New tabs and functions v3.5

core/crypto_dashboard.py

@@ -1,9 +1,6 @@
 """
-Crypto Dashboard — Plotly Edition + KPI Line
-Source: Coinlore API
-Changes:
-- KPI строка (без карточек), чтобы не прыгала вёрстка
-- Больше заполнение блока графиками (меньше отступов)
+Crypto Dashboard — Plotly Edition + KPI Line (clean version)
+Удалены встроенные заголовки из графиков.
 """
 import requests
 import pandas as pd
@@ -22,10 +19,7 @@ def fetch_coinlore_data(limit=100):
 
 
 def _kpi_line(df) -> str:
-    """
-    Возвращает одну строку: BTC $xx (Δ%), ETH $yy (Δ%), ...
-    чтобы место не прыгало при подгрузке.
-    """
+    """Возвращает строку KPI: BTC $xx (Δ%), ETH $yy (Δ%), ..."""
     tracked = ["BTC", "ETH", "SOL", "DOGE"]
     parts = []
     for sym in tracked:
@@ -36,57 +30,80 @@ def _kpi_line(df) -> str:
         ch = float(row["percent_change_24h"])
         arrow = "↑" if ch > 0 else "↓"
         color = "#4ade80" if ch > 0 else "#f87171"
-        parts.append(f"<span class='kpi-item'><b>{sym}</b> ${price:,.0f} <span style='color:{color}'>{arrow} {abs(ch):.2f}%</span></span>")
-    # Разделение запятой с пробелом
+        parts.append(
+            f"<span class='kpi-item'><b>{sym}</b> ${price:,.0f} "
+            f"<span style='color:{color}'>{arrow} {abs(ch):.2f}%</span></span>"
+        )
     return " , ".join(parts)
 
 
 def build_crypto_dashboard(top_n=50):
     df = fetch_coinlore_data(top_n)
 
-    # Treemap — плотный
+    # === Treemap (чистый, без заголовка) ===
     fig_treemap = px.treemap(
-        df, path=["symbol"], values="market_cap_usd",
-        color="percent_change_24h", color_continuous_scale="RdYlGn",
-        title="Market Composition by Market Cap (Top Coins)",
-        height=420
+        df,
+        path=["symbol"],
+        values="market_cap_usd",
+        color="percent_change_24h",
+        color_continuous_scale="RdYlGn",
+        height=420,
     )
     fig_treemap.update_layout(
-        template="plotly_dark", autosize=True,
-        margin=dict(l=5, r=5, t=28, b=5),
-        paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)"
+        title=None,  # 🔹 Убираем встроенный заголовок
+        template="plotly_dark",
+        autosize=True,
+        margin=dict(l=5, r=5, t=5, b=5),
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
     )
 
-    # Top gainers — плотный
+    # === Top Gainers (24h) ===
     top = df.sort_values("percent_change_24h", ascending=False).head(12)
     fig_bar = px.bar(
-        top, x="percent_change_24h", y="symbol",
-        orientation="h", color="percent_change_24h",
+        top,
+        x="percent_change_24h",
+        y="symbol",
+        orientation="h",
+        color="percent_change_24h",
         color_continuous_scale="Blues",
-        title="Top 12 Gainers (24h)", height=320
+        height=320,
     )
     fig_bar.update_layout(
-        template="plotly_dark", autosize=True,
-        margin=dict(l=40, r=10, t=28, b=18),
-        paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)"
+        title=None,  # 🔹 убран встроенный title
+        template="plotly_dark",
+        autosize=True,
+        margin=dict(l=40, r=10, t=5, b=18),
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
     )
 
-    # Bubble
+    # === Market Cap vs Volume ===
     fig_bubble = px.scatter(
-        df.head(60), x="market_cap_usd", y="volume24",
-        size="price_usd", color="percent_change_7d", hover_name="symbol",
-        log_x=True, log_y=True, color_continuous_scale="RdYlGn",
-        title="Market Cap vs 24h Volume", height=320
+        df.head(60),
+        x="market_cap_usd",
+        y="volume24",
+        size="price_usd",
+        color="percent_change_7d",
+        hover_name="symbol",
+        log_x=True,
+        log_y=True,
+        color_continuous_scale="RdYlGn",
+        height=320,
     )
     fig_bubble.update_layout(
-        template="plotly_dark", autosize=True,
-        margin=dict(l=36, r=10, t=28, b=18),
-        paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)"
+        title=None,  # 🔹 убран встроенный title
+        template="plotly_dark",
+        autosize=True,
+        margin=dict(l=36, r=10, t=5, b=18),
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
     )
 
-    # AI summary
+    # === AI summary ===
     summary = _ai_summary(df)
     kpi_text = _kpi_line(df)
+
     return fig_treemap, fig_bar, fig_bubble, summary, kpi_text