feat: Specialist Desks — per asset-class fundamental configs + report catalogue
- 7 pre-seeded desks (Forex, Metals, Agri, Energy, Indices, Crypto, Bonds) each with default fundamental drivers, macro regime sensitivities and price delta thresholds - Global report catalogue (specialist_reports) fully manual — add any report including non-calendar ones (e.g. Cocoa Grinding Report, ICCO) - Many-to-many report ↔ desk linking (report_desk_links table) - 12 default reports pre-seeded (COT, EIA, WASDE, FOMC, ECB, CPI, NFP…) - AI scorer injects SPECIALIST DESK context block for asset classes present in each scoring batch (upcoming reports, key drivers, regime sensitivity) - /specialist-desks page: desk sidebar + fundamentals editor + macro sensitivity tag editor + reports tab + global reports catalogue + modal to create/edit any report with desk assignment Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
OpenSquared
@@ -2,6 +2,7 @@ from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from routers import market_data, geopolitical, options, backtest, ai, portfolio, config, patterns, journal, cycle as cycle_router, profiles as profiles_router, reasoning as reasoning_router, knowledge as knowledge_router, options_vol as options_vol_router, analytics as analytics_router, risk as risk_router
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from routers import pattern_lab as pattern_lab_router
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from routers import specialist_desks as specialist_desks_router
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from routers import logs as logs_router
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from routers import var as var_router
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from routers import reports as reports_router
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@@ -119,6 +120,7 @@ app.include_router(var_router.router)
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app.include_router(reports_router.router)
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app.include_router(institutional_router.router)
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app.include_router(pattern_lab_router.router)
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app.include_router(specialist_desks_router.router)
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@app.get("/")
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144
backend/routers/specialist_desks.py
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144
backend/routers/specialist_desks.py
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@@ -0,0 +1,144 @@
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"""
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Specialist Desks — per asset-class fundamental configs + report catalogue.
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Prefix: /api/specialist-desks
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"""
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import uuid
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from typing import Optional, List
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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router = APIRouter(prefix="/api/specialist-desks", tags=["specialist-desks"])
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# ── Pydantic models ────────────────────────────────────────────────────────────
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class MacroSensitivity(BaseModel):
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regime: str
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effect: str
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class PriceDeltaThresholds(BaseModel):
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significant_day: float = 1.0
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extreme_day: float = 3.0
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significant_week: float = 2.0
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extreme_week: float = 5.0
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class DeskConfigUpdate(BaseModel):
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display_name: str
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icon: str = ""
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fundamentals: str = ""
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macro_sensitivity: List[MacroSensitivity] = []
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price_delta_thresholds: PriceDeltaThresholds = PriceDeltaThresholds()
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notes: str = ""
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class ReportUpsert(BaseModel):
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name: str
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source: str = ""
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cadence: str = "monthly"
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next_date: Optional[str] = None
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last_date: Optional[str] = None
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importance: int = 2
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notes: str = ""
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url: str = ""
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desks: List[str] = []
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# ── Configs ────────────────────────────────────────────────────────────────────
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@router.get("/configs")
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def list_configs():
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from services.database import get_all_asset_class_configs
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return get_all_asset_class_configs()
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@router.get("/configs/{asset_class}")
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def get_config(asset_class: str):
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from services.database import get_asset_class_config, get_desk_reports
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cfg = get_asset_class_config(asset_class)
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if not cfg:
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raise HTTPException(404, f"Desk '{asset_class}' not found")
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cfg["reports"] = get_desk_reports(asset_class)
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return cfg
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@router.put("/configs/{asset_class}")
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def update_config(asset_class: str, body: DeskConfigUpdate):
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from services.database import upsert_asset_class_config
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upsert_asset_class_config(
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asset_class=asset_class,
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display_name=body.display_name,
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icon=body.icon,
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fundamentals=body.fundamentals,
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macro_sensitivity=[s.dict() for s in body.macro_sensitivity],
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price_delta_thresholds=body.price_delta_thresholds.dict(),
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notes=body.notes,
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)
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return {"saved": asset_class}
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# ── Reports ────────────────────────────────────────────────────────────────────
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@router.get("/reports")
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def list_reports():
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from services.database import get_all_specialist_reports
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return get_all_specialist_reports()
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@router.post("/reports")
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def create_report(body: ReportUpsert):
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from services.database import upsert_specialist_report, link_report_desk
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report_id = "RPT_" + uuid.uuid4().hex[:8].upper()
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upsert_specialist_report(
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report_id=report_id,
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name=body.name, source=body.source, cadence=body.cadence,
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next_date=body.next_date, last_date=body.last_date,
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importance=body.importance, notes=body.notes, url=body.url,
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)
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for ac in body.desks:
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link_report_desk(report_id, ac)
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return {"id": report_id}
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@router.put("/reports/{report_id}")
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def update_report(report_id: str, body: ReportUpsert):
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from services.database import upsert_specialist_report, link_report_desk, unlink_report_desk, get_all_specialist_reports
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# Check exists
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all_reports = get_all_specialist_reports()
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if not any(r["id"] == report_id for r in all_reports):
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raise HTTPException(404, "Report not found")
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upsert_specialist_report(
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report_id=report_id,
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name=body.name, source=body.source, cadence=body.cadence,
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next_date=body.next_date, last_date=body.last_date,
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importance=body.importance, notes=body.notes, url=body.url,
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)
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# Sync desk links: remove all, re-add
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existing = next(r for r in all_reports if r["id"] == report_id)
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for old_ac in existing.get("desks", []):
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unlink_report_desk(report_id, old_ac)
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for new_ac in body.desks:
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link_report_desk(report_id, new_ac)
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return {"saved": report_id}
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@router.delete("/reports/{report_id}")
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def delete_report(report_id: str):
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from services.database import delete_specialist_report
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delete_specialist_report(report_id)
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return {"deleted": report_id}
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@router.post("/reports/{report_id}/link/{asset_class}")
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def link_to_desk(report_id: str, asset_class: str):
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from services.database import link_report_desk
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link_report_desk(report_id, asset_class)
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return {"linked": report_id, "desk": asset_class}
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@router.delete("/reports/{report_id}/link/{asset_class}")
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def unlink_from_desk(report_id: str, asset_class: str):
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from services.database import unlink_report_desk
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unlink_report_desk(report_id, asset_class)
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return {"unlinked": report_id, "desk": asset_class}
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@@ -376,6 +376,54 @@ SCORE DISTRIBUTION RULE (MANDATORY):
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- A pattern with 3+ relevant news AND favorable macro can reach 70-85/100"""
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def _build_specialist_context_block(asset_classes: set) -> str:
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"""Build a SPECIALIST DESK CONTEXT block for the given asset classes."""
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try:
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from services.database import get_asset_class_config, get_desk_reports
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from datetime import datetime as _dt
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blocks = []
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for ac in sorted(asset_classes):
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cfg = get_asset_class_config(ac)
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if not cfg:
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continue
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reports = get_desk_reports(ac)
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lines = [f"\n## SPECIALIST DESK — {cfg['display_name'].upper()} {cfg.get('icon','')}"]
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if cfg.get("fundamentals"):
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lines.append(f"Key drivers: {cfg['fundamentals'][:300]}")
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# Macro sensitivity
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sensitivities = cfg.get("macro_sensitivity") or []
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if sensitivities:
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sens_str = " | ".join(
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f"{s.get('regime','?')} → {s.get('effect','?')}"
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for s in sensitivities[:4]
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)
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lines.append(f"Regime sensitivity: {sens_str}")
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# Price thresholds
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thresh = cfg.get("price_delta_thresholds") or {}
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if thresh:
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lines.append(
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f"Price thresholds: significant_week={thresh.get('significant_week','?')}% "
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f"extreme_week={thresh.get('extreme_week','?')}%"
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)
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# Upcoming reports
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today = _dt.utcnow().strftime("%Y-%m-%d")
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upcoming = sorted(
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[r for r in reports if r.get("next_date") and r["next_date"] >= today],
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key=lambda r: r["next_date"]
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)[:5]
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if upcoming:
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lines.append("Upcoming reports:")
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for r in upcoming:
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lines.append(
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f" • {r['name']} ({r['source']}) — {r['next_date']} [{r['cadence']}]"
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+ (f" ⭐×{r['importance']}" if r.get("importance", 1) >= 3 else "")
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)
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blocks.append("\n".join(lines))
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return "\n".join(blocks) + "\n" if blocks else ""
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except Exception:
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return ""
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def score_patterns_with_context(
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patterns: List[Dict],
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recent_news: List[Dict],
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@@ -783,12 +831,18 @@ Lessons: {' | '.join(str(l)[:80] for l in lessons[:3])}
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"""
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# Build specialist-desk blocks for asset classes present in this pattern set
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_all_pattern_asset_classes = {
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p.get("asset_class", "") for p in patterns if p.get("asset_class")
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}
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specialist_block = _build_specialist_context_block(_all_pattern_asset_classes)
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# Build the per-batch prompt template (static parts)
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prompt_header = f"""GLOBAL CONTEXT:
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- Geopolitical risk score: {geo_score.get('score', 50)}/100 ({geo_score.get('level', 'medium')})
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- Top risks: {geo_score.get('top_risks', [])}
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{macro_section}{lessons_header}{iv_context}
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{risk_context}
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{risk_context}{specialist_block}
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SCORING TEMPLATE:
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{scoring_template}
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@@ -641,6 +641,101 @@ def init_db():
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except Exception:
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pass
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# ── Specialist Desks ───────────────────────────────────────────────────────
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c.execute("""CREATE TABLE IF NOT EXISTS specialist_reports (
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id TEXT PRIMARY KEY,
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name TEXT NOT NULL,
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source TEXT NOT NULL DEFAULT '',
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cadence TEXT NOT NULL DEFAULT 'monthly',
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next_date TEXT,
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last_date TEXT,
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importance INTEGER NOT NULL DEFAULT 2,
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notes TEXT NOT NULL DEFAULT '',
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url TEXT NOT NULL DEFAULT '',
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created_at TEXT NOT NULL DEFAULT (datetime('now')),
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updated_at TEXT NOT NULL DEFAULT (datetime('now'))
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)""")
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c.execute("""CREATE TABLE IF NOT EXISTS asset_class_configs (
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asset_class TEXT PRIMARY KEY,
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display_name TEXT NOT NULL,
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icon TEXT NOT NULL DEFAULT '',
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fundamentals TEXT NOT NULL DEFAULT '',
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macro_sensitivity TEXT NOT NULL DEFAULT '[]',
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price_delta_thresholds TEXT NOT NULL DEFAULT '{}',
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notes TEXT NOT NULL DEFAULT '',
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updated_at TEXT NOT NULL DEFAULT (datetime('now'))
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)""")
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c.execute("""CREATE TABLE IF NOT EXISTS report_desk_links (
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report_id TEXT NOT NULL,
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asset_class TEXT NOT NULL,
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PRIMARY KEY (report_id, asset_class)
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)""")
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# Seed desk defaults (idempotent)
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_desk_count = c.execute("SELECT COUNT(*) FROM asset_class_configs").fetchone()[0]
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if _desk_count == 0:
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_desk_defaults = [
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("forex", "Forex", "💱",
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"Rate differentials (Fed vs ECB/BOJ/BOE), current account balances, political risk premium, USD index trend, carry trade positioning, intervention risk.",
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'[{"regime":"dollar_strength","effect":"bearish EUR/JPY, bullish DXY pairs"},{"regime":"risk_off","effect":"bullish JPY/CHF, bearish EM FX"},{"regime":"dovish_fed","effect":"bearish USD, bullish EM FX"},{"regime":"rate_divergence_us_up","effect":"bullish USD across board"}]',
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'{"significant_day":0.5,"extreme_day":1.5,"significant_week":1.0,"extreme_week":2.5}'),
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("metals", "Metals", "🥇",
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"Real interest rates (TIPS), DXY trend, China PMI/demand, ETF flows (GLD/SLV), COT net positioning, inflation breakevens, central bank gold buying, industrial demand (copper/silver).",
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'[{"regime":"risk_off","effect":"bullish gold, silver underperforms"},{"regime":"real_rates_rising","effect":"bearish gold/silver"},{"regime":"dollar_weakness","effect":"bullish all metals"},{"regime":"china_stimulus","effect":"bullish copper/industrial metals"}]',
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'{"significant_day":1.0,"extreme_day":3.0,"significant_week":2.0,"extreme_week":5.0}'),
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("agri", "Agri & Softs", "🌾",
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"WASDE supply/demand balance, weather events (La Niña/El Niño), crop calendar (planting/harvest), freight rates, USD/BRL (soy), USD/ARS, biofuel mandates (corn/soy), export inspections.",
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'[{"regime":"la_nina","effect":"bullish corn/wheat (US drought), bearish soy (S. America)"},{"regime":"dollar_strength","effect":"bearish USD-denominated agri exports"},{"regime":"energy_shock","effect":"bullish corn (ethanol), bullish soy (biodiesel)"},{"regime":"china_demand_drop","effect":"bearish soy/corn"}]',
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'{"significant_day":1.5,"extreme_day":4.0,"significant_week":3.0,"extreme_week":8.0}'),
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("energy", "Energy", "⚡",
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"OPEC+ production decisions, EIA weekly inventory build/draw, US rig count/shale production, geopolitical premium (Middle East/Russia), demand/growth cycle, refinery margins, seasonal demand (summer driving/winter heating).",
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'[{"regime":"geopolitical_escalation","effect":"bullish crude, nat gas spike risk"},{"regime":"recession_fear","effect":"bearish crude (demand destruction)"},{"regime":"opec_cut","effect":"bullish crude"},{"regime":"dollar_strength","effect":"mildly bearish crude"}]',
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'{"significant_day":1.5,"extreme_day":4.0,"significant_week":3.0,"extreme_week":8.0}'),
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("indices", "Equity Indices", "📈",
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"Earnings growth trajectory, Fed policy path (PE multiples), credit spreads (HYG), buyback activity, market breadth/concentration, Buffett indicator, VIX regime, sector rotation (growth vs value).",
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'[{"regime":"fed_pivot_dovish","effect":"bullish equities, PE expansion"},{"regime":"credit_stress","effect":"bearish equities, flight to safety"},{"regime":"earnings_miss_wave","effect":"bearish indices, vol spike"},{"regime":"risk_on","effect":"bullish equities, small caps outperform"}]',
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'{"significant_day":1.0,"extreme_day":3.0,"significant_week":2.0,"extreme_week":5.0}'),
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("crypto", "Crypto", "₿",
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"BTC halving cycle position, on-chain net flows (exchange inflows/outflows), stablecoin supply growth, regulatory risk (SEC/CFTC), BTC dominance, macro correlation (SPY), ETF flows.",
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'[{"regime":"risk_off","effect":"bearish BTC/ETH, correlation with equities rises"},{"regime":"dollar_weakness_qe","effect":"bullish BTC as inflation hedge"},{"regime":"regulatory_crackdown","effect":"bearish all crypto"},{"regime":"btc_halving_post","effect":"bullish BTC 6-12m horizon"}]',
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'{"significant_day":3.0,"extreme_day":10.0,"significant_week":8.0,"extreme_week":20.0}'),
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("bonds", "Bonds & Rates", "📉",
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"Fed funds path (dots plot), real rates (TIPS), term premium, fiscal deficit trajectory, inflation breakevens, foreign central bank demand (Japan/China UST), credit spreads, duration risk.",
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'[{"regime":"hawkish_fed","effect":"bearish long duration (TLT), bearish EM bonds"},{"regime":"recession_confirmed","effect":"bullish long bonds (flight to quality)"},{"regime":"fiscal_expansion","effect":"bearish bonds (supply pressure)"},{"regime":"disinflation","effect":"bullish bonds, real rate normalization"}]',
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'{"significant_day":0.5,"extreme_day":1.5,"significant_week":1.0,"extreme_week":3.0}'),
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]
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for _ac, _dn, _ic, _fund, _macro, _thresh in _desk_defaults:
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c.execute("""INSERT OR IGNORE INTO asset_class_configs
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(asset_class, display_name, icon, fundamentals, macro_sensitivity, price_delta_thresholds)
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VALUES (?,?,?,?,?,?)""", (_ac, _dn, _ic, _fund, _macro, _thresh))
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# Seed default reports (idempotent)
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_rpt_count = c.execute("SELECT COUNT(*) FROM specialist_reports").fetchone()[0]
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if _rpt_count == 0:
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import uuid as _uuid
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_rpt_defaults = [
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("RPT_COT", "COT — Commitment of Traders", "CFTC", "weekly", 3, ["metals","forex","agri","energy"]),
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("RPT_EIA", "EIA Petroleum Status Report", "EIA", "weekly", 3, ["energy"]),
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("RPT_WASDE", "WASDE — World Ag Supply & Demand", "USDA", "monthly", 3, ["agri"]),
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("RPT_FOMC", "FOMC Statement & Projections", "Federal Reserve","6-weekly", 3, ["forex","indices","bonds"]),
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("RPT_ECB", "ECB Monetary Policy Decision", "ECB", "6-weekly", 3, ["forex","bonds"]),
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("RPT_CPI", "US CPI (Consumer Price Index)", "BLS", "monthly", 3, ["forex","indices","bonds","metals"]),
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("RPT_NFP", "US Non-Farm Payrolls", "BLS", "monthly", 3, ["forex","indices","bonds"]),
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("RPT_CN_PMI", "China PMI (NBS Manufacturing)", "NBS China", "monthly", 2, ["metals","agri","energy","indices"]),
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("RPT_BAKER", "Baker Hughes Rig Count", "Baker Hughes", "weekly", 2, ["energy"]),
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("RPT_EXPORT", "USDA Weekly Export Inspections", "USDA", "weekly", 2, ["agri"]),
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("RPT_BOJ", "BOJ Monetary Policy Decision", "Bank of Japan", "irregular", 2, ["forex","bonds"]),
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("RPT_VIX", "VIX Futures Monthly Settlement", "CBOE", "monthly", 2, ["indices"]),
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]
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for _rid, _rname, _rsrc, _rcad, _rimp, _racs in _rpt_defaults:
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c.execute("""INSERT OR IGNORE INTO specialist_reports (id, name, source, cadence, importance)
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VALUES (?,?,?,?,?)""", (_rid, _rname, _rsrc, _rcad, _rimp))
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for _rac in _racs:
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c.execute("INSERT OR IGNORE INTO report_desk_links (report_id, asset_class) VALUES (?,?)",
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(_rid, _rac))
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try:
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c.execute("CREATE INDEX IF NOT EXISTS idx_kb_category ON knowledge_base(category, status)")
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c.execute("CREATE INDEX IF NOT EXISTS idx_rs_version ON reasoning_state(version DESC)")
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@@ -3918,3 +4013,170 @@ def get_economic_events_for_calendar(days_back: int = 30, days_forward: int = 14
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return result
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finally:
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conn.close()
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# ── Specialist Desks ──────────────────────────────────────────────────────────
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def get_all_specialist_reports() -> List[Dict[str, Any]]:
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conn = get_conn()
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try:
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rows = conn.execute(
|
||||
"SELECT * FROM specialist_reports ORDER BY importance DESC, name ASC"
|
||||
).fetchall()
|
||||
result = []
|
||||
for r in rows:
|
||||
d = dict(r)
|
||||
d["desks"] = [
|
||||
lnk["asset_class"] for lnk in
|
||||
conn.execute(
|
||||
"SELECT asset_class FROM report_desk_links WHERE report_id=?", (d["id"],)
|
||||
).fetchall()
|
||||
]
|
||||
result.append(d)
|
||||
return result
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def upsert_specialist_report(
|
||||
report_id: str, name: str, source: str, cadence: str,
|
||||
next_date: Optional[str], last_date: Optional[str],
|
||||
importance: int, notes: str, url: str,
|
||||
) -> str:
|
||||
conn = get_conn()
|
||||
try:
|
||||
conn.execute("""INSERT INTO specialist_reports
|
||||
(id, name, source, cadence, next_date, last_date, importance, notes, url, updated_at)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,datetime('now'))
|
||||
ON CONFLICT(id) DO UPDATE SET
|
||||
name=excluded.name, source=excluded.source, cadence=excluded.cadence,
|
||||
next_date=excluded.next_date, last_date=excluded.last_date,
|
||||
importance=excluded.importance, notes=excluded.notes, url=excluded.url,
|
||||
updated_at=datetime('now')""",
|
||||
(report_id, name, source, cadence, next_date or None, last_date or None,
|
||||
importance, notes, url))
|
||||
conn.commit()
|
||||
return report_id
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def delete_specialist_report(report_id: str) -> bool:
|
||||
conn = get_conn()
|
||||
try:
|
||||
conn.execute("DELETE FROM report_desk_links WHERE report_id=?", (report_id,))
|
||||
conn.execute("DELETE FROM specialist_reports WHERE id=?", (report_id,))
|
||||
conn.commit()
|
||||
return True
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def link_report_desk(report_id: str, asset_class: str) -> bool:
|
||||
conn = get_conn()
|
||||
try:
|
||||
conn.execute(
|
||||
"INSERT OR IGNORE INTO report_desk_links (report_id, asset_class) VALUES (?,?)",
|
||||
(report_id, asset_class)
|
||||
)
|
||||
conn.commit()
|
||||
return True
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def unlink_report_desk(report_id: str, asset_class: str) -> bool:
|
||||
conn = get_conn()
|
||||
try:
|
||||
conn.execute(
|
||||
"DELETE FROM report_desk_links WHERE report_id=? AND asset_class=?",
|
||||
(report_id, asset_class)
|
||||
)
|
||||
conn.commit()
|
||||
return True
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def get_desk_reports(asset_class: str) -> List[Dict[str, Any]]:
|
||||
conn = get_conn()
|
||||
try:
|
||||
rows = conn.execute("""
|
||||
SELECT sr.* FROM specialist_reports sr
|
||||
JOIN report_desk_links rdl ON rdl.report_id = sr.id
|
||||
WHERE rdl.asset_class = ?
|
||||
ORDER BY sr.importance DESC, sr.name ASC""", (asset_class,)).fetchall()
|
||||
return [dict(r) for r in rows]
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def get_all_asset_class_configs() -> List[Dict[str, Any]]:
|
||||
conn = get_conn()
|
||||
try:
|
||||
rows = conn.execute(
|
||||
"SELECT * FROM asset_class_configs ORDER BY asset_class ASC"
|
||||
).fetchall()
|
||||
result = []
|
||||
for r in rows:
|
||||
d = dict(r)
|
||||
try:
|
||||
d["macro_sensitivity"] = json.loads(d.get("macro_sensitivity") or "[]")
|
||||
except Exception:
|
||||
d["macro_sensitivity"] = []
|
||||
try:
|
||||
d["price_delta_thresholds"] = json.loads(d.get("price_delta_thresholds") or "{}")
|
||||
except Exception:
|
||||
d["price_delta_thresholds"] = {}
|
||||
d["reports"] = get_desk_reports(d["asset_class"])
|
||||
result.append(d)
|
||||
return result
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def get_asset_class_config(asset_class: str) -> Optional[Dict[str, Any]]:
|
||||
conn = get_conn()
|
||||
try:
|
||||
row = conn.execute(
|
||||
"SELECT * FROM asset_class_configs WHERE asset_class=?", (asset_class,)
|
||||
).fetchone()
|
||||
if not row:
|
||||
return None
|
||||
d = dict(row)
|
||||
try:
|
||||
d["macro_sensitivity"] = json.loads(d.get("macro_sensitivity") or "[]")
|
||||
except Exception:
|
||||
d["macro_sensitivity"] = []
|
||||
try:
|
||||
d["price_delta_thresholds"] = json.loads(d.get("price_delta_thresholds") or "{}")
|
||||
except Exception:
|
||||
d["price_delta_thresholds"] = {}
|
||||
return d
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def upsert_asset_class_config(
|
||||
asset_class: str, display_name: str, icon: str,
|
||||
fundamentals: str, macro_sensitivity: list,
|
||||
price_delta_thresholds: dict, notes: str,
|
||||
) -> bool:
|
||||
conn = get_conn()
|
||||
try:
|
||||
conn.execute("""INSERT INTO asset_class_configs
|
||||
(asset_class, display_name, icon, fundamentals, macro_sensitivity,
|
||||
price_delta_thresholds, notes, updated_at)
|
||||
VALUES (?,?,?,?,?,?,?,datetime('now'))
|
||||
ON CONFLICT(asset_class) DO UPDATE SET
|
||||
display_name=excluded.display_name, icon=excluded.icon,
|
||||
fundamentals=excluded.fundamentals,
|
||||
macro_sensitivity=excluded.macro_sensitivity,
|
||||
price_delta_thresholds=excluded.price_delta_thresholds,
|
||||
notes=excluded.notes, updated_at=datetime('now')""",
|
||||
(asset_class, display_name, icon, fundamentals,
|
||||
json.dumps(macro_sensitivity), json.dumps(price_delta_thresholds), notes))
|
||||
conn.commit()
|
||||
return True
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
Reference in New Issue
Block a user