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https://github.com/shawnkim1997/All-in-one-Financial-Analysis.git
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shawnkim1997
38c56a5a43
Add asset-type aware market/overview flows, portfolio OCR reverse-engineering with exchange overrides, and interactive index heatmap features. Update README with recent updates and wire backend/frontend APIs for FX matrix, exchange options, and improved portfolio editing flows. Made-with: Cursor
72 lines
2.7 KiB
Python
72 lines
2.7 KiB
Python
"""Heatmap data service for index constituents."""
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from __future__ import annotations
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from typing import Any
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import pandas as pd
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import yfinance as yf
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async def get_index_constituents(index_name: str) -> list[str]:
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name = (index_name or "").lower().strip()
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if name == "sp500":
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try:
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table = pd.read_html("https://en.wikipedia.org/wiki/List_of_S%26P_500_companies")[0]
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return table["Symbol"].astype(str).str.replace(".", "-", regex=False).tolist()
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except Exception:
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return ["AAPL", "MSFT", "NVDA", "AMZN", "GOOGL", "META", "BRK-B", "TSLA", "UNH", "XOM"]
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if name == "nasdaq100":
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try:
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table = pd.read_html("https://en.wikipedia.org/wiki/Nasdaq-100")[4]
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return table["Ticker"].astype(str).tolist()
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except Exception:
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return ["AAPL", "MSFT", "NVDA", "AMZN", "GOOGL", "META", "TSLA", "AVGO", "COST", "NFLX"]
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if name == "kospi":
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return [
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"005930.KS", "000660.KS", "035420.KS", "051910.KS", "006400.KS",
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"035720.KS", "068270.KS", "028260.KS", "105560.KS", "012330.KS",
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"055550.KS", "034730.KS", "003550.KS", "015760.KS", "066570.KS",
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"032830.KS", "096770.KS", "009150.KS", "003670.KS", "018260.KS",
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]
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if name == "ftse100":
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return ["SHEL.L", "AZN.L", "HSBA.L", "ULVR.L", "BP.L", "GSK.L", "RIO.L", "LSEG.L"]
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return []
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def _calc_change_pct(ticker: str) -> float:
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try:
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hist = yf.Ticker(ticker).history(period="2d")
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if hist is not None and len(hist) >= 2:
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prev = float(hist["Close"].iloc[-2])
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cur = float(hist["Close"].iloc[-1])
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if prev != 0:
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return round((cur - prev) / prev * 100, 2)
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except Exception:
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pass
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return 0.0
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async def get_heatmap_data(index_name: str, top_n: int = 50) -> list[dict[str, Any]]:
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tickers = (await get_index_constituents(index_name))[: max(top_n, 1)]
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out: list[dict[str, Any]] = []
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for ticker in tickers:
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try:
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info = yf.Ticker(ticker).info or {}
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mcap = info.get("marketCap")
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if not mcap or float(mcap) <= 0:
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continue
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out.append(
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{
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"ticker": ticker.replace(".KS", "").replace(".L", ""),
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"name": info.get("shortName") or info.get("longName") or ticker,
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"sector": info.get("sector") or "Other",
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"market_cap": float(mcap),
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"change_pct": _calc_change_pct(ticker),
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}
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)
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except Exception:
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continue
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return sorted(out, key=lambda x: x["market_cap"], reverse=True)
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