from tulip.core import TulipLibrary
import pandas as pd
from arcticdb import QueryBuilder
import ipywidgets as widgets
from IPython.display import display, HTML, Markdown

risk_lib = TulipLibrary.risk()

# Load data
last_date = risk_lib.tail("counterparty_dashboard", 1).data.index[0]
q = QueryBuilder()
q = q[q["pricing_date"] == last_date]
df = risk_lib.read("counterparty_dashboard", query_builder=q).data.reset_index()

# Split into Equities and CDS
equities = df[df["security"].str.contains("EQUITY")].copy()
cds = df[df["security"].str.contains("CDS")].copy()

# Clean up column names for display
display_cols = [
    "SHORT_NAME",
    "PX_LAST",
    "CHG_PCT_1D",
    "CHG_PCT_5D",
    "CHG_PCT_1M",
    "CHG_PCT_1YR",
]
col_names = {
    "SHORT_NAME": "Name",
    "PX_LAST": "Price",
    "CHG_PCT_1D": "1D %",
    "CHG_PCT_5D": "5D %",
    "CHG_PCT_1M": "1M %",
    "CHG_PCT_1YR": "1Y %",
}


def style_changes(val):
    """Color code positive/negative changes"""
    if pd.isna(val):
        return ""
    color = "#2e7d32" if val > 0 else "#c62828" if val < 0 else "#666"
    return f"color: {color}; font-weight: 500"


def format_table(data, title, invert_colors=False):
    """Create a styled table for display"""
    table = data[display_cols].copy()
    table.columns = [col_names.get(c, c) for c in table.columns]

    change_cols = ["1D %", "5D %", "1M %", "1Y %"]

    styled = (
        table.style.format(
            {
                "Price": "{:,.2f}",
                "1D %": "{:+.2f}%",
                "5D %": "{:+.2f}%",
                "1M %": "{:+.2f}%",
                "1Y %": "{:+.2f}%",
            }
        )
        .map(lambda v: style_changes(-v if invert_colors else v), subset=change_cols)
        .set_properties(**{"text-align": "right"}, subset=["Price"] + change_cols)
        .set_properties(**{"text-align": "left"}, subset=["Name"])
        .set_table_styles(
            [
                {
                    "selector": "th",
                    "props": [
                        ("background-color", "#000000"),
                        ("color", "white"),
                        ("padding", "10px"),
                        ("font-weight", "600"),
                    ],
                },
                {"selector": "td", "props": [("padding", "8px 12px")]},
                {"selector": "tr:hover", "props": [("background-color", "#f5f5f5")]},
                {
                    "selector": "caption",
                    "props": [
                        ("caption-side", "top"),
                        ("font-size", "1.1em"),
                        ("font-weight", "bold"),
                        ("padding", "10px"),
                        ("color", "#000000"),
                    ],
                },
            ]
        )
        .hide(axis="index")
        .set_caption(title)
    )
    return styled

Counterparties¶

# Dashboard Header
pricing_dt = last_date.strftime("%B %d, %Y at %H:%M")
Markdown(f"_As of {pricing_dt}_")

# Equity Prices - Green = stock up (positive for counterparty health)
display(format_table(equities, "Bank Equity Prices"))

# CDS Spreads - Colors inverted: spread widening (positive) = bad, tightening (negative) = good
display(format_table(cds, "CDS Spreads (5Y Senior)", invert_colors=True))

# Legend
legend_html = """
<div style="margin-top: 20px; padding: 12px 16px; background: #f8f9fa; 
            border-left: 4px solid #1a237e; border-radius: 4px; font-size: 0.9em;">
    <strong>Color Guide:</strong> 
    <span style="color: #2e7d32; margin-left: 15px;">&#9650; Green = Favorable</span>
    <span style="color: #c62828; margin-left: 15px;">&#9660; Red = Adverse</span>
    <span style="color: #666; margin-left: 20px; font-style: italic;">
        (For CDS: spread tightening is favorable, widening is adverse)
    </span>
</div>
"""
display(HTML(legend_html))

from tulip_mania.notebook_related import notebook_updated

notebook_updated()