feat: configurable ticker window for market stats (1h, 4h, 1d)
- Replace hardcoded ticker_24h with ticker_stats supporting configurable window - Add -w/--window flag to `market tickers` (choices: 1h, 4h, 1d, default 1d) - Update TUI title and JSON output to include window field - Keep opportunity/pf service on 1d default - Sync tests and doc comments Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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@@ -52,13 +52,14 @@ class SpotBinanceClient:
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kwargs["symbol"] = symbol
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return self._call("exchange info", self._client.exchange_info, **kwargs) # type: ignore[no-any-return]
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def ticker_24h(self, symbols: list[str] | None = None) -> list[dict[str, Any]]:
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if not symbols:
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response = self._call("24h ticker", self._client.ticker_24hr)
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elif len(symbols) == 1:
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response = self._call("24h ticker", self._client.ticker_24hr, symbol=symbols[0])
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else:
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response = self._call("24h ticker", self._client.ticker_24hr, symbols=symbols)
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def ticker_stats(self, symbols: list[str] | None = None, *, window: str = "1d") -> list[dict[str, Any]]:
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kwargs: dict[str, Any] = {"windowSize": window}
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if symbols:
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if len(symbols) == 1:
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kwargs["symbol"] = symbols[0]
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else:
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kwargs["symbols"] = symbols
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response = self._call("ticker stats", self._client.ticker, **kwargs)
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return response if isinstance(response, list) else [response]
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def ticker_price(self, symbols: list[str] | None = None) -> list[dict[str, Any]]:
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@@ -136,6 +136,7 @@ Fields:
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"market/tickers": {
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"tui": """\
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TUI Output:
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TICKERS window=1d
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┌─────────┬────────────┬──────────┬──────────────┐
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│ Symbol │ Last Price │ Change % │ Quote Volume │
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├─────────┼────────────┼──────────┼──────────────┤
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@@ -147,26 +148,30 @@ JSON Output:
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{
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"tickers": [
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{"symbol": "BTCUSDT", "last_price": 70000.0, "price_change_pct": 2.5, "quote_volume": 123456.0}
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]
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],
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"window": "1d"
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}
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Fields:
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symbol – normalized trading pair (e.g. "BTCUSDT")
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last_price – latest traded price (float)
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price_change_pct – 24h change % (float, e.g. 2.5 = +2.5%)
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quote_volume – 24h quote volume (float)
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price_change_pct – change % over the selected window (float, e.g. 2.5 = +2.5%)
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quote_volume – quote volume over the selected window (float)
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window – statistics window (enum: 1h, 4h, 1d)
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""",
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"json": """\
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JSON Output:
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{
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"tickers": [
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{"symbol": "BTCUSDT", "last_price": 70000.0, "price_change_pct": 2.5, "quote_volume": 123456.0}
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]
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],
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"window": "1d"
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}
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Fields:
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symbol – normalized trading pair (e.g. "BTCUSDT")
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last_price – latest traded price (float)
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price_change_pct – 24h change % (float, e.g. 2.5 = +2.5%)
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quote_volume – 24h quote volume (float)
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price_change_pct – change % over the selected window (float, e.g. 2.5 = +2.5%)
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quote_volume – quote volume over the selected window (float)
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window – statistics window (enum: 1h, 4h, 1d)
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""",
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},
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"market/klines": {
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@@ -720,10 +725,14 @@ def build_parser() -> argparse.ArgumentParser:
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)
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market_subparsers = market_parser.add_subparsers(dest="market_command")
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tickers_parser = market_subparsers.add_parser(
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"tickers", aliases=["tk", "t"], help="Fetch 24h ticker data",
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description="Fetch 24h ticker statistics (last price, change %, volume) for one or more symbols.",
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"tickers", aliases=["tk", "t"], help="Fetch ticker statistics",
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description="Fetch ticker statistics (last price, change %, volume) for one or more symbols with optional window.",
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)
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tickers_parser.add_argument("symbols", nargs="+", metavar="SYM", help="Symbols to query (e.g. BTCUSDT ETH/USDT)")
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tickers_parser.add_argument(
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"-w", "--window", choices=["1h", "4h", "1d"], default="1d",
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help="Statistics window: 1h, 4h, 1d (default: 1d)",
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)
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_add_global_flags(tickers_parser)
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klines_parser = market_subparsers.add_parser(
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"klines", aliases=["k"], help="Fetch OHLCV klines",
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@@ -987,7 +996,9 @@ def main(argv: list[str] | None = None) -> int:
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spot_client = _load_spot_client(config)
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if args.market_command == "tickers":
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with with_spinner("Fetching tickers...", enabled=not args.agent):
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result = market_service.get_tickers(config, args.symbols, spot_client=spot_client)
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result = market_service.get_tickers(
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config, args.symbols, spot_client=spot_client, window=args.window
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)
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print_output(result, agent=args.agent)
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return 0
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if args.market_command == "klines":
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@@ -278,7 +278,7 @@ def _render_tui(payload: Any) -> None:
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]
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)
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_print_box_table(
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"24H TICKERS",
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f"TICKERS window={payload.get('window', '1d')}",
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["Symbol", "Last Price", "Change %", "Quote Volume"],
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table_rows,
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aligns=["left", "right", "right", "right"],
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@@ -48,10 +48,10 @@ class KlineView:
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quote_volume: float
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def get_tickers(config: dict[str, Any], symbols: list[str], *, spot_client: Any) -> dict[str, Any]:
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def get_tickers(config: dict[str, Any], symbols: list[str], *, spot_client: Any, window: str = "1d") -> dict[str, Any]:
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normalized = normalize_symbols(symbols)
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rows = []
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for ticker in spot_client.ticker_24h(normalized):
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for ticker in spot_client.ticker_stats(normalized, window=window):
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rows.append(
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asdict(
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TickerView(
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@@ -64,7 +64,7 @@ def get_tickers(config: dict[str, Any], symbols: list[str], *, spot_client: Any)
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)
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)
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)
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return {"tickers": rows}
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return {"tickers": rows, "window": window}
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def get_klines(
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@@ -103,6 +103,7 @@ def get_scan_universe(
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*,
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spot_client: Any,
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symbols: list[str] | None = None,
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window: str = "1d",
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) -> list[dict[str, Any]]:
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market_config = config.get("market", {})
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opportunity_config = config.get("opportunity", {})
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@@ -116,7 +117,7 @@ def get_scan_universe(
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status_map = {normalize_symbol(item["symbol"]): item.get("status", "") for item in exchange_info.get("symbols", [])}
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rows: list[dict[str, Any]] = []
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for ticker in spot_client.ticker_24h(list(requested) if requested else None):
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for ticker in spot_client.ticker_stats(list(requested) if requested else None, window=window):
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symbol = normalize_symbol(ticker["symbol"])
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if not symbol.endswith(quote):
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continue
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@@ -104,7 +104,7 @@ def analyze_portfolio(config: dict[str, Any], *, spot_client: Any) -> dict[str,
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klines = spot_client.klines(symbol=symbol, interval="1h", limit=24)
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closes = [float(item[4]) for item in klines]
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volumes = [float(item[5]) for item in klines]
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tickers = spot_client.ticker_24h([symbol])
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tickers = spot_client.ticker_stats([symbol], window="1d")
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ticker = tickers[0] if tickers else {"priceChangePercent": "0"}
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concentration = position["notional_usdt"] / total_notional
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score, metrics = _score_candidate(
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