"""Macro tab — market-wide panels: Index Performance, Yield Curve, Sector Heatmap."""
import streamlit as st
import streamlit.components.v1 as _html
import plotly.graph_objects as go
import yfinance as yf
import pandas as pd
from datetime import date as _date


_INDICES = {
    "S&P 500": "^GSPC",
    "NASDAQ":  "^IXIC",
    "DOW":     "^DJI",
    "Russell": "^RUT",
    "VIX":     "^VIX",
}

# (symbol, divisor) — yfinance encodes yields as rate×divisor
_YIELDS = {
    "3M":  ("^IRX", 100),
    "5Y":  ("^FVX", 10),
    "10Y": ("^TNX", 10),
    "30Y": ("^TYX", 10),
}

_SECTORS = {
    "Technology":   "XLK",
    "Financials":   "XLF",
    "Healthcare":   "XLV",
    "Energy":       "XLE",
    "Industrials":  "XLI",
    "Cons. Disc.":  "XLY",
    "Cons. Stap.":  "XLP",
    "Utilities":    "XLU",
    "Real Estate":  "XLRE",
    "Materials":    "XLB",
    "Comm. Svcs.":  "XLC",
}


# ── Data fetch ────────────────────────────────────────────────────────────────

@st.cache_data(ttl=300)
def _get_macro_data() -> dict:
    indices = {}
    for name, sym in _INDICES.items():
        try:
            hist = yf.Ticker(sym).history(period="1y")
            if hist.empty:
                indices[name] = None
                continue
            closes = hist["Close"].dropna()
            last = float(closes.iloc[-1])

            def _pct(n):
                if len(closes) > n:
                    return float((closes.iloc[-1] - closes.iloc[-(n + 1)]) / closes.iloc[-(n + 1)] * 100)
                return None

            p1d = _pct(1)
            p1w = _pct(5)
            p1m = _pct(21)

            today = _date.today()
            jan1 = pd.Timestamp(today.year, 1, 1)
            idx = closes.index
            if idx.tz is not None:
                jan1 = jan1.tz_localize(idx.tz)
            ytd_slice = closes[idx.normalize() >= jan1.normalize()]
            pytd = float((last - float(ytd_slice.iloc[0])) / float(ytd_slice.iloc[0]) * 100) if not ytd_slice.empty else None

            indices[name] = {"price": last, "1d": p1d, "1w": p1w, "1m": p1m, "ytd": pytd}
        except Exception:
            indices[name] = None

    yields = {}
    for label, (sym, div) in _YIELDS.items():
        try:
            hist = yf.Ticker(sym).history(period="5d")
            if hist.empty:
                yields[label] = None
                continue
            closes = hist["Close"].dropna()
            curr = float(closes.iloc[-1]) / div
            prev = float(closes.iloc[-2]) / div if len(closes) >= 2 else None
            yields[label] = {"rate": curr, "change_1d": (curr - prev) if prev is not None else None}
        except Exception:
            yields[label] = None

    sectors = {}
    for name, etf in _SECTORS.items():
        try:
            hist = yf.Ticker(etf).history(period="2d")
            if len(hist) >= 2:
                pct = float((hist["Close"].iloc[-1] - hist["Close"].iloc[-2]) / hist["Close"].iloc[-2] * 100)
                price = float(hist["Close"].iloc[-1])
            elif len(hist) == 1:
                pct = 0.0
                price = float(hist["Close"].iloc[-1])
            else:
                sectors[name] = None
                continue
            sectors[name] = {"etf": etf, "pct": pct, "price": price}
        except Exception:
            sectors[name] = None

    return {"indices": indices, "yields": yields, "sectors": sectors}


# ── Helpers ───────────────────────────────────────────────────────────────────

def _pct_cell(v) -> str:
    """Return an HTML <span> with color class for a % value."""
    if v is None:
        return "<span class='flat'>—</span>"
    sign = "+" if v >= 0 else ""
    cls = "pos" if v > 0.005 else ("neg" if v < -0.005 else "flat")
    return "<span class='" + cls + "'>" + sign + f"{v:.2f}%" + "</span>"


def _sector_bg(pct: float) -> str:
    """Interpolate background color between neutral and pos/neg based on magnitude."""
    neutral = (24, 29, 38)
    pos_bg  = (21, 36, 26)
    neg_bg  = (42, 21, 23)
    intensity = min(1.0, abs(pct) / 3.0)
    target = pos_bg if pct >= 0 else neg_bg
    r = int(neutral[0] + (target[0] - neutral[0]) * intensity)
    g = int(neutral[1] + (target[1] - neutral[1]) * intensity)
    b = int(neutral[2] + (target[2] - neutral[2]) * intensity)
    return "rgb(" + str(r) + "," + str(g) + "," + str(b) + ")"


# ── Panel renderers ───────────────────────────────────────────────────────────

def _render_index_table(indices: dict) -> None:
    css = (
        "<style>"
        "* { margin:0; padding:0; box-sizing:border-box; }"
        "body { background:#0B0E13; font-family:'IBM Plex Mono',monospace; overflow:hidden; }"
        "table { width:100%; border-collapse:collapse; }"
        "thead th {"
        "  font-family:'IBM Plex Sans',sans-serif; font-size:10px; font-weight:600;"
        "  text-transform:uppercase; letter-spacing:0.14em; color:#5E5849;"
        "  padding:7px 12px 7px; border-bottom:1px solid #232934; text-align:right; }"
        "thead th:first-child { text-align:left; }"
        "tbody tr { border-bottom:1px solid #181D26; }"
        "tbody td { padding:9px 12px; font-size:13px; color:#C7C0AE; text-align:right; "
        "  font-variant-numeric:tabular-nums; }"
        "tbody td:first-child { text-align:left; color:#F2ECDC; font-size:12px; letter-spacing:0.02em; }"
        ".pos { color:#4F8C5E; } .neg { color:#B5494B; } .flat { color:#5E5849; }"
        "</style>"
    )
    head = (
        "<table><thead><tr>"
        "<th>Index</th><th>Price</th><th>1D</th><th>1W</th><th>1M</th><th>YTD</th>"
        "</tr></thead><tbody>"
    )
    rows = ""
    for name, d in indices.items():
        if d is None:
            rows += "<tr><td>" + name + "</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr>"
            continue
        price = f"{d['price']:,.2f}"
        rows += (
            "<tr><td>" + name + "</td>"
            "<td>" + price + "</td>"
            "<td>" + _pct_cell(d["1d"]) + "</td>"
            "<td>" + _pct_cell(d["1w"]) + "</td>"
            "<td>" + _pct_cell(d["1m"]) + "</td>"
            "<td>" + _pct_cell(d["ytd"]) + "</td>"
            "</tr>"
        )
    _html.html(css + head + rows + "</tbody></table>", height=290, scrolling=False)


def _render_yield_curve(yields: dict) -> None:
    labels = list(yields.keys())
    rates = [yields[l]["rate"] if yields[l] else None for l in labels]
    valid = [(l, r) for l, r in zip(labels, rates) if r is not None]

    fig = go.Figure()
    if valid:
        xl, yl = zip(*valid)
        fig.add_trace(go.Scatter(
            x=list(xl),
            y=list(yl),
            mode="lines+markers",
            line=dict(color="#C2AA7A", width=2),
            marker=dict(size=7, color="#C2AA7A", line=dict(width=1, color="#8F7A50")),
            hovertemplate="%{x}: %{y:.2f}%<extra></extra>",
        ))

    fig.update_layout(
        xaxis_title="Maturity",
        yaxis=dict(tickformat=".2f", ticksuffix="%"),
        height=240,
        margin=dict(l=52, r=16, t=16, b=40),
    )
    st.plotly_chart(fig, use_container_width=True)


def _render_yield_table(yields: dict) -> None:
    css = (
        "<style>"
        "* { margin:0; padding:0; box-sizing:border-box; }"
        "body { background:#0B0E13; font-family:'IBM Plex Mono',monospace; overflow:hidden; }"
        "table { width:100%; border-collapse:collapse; }"
        "thead th { font-family:'IBM Plex Sans',sans-serif; font-size:10px; font-weight:600;"
        "  text-transform:uppercase; letter-spacing:0.14em; color:#5E5849;"
        "  padding:6px 10px; border-bottom:1px solid #232934; text-align:right; }"
        "thead th:first-child { text-align:left; }"
        "tbody tr { border-bottom:1px solid #181D26; }"
        "tbody td { padding:8px 10px; font-size:13px; color:#C7C0AE; text-align:right;"
        "  font-variant-numeric:tabular-nums; }"
        "tbody td:first-child { text-align:left; color:#F2ECDC; }"
        ".pos { color:#4F8C5E; } .neg { color:#B5494B; } .flat { color:#5E5849; }"
        "</style>"
    )
    head = (
        "<table><thead><tr>"
        "<th>Maturity</th><th>Yield</th><th>1D Chg</th>"
        "</tr></thead><tbody>"
    )
    rows = ""
    for label, d in yields.items():
        if d is None:
            rows += "<tr><td>" + label + "</td><td>—</td><td>—</td></tr>"
            continue
        rate = f"{d['rate']:.2f}%"
        chg = d["change_1d"]
        sign = "+" if chg is not None and chg >= 0 else ""
        chg_s = (sign + f"{chg:.2f}%") if chg is not None else "—"
        cls = "pos" if (chg or 0) > 0.001 else ("neg" if (chg or 0) < -0.001 else "flat")
        rows += (
            "<tr><td>" + label + "</td>"
            "<td>" + rate + "</td>"
            "<td><span class='" + cls + "'>" + chg_s + "</span></td>"
            "</tr>"
        )
    _html.html(css + head + rows + "</tbody></table>", height=240, scrolling=False)


def _render_sector_heatmap(sectors: dict) -> None:
    css = (
        "<style>"
        "* { margin:0; padding:0; box-sizing:border-box; }"
        "body { background:#0B0E13; font-family:'IBM Plex Sans',sans-serif; overflow:hidden; }"
        ".grid { display:grid; grid-template-columns:repeat(4,1fr); gap:4px; padding:2px; }"
        ".cell { padding:10px 12px; border-radius:2px; border:1px solid #232934; }"
        ".cell .name { font-size:11px; font-weight:600; color:#C7C0AE; letter-spacing:0.01em; }"
        ".cell .etf { font-family:'IBM Plex Mono',monospace; font-size:10px; color:#5E5849; margin-top:1px; }"
        ".cell .pct { font-family:'IBM Plex Mono',monospace; font-size:14px; font-weight:500; margin-top:5px;"
        "  font-variant-numeric:tabular-nums; }"
        ".pos { color:#4F8C5E; } .neg { color:#B5494B; } .flat { color:#5E5849; }"
        "</style>"
        "<div class='grid'>"
    )
    cells = ""
    for name, d in sectors.items():
        if d is None:
            cells += (
                "<div class='cell' style='background:#11151C'>"
                "<div class='name'>" + name + "</div>"
                "<div class='pct flat'>—</div>"
                "</div>"
            )
            continue
        pct = d["pct"]
        bg = _sector_bg(pct)
        sign = "+" if pct >= 0 else ""
        cls = "pos" if pct > 0.005 else ("neg" if pct < -0.005 else "flat")
        cells += (
            "<div class='cell' style='background:" + bg + "'>"
            "<div class='name'>" + name + "</div>"
            "<div class='etf'>" + d["etf"] + "</div>"
            "<div class='pct " + cls + "'>" + sign + f"{pct:.2f}%" + "</div>"
            "</div>"
        )
    _html.html(css + cells + "</div>", height=340, scrolling=False)


# ── Public entry point ────────────────────────────────────────────────────────

def render_macro() -> None:
    data = _get_macro_data()

    st.markdown(
        "<h5 style='font-family:\"IBM Plex Sans\",sans-serif;font-size:10px;font-weight:600;"
        "text-transform:uppercase;letter-spacing:0.14em;color:#5E5849;margin-bottom:8px;'>Index Performance</h5>",
        unsafe_allow_html=True,
    )
    _render_index_table(data["indices"])

    st.markdown("<div style='height:24px'></div>", unsafe_allow_html=True)

    col1, col2 = st.columns([3, 2])
    with col1:
        st.markdown(
            "<h5 style='font-family:\"IBM Plex Sans\",sans-serif;font-size:10px;font-weight:600;"
            "text-transform:uppercase;letter-spacing:0.14em;color:#5E5849;margin-bottom:8px;'>Yield Curve</h5>",
            unsafe_allow_html=True,
        )
        _render_yield_curve(data["yields"])
    with col2:
        st.markdown(
            "<h5 style='font-family:\"IBM Plex Sans\",sans-serif;font-size:10px;font-weight:600;"
            "text-transform:uppercase;letter-spacing:0.14em;color:#5E5849;margin-bottom:8px;'>Treasury Yields</h5>",
            unsafe_allow_html=True,
        )
        _render_yield_table(data["yields"])

    st.markdown("<div style='height:24px'></div>", unsafe_allow_html=True)

    st.markdown(
        "<h5 style='font-family:\"IBM Plex Sans\",sans-serif;font-size:10px;font-weight:600;"
        "text-transform:uppercase;letter-spacing:0.14em;color:#5E5849;margin-bottom:8px;'>Sector Performance — Today</h5>",
        unsafe_allow_html=True,
    )
    _render_sector_heatmap(data["sectors"])