core/visual_comparison.py

"""
Module: visual_comparison.py
Purpose: Interactive crypto pair comparison (Plotly + CoinGecko)
"""

import requests
import pandas as pd
import plotly.graph_objects as go

COINGECKO_API = "https://api.coingecko.com/api/v3"


def get_coin_history(coin_id: str, days: int = 180):
    """Fetch historical market data for given coin from CoinGecko API."""
    url = f"{COINGECKO_API}/coins/{coin_id}/market_chart?vs_currency=usd&days={days}"
    r = requests.get(url)
    r.raise_for_status()
    data = r.json()
    df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
    df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
    return df


def build_price_chart(pair: tuple[str, str], days: int = 180):
    """Build comparative price chart for selected pair."""
    coin_a, coin_b = pair

    df_a = get_coin_history(coin_a, days)
    df_b = get_coin_history(coin_b, days)

    fig = go.Figure()
    fig.add_trace(go.Scatter(
        x=df_a["timestamp"],
        y=df_a["price"],
        name=f"{coin_a.capitalize()} / USD",
        line=dict(width=2),
    ))
    fig.add_trace(go.Scatter(
        x=df_b["timestamp"],
        y=df_b["price"],
        name=f"{coin_b.capitalize()} / USD",
        line=dict(width=2),
    ))

    fig.update_layout(
        template="plotly_dark",
        height=480,
        margin=dict(l=40, r=20, t=30, b=40),
        xaxis_title="Date",
        yaxis_title="Price (USD)",
        legend_title="Asset",
        hovermode="x unified",
    )

    return fig


def build_volatility_chart(pair: tuple[str, str], days: int = 180):
    """Build comparative volatility chart for selected pair."""
    coin_a, coin_b = pair

    df_a = get_coin_history(coin_a, days)
    df_b = get_coin_history(coin_b, days)

    df_a["returns"] = df_a["price"].pct_change() * 100
    df_b["returns"] = df_b["price"].pct_change() * 100

    fig = go.Figure()
    fig.add_trace(go.Scatter(
        x=df_a["timestamp"],
        y=df_a["returns"],
        name=f"{coin_a.upper()} Daily Change (%)",
        mode="lines",
        line=dict(width=1.6),
    ))
    fig.add_trace(go.Scatter(
        x=df_b["timestamp"],
        y=df_b["returns"],
        name=f"{coin_b.upper()} Daily Change (%)",
        mode="lines",
        line=dict(width=1.6),
    ))

    fig.update_layout(
        template="plotly_dark",
        height=400,
        margin=dict(l=40, r=20, t=30, b=40),
        xaxis_title="Date",
        yaxis_title="Daily Change (%)",
        legend_title="Volatility",
        hovermode="x unified",
    )

    return fig