Add Binance REST client with OHLCV, ticker, and volume methods

Implements BinanceRestClient wrapping python-binance with get_top_coins,
get_ohlcv, get_all_prices, and get_24h_volume. Includes mocked unit tests
for all public methods.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

data/binance_rest.py

@@ -0,0 +1,42 @@
+import pandas as pd
+from binance.client import Client
+import logging
+
+logger = logging.getLogger(__name__)
+
+class BinanceRestClient:
+    def __init__(self, api_key: str, api_secret: str):
+        self.client = Client(api_key, api_secret)
+
+    def get_top_coins(self, limit: int = 50) -> list[str]:
+        tickers = self.client.get_ticker()
+        usdt_pairs = [
+            t for t in tickers
+            if t["symbol"].endswith("USDT") and not t["symbol"].startswith("USDT")
+        ]
+        usdt_pairs.sort(key=lambda x: float(x["quoteVolume"]), reverse=True)
+        return [t["symbol"] for t in usdt_pairs[:limit]]
+
+    def get_ohlcv(self, symbol: str, interval: str = "1h", limit: int = 100) -> pd.DataFrame:
+        klines = self.client.get_klines(symbol=symbol, interval=interval, limit=limit)
+        df = pd.DataFrame(klines, columns=[
+            "timestamp", "open", "high", "low", "close", "volume",
+            "close_time", "quote_volume", "trades", "taker_buy_base",
+            "taker_buy_quote", "ignore",
+        ])
+        for col in ["open", "high", "low", "close", "volume", "quote_volume"]:
+            df[col] = df[col].astype(float)
+        df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
+        return df[["timestamp", "open", "high", "low", "close", "volume", "quote_volume"]]
+
+    def get_all_prices(self) -> dict[str, float]:
+        tickers = self.client.get_all_tickers()
+        return {t["symbol"]: float(t["price"]) for t in tickers}
+
+    def get_24h_volume(self, symbol: str) -> dict:
+        ticker = self.client.get_ticker(symbol=symbol)
+        return {
+            "volume": float(ticker["volume"]),
+            "quote_volume": float(ticker["quoteVolume"]),
+            "price_change_pct": float(ticker["priceChangePercent"]),
+        }