Nothing but VC

core/visual_comparison.py

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+"""
+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