Aissa
5d60d33db1
Volledige Foodlinkk Command Center uitbreiding met social automatisering, reclamefolder filters, Proxmox monitoring en documentatie.
90 lines
3.6 KiB
Python
90 lines
3.6 KiB
Python
"""Fetch retail stock quotes — delegates to tools-api when available."""
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from __future__ import annotations
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import json
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import os
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from typing import Any
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from urllib.request import Request, urlopen
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USER_AGENT = "Foodlinkk-MarketIntel/1.0"
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TOOLS = os.getenv("TOOLS_API_URL", "http://tools-api:8700").rstrip("/")
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RETAIL_STOCKS = [
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{"symbol": "AD.AS", "name": "Ahold Delhaize", "chain": "Albert Heijn / Gall", "market": "Euronext"},
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{"symbol": "TSCO.L", "name": "Tesco", "chain": "Tesco UK", "market": "LSE"},
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{"symbol": "CAR.PA", "name": "Carrefour", "chain": "Carrefour EU", "market": "Euronext Paris"},
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{"symbol": "SBRY.L", "name": "Sainsbury's", "chain": "Sainsbury's", "market": "LSE"},
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{"symbol": "MKS.L", "name": "Marks & Spencer", "chain": "M&S Food", "market": "LSE"},
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{"symbol": "WMT", "name": "Walmart", "chain": "Global benchmark", "market": "NYSE"},
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{"symbol": "ULVR.L", "name": "Unilever", "chain": "FMCG / food", "market": "LSE"},
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]
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def _fetch_chart(symbol: str) -> dict[str, Any]:
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url = (
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f"https://query1.finance.yahoo.com/v8/finance/chart/{symbol}"
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f"?interval=1d&range=1mo&includePrePost=false"
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)
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req = Request(url, headers={"User-Agent": USER_AGENT})
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with urlopen(req, timeout=12) as resp:
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payload = json.loads(resp.read().decode())
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result = (payload.get("chart") or {}).get("result") or []
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if not result:
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return {}
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meta = result[0].get("meta") or {}
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closes = (result[0].get("indicators") or {}).get("quote") or [{}]
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close_series = closes[0].get("close") or []
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valid = [c for c in close_series if c is not None]
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sparkline = valid[-14:] if len(valid) >= 14 else valid
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prev = valid[-2] if len(valid) >= 2 else None
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last = valid[-1] if valid else meta.get("regularMarketPrice")
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change_pct = meta.get("regularMarketChangePercent")
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if change_pct is None and prev and last and prev:
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change_pct = ((last - prev) / prev) * 100
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return {
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"price": meta.get("regularMarketPrice") or last,
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"currency": meta.get("currency") or "EUR",
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"change_pct": round(float(change_pct or 0), 2),
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"sparkline": [round(float(v), 2) for v in sparkline],
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"market_state": meta.get("marketState") or "CLOSED",
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}
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def fetch_retail_quotes() -> list[dict[str, Any]]:
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try:
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req = Request(f"{TOOLS}/retail/market/stocks", headers={"User-Agent": USER_AGENT})
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with urlopen(req, timeout=15) as resp:
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data = json.loads(resp.read().decode())
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if data.get("items"):
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return data["items"]
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except Exception:
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pass
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items: list[dict[str, Any]] = []
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for stock in RETAIL_STOCKS:
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row = dict(stock)
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try:
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chart = _fetch_chart(stock["symbol"])
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row.update(chart)
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row["trend"] = "up" if (row.get("change_pct") or 0) >= 0 else "down"
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except Exception:
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row["price"] = None
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row["change_pct"] = 0
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row["sparkline"] = []
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row["trend"] = "flat"
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items.append(row)
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return items
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def market_summary(quotes: list[dict[str, Any]] | None = None) -> dict[str, Any]:
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quotes = quotes or fetch_retail_quotes()
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valid = [q for q in quotes if q.get("price") is not None]
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avg_change = sum(float(q.get("change_pct") or 0) for q in valid) / len(valid) if valid else 0
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best = max(valid, key=lambda q: float(q.get("change_pct") or 0), default=None)
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worst = min(valid, key=lambda q: float(q.get("change_pct") or 0), default=None)
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return {
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"avg_change_pct": round(avg_change, 2),
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"best_performer": best,
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"worst_performer": worst,
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"quote_count": len(valid),
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}
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