multi-speed, event-driven, multi-worker architecture** with proper resource isolation and self-healing capabilities.
**Problem Solved**: 2026-03-24 system outage caused by uncontrolled Prefect process explosion (60+ `prefect.engine` zombies → resource exhaustion → kernel deadlock).
**Current Status**: Running directly (PID 158929) due to Prefect worker scheduling issues.
### 24.5 Meta Health Service v3 (MHS) — REWRITTEN v5.0
> **MHS v2 is retired.** `meta_health_daemon_v2.py` was calling `systemctl restart` on supervisord-managed processes — this was the "random killer" bug. v3 is the canonical implementation.
### 26.1 The "Random Killer" Bug — Root Cause & Fix
**Incident**: Services were being unexpectedly killed and restarted at seemingly random intervals. The system appeared healthy according to supervisord but processes would die without obvious cause.
**Root cause** (diagnosed 2026-03-30):
1.`meta_health_daemon_v2.py` had been running under `meta_health_daemon.service` (systemd) for 4+ days.
2. MHS v2's process patterns (`exf_prefect_final`, `esof_prefect_flow`) did not match any running process → M1=0 → `rm_meta = M1*M2*M3*M4*M5 = 0` always → status="DEAD".
3. MHS v2 recovery action: `systemctl restart <service>` — called every 5s.
4. But the services were supervisord-managed, not systemd-managed. `systemctl restart` on a supervisord process:
- Sends SIGTERM to the process (it dies)
- Supervisord detects the death and autostarts a new instance
- Creates brief duplicate processes, interleaved with MHS v2's next kill cycle
5. Additionally, `dolphin-nautilus-trader.service` (systemd) AND supervisord were both managing `nautilus_event_trader.py` simultaneously — two PIDs running at once.
**Permanent guard**: `test_mhs_v3.py::TestKillAndRevive::test_no_systemd_units_active_for_managed_services` asserts no conflicting systemd units are active.
### 26.2 OBF Universe Service
**Purpose**: Lightweight L2 order book health monitor for ALL 540 active USDT perpetuals on Binance Futures.
**Why**: Asset Picker needs OB health scores for the full universe (540 assets) to make informed selection decisions, not just the 400 assets covered by the existing OBF shard store.
**Design**: Push streams (zero REST weight), no polling.
```
wss://fstream.binance.com/ws
Connection 1: 200 symbols ×@depth5@500ms
Connection 2: 200 symbols ×@depth5@500ms
Connection 3: 140 symbols ×@depth5@500ms
(total: 540, Binance limit: 300/conn)
```
**Computed metrics per asset** (every 60s snapshot):
| Field | Description |
|---|---|
| `spread_bps` | (ask - bid) / mid × 10000 |
| `depth_1pct_usd` | Total USD volume within 1% of mid on both sides |
**Bug (v4.1)**: `MAX_FILE_AGE_DAYS = 7` — every daily cleanup run deleted all OBF Parquet data older than 7 days, destroying the entire backtesting dataset.
**Fix (v5.0)**:
```python
MAX_FILE_AGE_DAYS = 0 # 0 = disabled — never prune, accumulate for backtesting
def _cleanup_old_partitions(self):
"""0 = disabled."""
if not MAX_FILE_AGE_DAYS or not self.base_dir.exists():
return
...
```
Data now accumulates indefinitely in `/mnt/ng6_data/ob_features/` (existing OBF) and `/mnt/ng6_data/ob_universe/` (new universe service).
---
---
## 27. NG8 LINUX EIGENSCAN SERVICE
**File**: `- Dolphin NG8/ng8_scanner.py`
**Status**: Built, smoke-tested. Replaces Windows NG7 eigenscan.
Windows NG7 maintained two independent tracker cycles:
- **Fast cycle** (w50, w150): completed ~11s after scan start → wrote Arrow file 1, HZ write 1
- **Slow cycle** (w300, w750): completed ~3 min later with **stale BTC price** → wrote Arrow file 2, HZ write 2
Both cycles shared the same `scan_number` counter. Result: two Arrow files per logical scan, the second containing stale prices from 3 minutes earlier. The scan bridge de-duplicated by file mtime (file 1 is always the useful one).
### 27.2 NG8 Fix: Single `enhance()` Pass
`DolphinCorrelationEnhancerArb512.enhance()` processes all four windows (50, 150, 300, 750) in a single sequential loop. NG8 calls this once per scan cycle:
```python
result = self.engine.enhance(price_data, PRIORITY_SYMBOLS, now)
# result.multi_window_results has all four windows populated
# Exactly one Arrow write + one HZ write follows
```
`use_arrow=False` is passed to the engine constructor so the engine does **not** perform its own internal Arrow write — `ng8_scanner.py` owns that write exclusively.
### 27.3 Schema Contract (Doctrinal NG5)
Arrow IPC schema is defined in `ng7_arrow_writer_original.py` → `SCAN_SCHEMA` (27 fields, `SCHEMA_VERSION="5.0.0"`). `arrow_writer.py` is a thin re-export shim:
**Critical**: pass `get_arrow_scans_path().parent` (= `/mnt/dolphinng6_data`) — NOT `get_arrow_scans_path()` — or the writer creates `arrow_scans/arrow_scans/` double-nesting.
### 27.5 Hazelcast Output
Map: `DOLPHIN_FEATURES` → key `latest_eigen_scan`
**NG8 flat payload** (written by NG8, differs from NG7 nested payload):
```python
{
"scan_number": int,
"timestamp": "ISO-8601",
"bridge_ts": float, # Unix epoch at HZ write
"vel_div": float,
"w50_velocity": float,
"w150_velocity": float,
"w300_velocity": float,
"w750_velocity": float,
"eigenvalue_gradients": {...},
"multi_window_results": {...}, # full per-window stats
}
```
TUI v3 `_eigen_from_scan()` normalises both NG7 nested and NG8 flat formats transparently.
### 27.6 Scan Number Continuity
On startup, `_load_last_scan_number(arrow_scans_dir)` scans all `scan_NNNNNN_*.arrow` filenames for the highest N and resumes from N+1. Prevents counter reset gaps after service restart.
### 27.7 Symbol List
50 symbols matching doctrinal NG3/NG5/NG7 `PRIORITY_SYMBOLS`. Do NOT change this list without a full schema migration — historical correlation matrices are computed on this exact universe.
Set `autostart=true` only after confirming Windows NG7 is shut down — dual-write to the same HZ key is safe (last-write-wins) but creates confusing Arrow audit trails.
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## 28. TUI v3 — LIVE OBSERVABILITY TERMINAL
**File**: `Observability/TUI/dolphin_tui_v3.py`
**Run**: `source /home/dolphin/siloqy_env/bin/activate && cd /mnt/dolphinng5_predict/Observability/TUI && python3 dolphin_tui_v3.py`
`IMap.add_entry_listener(include_value=True, updated=fn, added=fn)` fires callbacks from the HZ internal thread pool on any map change. No polling of origin systems.
Prefect is the **only** polled source — 60s interval via `run_worker(prefect_poll_loop())`.
The footer reads `run_logs/test_results_latest.json` (relative to `dolphin_tui_v3.py`'s working directory, i.e., `/mnt/dolphinng5_predict/run_logs/test_results_latest.json`).
`write_test_results()` atomically writes `_run_at` (current UTC ISO timestamp) + the provided category dict. The TUI footer auto-refreshes on next mount or `t` keypress.
Full integration documentation: `prod/docs/TEST_REPORTING.md`.
### 28.5 NG7 / NG8 Dual Format Normalisation
`_eigen_from_scan(scan)` handles both live HZ formats:
MC-Forewarner writes to `DOLPHIN_FEATURES` key `mc_forewarner_latest`. The TUI entry listener fires on each write and populates the full MC footer panel: `catastrophic_prob` Digits + ProgressBar, `envelope_score` bar, prob sparkline history, `source` label (`REAL_MODEL` / `FALLBACK_NO_DATA` / `FALLBACK_ERROR`).
If the TUI starts between 4-hour runs and HZ has never been written to (e.g., fresh HZ instance), the footer shows `"awaiting HZ data (runs every 4h via Prefect)"` in yellow. This is a cold-start state only — once the first Prefect run completes the key persists in HZ indefinitely (no TTL).
**Thresholds**: GREEN `prob < 0.10` · ORANGE `0.10–0.30` · RED `≥ 0.30`
**Models path**: `nautilus_dolphin/mc_results/models/*.pkl` — if absent, falls back to `FALLBACK_NO_DATA` (ORANGE, prob=0.20, env=0.80) which is a safe conservative posture, never random.
### 28.7 Pending: DOLPHIN_PNL_BLUE
The Trader panel contains placeholder text `"read DOLPHIN_PNL_BLUE (not yet wired)"`. Open positions and session PnL data should be sourced from this map when Nautilus live trading is active.
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*End of DOLPHIN-NAUTILUS System Bible v7.0 — 2026-06-08*
*Champion: SHORT only (APEX posture, blue configuration)*
*Process manager: Supervisord exclusively (systemd units retired).*
