New tabs and functions v1.8

core/crypto_dashboard.py

@@ -1,24 +1,22 @@
 """
 🇬🇧 Module: crypto_dashboard.py
-Purpose: Unified dashboard for live & historical crypto analytics (Binance + TradingView)
+Purpose: Unified dashboard for live & historical crypto analytics (Binance + Yahoo Finance)
 🇷🇺 Модуль: crypto_dashboard.py
-Назначение: Единый дашборд для рыночного и исторического анализа крипты.
+Назначение: Единый дашборд для анализа крипторынка на Binance и Yahoo.
 """
 
 import requests
 import pandas as pd
+import yfinance as yf
 import plotly.express as px
 import plotly.graph_objects as go
-from datetime import datetime, timedelta
-from tvDatafeed import TvDatafeed, Interval
 from services.llm_client import llm_service
 
 BINANCE_API = "https://api.binance.com/api/v3"
-tv = TvDatafeed()  # без авторизации — работает для публичных тикеров
 
 
 # === Binance data (live candles) ===
-def get_binance_klines(symbol: str = "BTCUSDT", interval="1d", limit=365):
+def get_binance_klines(symbol: str = "BTCUSDT", interval="1d", limit=180):
     url = f"{BINANCE_API}/klines?symbol={symbol}&interval={interval}&limit={limit}"
     data = requests.get(url).json()
     df = pd.DataFrame(data, columns=[
@@ -30,20 +28,22 @@ def get_binance_klines(symbol: str = "BTCUSDT", interval="1d", limit=365):
     return df
 
 
-# === TradingView data (extended history) ===
-def get_tv_history(symbols: list[str], exchange="BINANCE", bars=1000):
+# === Yahoo Finance historical data ===
+def get_yf_history(symbols: list[str]):
     frames = []
     for s in symbols:
         try:
-            df = tv.get_hist(symbol=s.replace("USDT", ""), exchange=exchange, interval=Interval.in_daily, n_bars=bars)
+            ticker = s.replace("USDT", "-USD")
+            df = yf.download(ticker, period="5y", interval="1d", progress=False)
+            df = df.reset_index()[["Date", "Close"]]
+            df.columns = ["datetime", "close"]
             df["symbol"] = s
             frames.append(df)
         except Exception:
             continue
     if not frames:
         return pd.DataFrame()
-    df_all = pd.concat(frames).reset_index()
-    return df_all
+    return pd.concat(frames, ignore_index=True)
 
 
 # === Build Dashboard ===
@@ -51,29 +51,34 @@ def build_crypto_dashboard(selected_assets: list[str], start_date: str, end_date
     if not selected_assets:
         selected_assets = ["BTCUSDT", "ETHUSDT", "BNBUSDT"]
 
-    # --- Binance multi-asset (recent) ---
+    # --- Binance recent ---
     recent_frames = []
     for sym in selected_assets:
         df = get_binance_klines(sym, "1d", 180)
         recent_frames.append(df.assign(symbol=sym))
     df_recent = pd.concat(recent_frames)
+
     fig_recent = px.line(
         df_recent, x="timestamp", y="close", color="symbol",
-        title="Market Prices (Binance, recent 6 months)", template="plotly_dark"
+        title="Market Prices (Binance, recent 6 months)",
+        template="plotly_dark"
     )
     fig_recent.update_layout(height=420, legend_title_text="Asset")
 
-    # --- TradingView history (normalized) ---
-    df_hist = get_tv_history(selected_assets)
+    # --- Yahoo historical normalized ---
+    df_hist = get_yf_history(selected_assets)
     if not df_hist.empty:
         df_hist["returns"] = df_hist.groupby("symbol")["close"].apply(lambda x: x / x.iloc[0] - 1)
         fig_hist = px.line(df_hist, x="datetime", y="returns", color="symbol",
-                           title="Historical Normalized Performance (TradingView)",
+                           title="Historical Normalized Performance (Yahoo Finance)",
                            template="plotly_dark")
         fig_hist.update_layout(height=420)
     else:
         fig_hist = go.Figure()
-        fig_hist.add_annotation(text="No TradingView data available", xref="paper", yref="paper", x=0.5, y=0.5, showarrow=False)
+        fig_hist.add_annotation(
+            text="No Yahoo Finance data available",
+            xref="paper", yref="paper", x=0.5, y=0.5, showarrow=False
+        )
 
     # --- AI Market Summary ---
     summary = _generate_ai_summary(df_recent, df_hist, selected_assets)
@@ -94,14 +99,12 @@ def _generate_ai_summary(df_recent, df_hist, assets):
     growth_text = ", ".join(growth)
 
     prompt = f"""
-Analyze current crypto market based on these assets:
-{', '.join(assets)}.
-
-Performance last months: {growth_text}.
-Generate a concise summary:
+Analyze the crypto market based on these assets: {', '.join(assets)}.
+Performance (last 6 months): {growth_text}.
+Give a concise professional summary:
 - Market direction (bullish/bearish)
-- Relative leaders/laggards
-- Risk tone and volatility
+- Volatility trends
+- Leaders vs laggards
 - Short-term outlook
 """
     summary = ""

requirements.txt

@@ -5,4 +5,6 @@ httpx
 pandas
 matplotlib
 plotly
-tvDatafeed>=1.0.9
+yfinance>=0.2.43
+plotly>=6.3.1
+