diff --git a/.env.example b/.env.example index fe09a64..36ad0fb 100644 --- a/.env.example +++ b/.env.example @@ -1,5 +1,7 @@ -# Cerbero MCP (locale durante Phase 1) -CERBERO_BASE_URL=http://localhost:9000 +# Cerbero MCP — VPS endpoint per dati storici reali +CERBERO_BASE_URL=https://cerbero-mcp.tielogic.xyz +# NOTE: per dati storici reali Phase 1 (BTC-PERPETUAL Deribit) serve il MAINNET_TOKEN. +# Il TESTNET_TOKEN punta agli endpoint testnet degli exchange — utile solo per smoke test. CERBERO_TESTNET_TOKEN= CERBERO_MAINNET_TOKEN= CERBERO_BOT_TAG=swarm-poc-phase1 diff --git a/pyproject.toml b/pyproject.toml index 9b0e015..e2be236 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,6 @@ description = "Multi-Swarm Coevolutive PoC trading swarm — Phase 1 lean spike" authors = [{ name = "Adriano Dal Pastro", email = "adrianodalpastro@tielogic.com" }] requires-python = ">=3.13" dependencies = [ - "ccxt>=4.4", "pandas>=2.2", "numpy>=2.1", "scipy>=1.14", diff --git a/scripts/run_phase1.py b/scripts/run_phase1.py index 2175935..daabea1 100644 --- a/scripts/run_phase1.py +++ b/scripts/run_phase1.py @@ -3,8 +3,9 @@ from __future__ import annotations import argparse from datetime import datetime +from multi_swarm.cerbero.client import CerberoClient from multi_swarm.config import load_settings -from multi_swarm.data.ohlcv_loader import OHLCVLoader, OHLCVRequest +from multi_swarm.data.cerbero_ohlcv import CerberoOHLCVLoader, OHLCVRequest from multi_swarm.genome.hypothesis import ModelTier from multi_swarm.llm.client import LLMClient from multi_swarm.orchestrator.run import RunConfig, run_phase1 @@ -19,7 +20,12 @@ def parse_args() -> argparse.Namespace: p.add_argument("--tournament-k", type=int, default=3) p.add_argument("--p-crossover", type=float, default=0.5) p.add_argument("--seed", type=int, default=42) - p.add_argument("--symbol", default="BTC/USDT") + p.add_argument( + "--exchange", + default="deribit", + choices=["deribit", "bybit", "hyperliquid"], + ) + p.add_argument("--symbol", default="BTC-PERPETUAL") p.add_argument("--timeframe", default="1h") p.add_argument("--start", default="2024-01-01T00:00:00+00:00") p.add_argument("--end", default="2026-01-01T00:00:00+00:00") @@ -32,12 +38,24 @@ def main() -> None: args = parse_args() settings = load_settings() - loader = OHLCVLoader(cache_dir=settings.series_dir) + token = ( + settings.cerbero_mainnet_token.get_secret_value() + if settings.cerbero_mainnet_token + else settings.cerbero_testnet_token.get_secret_value() + ) + cerbero = CerberoClient( + base_url=settings.cerbero_base_url, + token=token, + bot_tag=settings.cerbero_bot_tag, + ) + + loader = CerberoOHLCVLoader(client=cerbero, cache_dir=settings.series_dir) req = OHLCVRequest( symbol=args.symbol, timeframe=args.timeframe, start=datetime.fromisoformat(args.start), end=datetime.fromisoformat(args.end), + exchange=args.exchange, ) ohlcv = loader.load(req) print(f"OHLCV loaded: {len(ohlcv)} bars from {ohlcv.index[0]} to {ohlcv.index[-1]}") diff --git a/src/multi_swarm/data/cerbero_ohlcv.py b/src/multi_swarm/data/cerbero_ohlcv.py new file mode 100644 index 0000000..83efdb7 --- /dev/null +++ b/src/multi_swarm/data/cerbero_ohlcv.py @@ -0,0 +1,162 @@ +"""OHLCV loader backed by Cerbero MCP (replaces ccxt in Phase 1). + +Cerbero is the single source of truth for market data; Phase 1 uses only +OHLCV. Default exchange = deribit (BTC-PERPETUAL / ETH-PERPETUAL). + +Cerbero get_historical request schemas (from OpenAPI at +``https://cerbero-mcp.tielogic.xyz/openapi.json``): + +- ``mcp-deribit/tools/get_historical``: required ``instrument``, + ``start_date``, ``end_date``; optional ``resolution`` (default ``1h``). +- ``mcp-bybit/tools/get_historical``: ``symbol`` + ``interval`` (minutes) + + range params (``start``/``end`` ms epoch). +- ``mcp-hyperliquid/tools/get_historical``: ``instrument`` (or ``asset``), + ``start_date``, ``end_date``, optional ``resolution``. + +Response shape is not statically guaranteed by the OpenAPI schema (200 +returns an opaque object). The parser is therefore defensive: it tries +the three plausible shapes (object-of-records under ``candles``/``data``/ +``result``/``ohlcv``/``klines``/``bars``, array-of-arrays ccxt-style, or +a raw list at the top level) and raises a clear error if none matches. + +Pagination is NOT yet implemented — Cerbero is assumed to accept the full +date range and page internally. If a future live call shows a cap (e.g. +~1000 candles per call), add a chunked fetch in a follow-up. +""" + +from __future__ import annotations + +import hashlib +from dataclasses import dataclass +from datetime import datetime +from pathlib import Path +from typing import Any, ClassVar + +import pandas as pd # type: ignore[import-untyped] + +from ..cerbero.client import CerberoClient + + +@dataclass(frozen=True) +class OHLCVRequest: + symbol: str # e.g. "BTC-PERPETUAL" for deribit, "BTCUSDT" for bybit + timeframe: str # e.g. "1h", "5m" + start: datetime + end: datetime + exchange: str = "deribit" + + def cache_key(self) -> str: + s = ( + f"{self.exchange}|{self.symbol}|{self.timeframe}|" + f"{self.start.isoformat()}|{self.end.isoformat()}" + ) + return hashlib.sha1(s.encode()).hexdigest()[:16] + + +class CerberoOHLCVLoader: + """Carica OHLCV chiamando Cerbero MCP get_historical, cachea in parquet.""" + + _COLUMNS: ClassVar[list[str]] = ["open", "high", "low", "close", "volume"] + + def __init__(self, client: CerberoClient, cache_dir: Path): + self.client = client + self.cache_dir = Path(cache_dir) + self.cache_dir.mkdir(parents=True, exist_ok=True) + + def load(self, req: OHLCVRequest) -> pd.DataFrame: + cache_file = self.cache_dir / f"{req.cache_key()}.parquet" + if cache_file.exists(): + df = pd.read_parquet(cache_file) + assert isinstance(df, pd.DataFrame) + return df + df = self._fetch(req) + df.to_parquet(cache_file) + return df + + def _fetch(self, req: OHLCVRequest) -> pd.DataFrame: + args = self._build_args(req) + response = self.client.call_tool(req.exchange, "get_historical", args) + return self._parse_response(response) + + def _build_args(self, req: OHLCVRequest) -> dict[str, Any]: + if req.exchange == "deribit": + return { + "instrument": req.symbol, + "start_date": req.start.isoformat(), + "end_date": req.end.isoformat(), + "resolution": req.timeframe, + } + if req.exchange == "bybit": + return { + "symbol": req.symbol, + "interval": _timeframe_to_minutes(req.timeframe), + "start": int(req.start.timestamp() * 1000), + "end": int(req.end.timestamp() * 1000), + } + if req.exchange == "hyperliquid": + return { + "instrument": req.symbol, + "start_date": req.start.isoformat(), + "end_date": req.end.isoformat(), + "resolution": req.timeframe, + } + raise ValueError(f"unsupported exchange: {req.exchange}") + + def _parse_response(self, response: Any) -> pd.DataFrame: + records = self._extract_records(response) + if not records: + empty = pd.DataFrame(columns=self._COLUMNS) + empty.index = pd.DatetimeIndex([], tz="UTC", name="ts") + return empty.astype("float64") + + first = records[0] + if isinstance(first, dict): + df = pd.DataFrame(records) + ts_col = self._guess_ts_col(df.columns) + df = df.rename(columns={ts_col: "ts"}) + elif isinstance(first, list | tuple) and len(first) >= 6: + df = pd.DataFrame( + records, columns=["ts", "open", "high", "low", "close", "volume"] + ) + else: + raise RuntimeError(f"unrecognized record shape: {first!r}") + + df["ts"] = self._to_utc_index(df["ts"]) + df = df.drop_duplicates(subset=["ts"]).sort_values("ts").set_index("ts") + keep = [c for c in self._COLUMNS if c in df.columns] + return df[keep].astype("float64") + + @staticmethod + def _extract_records(response: Any) -> list[Any]: + if isinstance(response, list): + return response + if isinstance(response, dict): + for key in ("candles", "data", "result", "ohlcv", "klines", "bars"): + if key in response and isinstance(response[key], list): + return list(response[key]) + raise RuntimeError( + f"cannot find records list in response: {type(response).__name__}" + ) + + @staticmethod + def _guess_ts_col(columns: pd.Index) -> str: + for cand in ("ts", "timestamp", "time", "date", "datetime", "open_time", "t"): + if cand in columns: + return cand + raise RuntimeError(f"no timestamp column in {list(columns)}") + + @staticmethod + def _to_utc_index(s: pd.Series) -> pd.Series: + # Accepts ms-epoch ints, sec-epoch ints, ISO strings. + if pd.api.types.is_numeric_dtype(s): + mx = float(s.max()) + unit = "ms" if mx > 1e12 else "s" + return pd.to_datetime(s, unit=unit, utc=True) + return pd.to_datetime(s, utc=True) + + +def _timeframe_to_minutes(tf: str) -> int: + units = {"m": 1, "h": 60, "d": 60 * 24} + if not tf or tf[-1] not in units: + raise ValueError(f"unsupported timeframe: {tf}") + return int(tf[:-1]) * units[tf[-1]] diff --git a/src/multi_swarm/data/ohlcv_loader.py b/src/multi_swarm/data/ohlcv_loader.py deleted file mode 100644 index c6c084a..0000000 --- a/src/multi_swarm/data/ohlcv_loader.py +++ /dev/null @@ -1,75 +0,0 @@ -from __future__ import annotations - -import hashlib -from dataclasses import dataclass -from datetime import datetime -from pathlib import Path - -import ccxt # type: ignore[import-untyped] -import pandas as pd # type: ignore[import-untyped] - - -@dataclass(frozen=True) -class OHLCVRequest: - symbol: str - timeframe: str - start: datetime - end: datetime - - def cache_key(self) -> str: - s = f"{self.symbol}|{self.timeframe}|{self.start.isoformat()}|{self.end.isoformat()}" - return hashlib.sha1(s.encode()).hexdigest()[:16] - - -class OHLCVLoader: - """Carica OHLCV via ccxt (Binance) e cachea in parquet.""" - - def __init__(self, cache_dir: Path, exchange_name: str = "binance"): - self.cache_dir = Path(cache_dir) - self.cache_dir.mkdir(parents=True, exist_ok=True) - self.exchange_name = exchange_name - - def load(self, req: OHLCVRequest) -> pd.DataFrame: - cache_file = self.cache_dir / f"{req.cache_key()}.parquet" - if cache_file.exists(): - return pd.read_parquet(cache_file) - - df = self._fetch_paginated(req) - df.to_parquet(cache_file) - return df - - @staticmethod - def _timeframe_to_ms(timeframe: str) -> int: - units = {"m": 60, "h": 3600, "d": 86400, "w": 604800} - unit = timeframe[-1] - if unit not in units: - raise ValueError(f"Unsupported timeframe: {timeframe}") - return int(timeframe[:-1]) * units[unit] * 1000 - - def _fetch_paginated(self, req: OHLCVRequest) -> pd.DataFrame: - exchange = getattr(ccxt, self.exchange_name)({"enableRateLimit": True}) - timeframe_ms = self._timeframe_to_ms(req.timeframe) - since = int(req.start.timestamp() * 1000) - end_ms = int(req.end.timestamp() * 1000) - all_rows: list[list[float]] = [] - limit = 1000 - - while since <= end_ms: - rows = exchange.fetch_ohlcv(req.symbol, req.timeframe, since=since, limit=limit) - if not rows: - break - all_rows.extend(rows) - if len(rows) < limit: - break - last_ts = rows[-1][0] - new_since = last_ts + timeframe_ms - if new_since <= since: - break - since = new_since - - df = pd.DataFrame(all_rows, columns=["ts", "open", "high", "low", "close", "volume"]) - df = df.drop_duplicates(subset=["ts"]).sort_values("ts") - df["ts"] = pd.to_datetime(df["ts"], unit="ms", utc=True) - df = df.set_index("ts") - df = df[(df.index >= req.start) & (df.index < req.end)] - return df[["open", "high", "low", "close", "volume"]].astype("float64") diff --git a/tests/unit/test_cerbero_ohlcv.py b/tests/unit/test_cerbero_ohlcv.py new file mode 100644 index 0000000..81ecf19 --- /dev/null +++ b/tests/unit/test_cerbero_ohlcv.py @@ -0,0 +1,140 @@ +"""Tests for CerberoOHLCVLoader (mocked CerberoClient).""" + +from datetime import UTC, datetime +from pathlib import Path + +import pandas as pd +import pytest + +from multi_swarm.data.cerbero_ohlcv import CerberoOHLCVLoader, OHLCVRequest + + +@pytest.fixture +def sample_records_object() -> list[dict[str, float | int]]: + base = int(datetime(2024, 1, 1, tzinfo=UTC).timestamp() * 1000) + return [ + { + "ts": base + i * 3600 * 1000, + "open": 40000 + i, + "high": 40100 + i, + "low": 39900 + i, + "close": 40050 + i, + "volume": 100.0 + i, + } + for i in range(48) + ] + + +@pytest.fixture +def sample_records_array() -> list[list[float | int]]: + base = int(datetime(2024, 1, 1, tzinfo=UTC).timestamp() * 1000) + return [ + [base + i * 3600 * 1000, 40000 + i, 40100 + i, 39900 + i, 40050 + i, 100.0 + i] + for i in range(48) + ] + + +def test_loader_parses_object_records( + tmp_path: Path, mocker, sample_records_object +) -> None: + fake_client = mocker.MagicMock() + fake_client.call_tool.return_value = {"candles": sample_records_object} + + loader = CerberoOHLCVLoader(client=fake_client, cache_dir=tmp_path) + df = loader.load( + OHLCVRequest( + symbol="BTC-PERPETUAL", + timeframe="1h", + start=datetime(2024, 1, 1, tzinfo=UTC), + end=datetime(2024, 1, 3, tzinfo=UTC), + exchange="deribit", + ) + ) + + assert list(df.columns) == ["open", "high", "low", "close", "volume"] + assert len(df) == 48 + assert df.index.tz is not None + fake_client.call_tool.assert_called_once_with( + "deribit", + "get_historical", + { + "instrument": "BTC-PERPETUAL", + "start_date": "2024-01-01T00:00:00+00:00", + "end_date": "2024-01-03T00:00:00+00:00", + "resolution": "1h", + }, + ) + + +def test_loader_parses_array_records( + tmp_path: Path, mocker, sample_records_array +) -> None: + fake_client = mocker.MagicMock() + fake_client.call_tool.return_value = {"candles": sample_records_array} + + loader = CerberoOHLCVLoader(client=fake_client, cache_dir=tmp_path) + df = loader.load( + OHLCVRequest( + symbol="BTC-PERPETUAL", + timeframe="1h", + start=datetime(2024, 1, 1, tzinfo=UTC), + end=datetime(2024, 1, 3, tzinfo=UTC), + ) + ) + assert len(df) == 48 + + +def test_loader_uses_cache_on_second_call( + tmp_path: Path, mocker, sample_records_object +) -> None: + fake_client = mocker.MagicMock() + fake_client.call_tool.return_value = {"candles": sample_records_object} + + loader = CerberoOHLCVLoader(client=fake_client, cache_dir=tmp_path) + req = OHLCVRequest( + symbol="BTC-PERPETUAL", + timeframe="1h", + start=datetime(2024, 1, 1, tzinfo=UTC), + end=datetime(2024, 1, 3, tzinfo=UTC), + ) + df1 = loader.load(req) + fake_client.call_tool.reset_mock() + df2 = loader.load(req) + assert fake_client.call_tool.call_count == 0 + pd.testing.assert_frame_equal(df1, df2) + + +def test_loader_unsupported_exchange_raises(tmp_path: Path, mocker) -> None: + fake_client = mocker.MagicMock() + loader = CerberoOHLCVLoader(client=fake_client, cache_dir=tmp_path) + req = OHLCVRequest( + symbol="X", + timeframe="1h", + start=datetime(2024, 1, 1, tzinfo=UTC), + end=datetime(2024, 1, 2, tzinfo=UTC), + exchange="kraken", + ) + with pytest.raises(ValueError, match="unsupported exchange"): + loader.load(req) + + +def test_loader_bybit_args(tmp_path: Path, mocker, sample_records_object) -> None: + fake_client = mocker.MagicMock() + fake_client.call_tool.return_value = {"candles": sample_records_object} + + loader = CerberoOHLCVLoader(client=fake_client, cache_dir=tmp_path) + loader.load( + OHLCVRequest( + symbol="BTCUSDT", + timeframe="1h", + start=datetime(2024, 1, 1, tzinfo=UTC), + end=datetime(2024, 1, 3, tzinfo=UTC), + exchange="bybit", + ) + ) + args = fake_client.call_tool.call_args.args + assert args[0] == "bybit" + assert args[1] == "get_historical" + payload = args[2] + assert payload["symbol"] == "BTCUSDT" + assert payload["interval"] == 60 diff --git a/tests/unit/test_ohlcv_loader.py b/tests/unit/test_ohlcv_loader.py deleted file mode 100644 index 4a80425..0000000 --- a/tests/unit/test_ohlcv_loader.py +++ /dev/null @@ -1,64 +0,0 @@ -from datetime import UTC, datetime -from pathlib import Path - -import pandas as pd -import pytest - -from multi_swarm.data.ohlcv_loader import OHLCVLoader, OHLCVRequest - - -@pytest.fixture -def sample_ohlcv_rows(): - base_ts = int(datetime(2024, 1, 1, tzinfo=UTC).timestamp() * 1000) - rows = [] - for i in range(48): - rows.append( - [base_ts + i * 3600 * 1000, 40000 + i, 40100 + i, 39900 + i, 40050 + i, 100.0 + i] - ) - return rows - - -def test_loader_fetches_and_caches(tmp_path: Path, mocker, sample_ohlcv_rows): - fake_exchange = mocker.MagicMock() - fake_exchange.fetch_ohlcv.return_value = sample_ohlcv_rows - mocker.patch("multi_swarm.data.ohlcv_loader.ccxt.binance", return_value=fake_exchange) - - loader = OHLCVLoader(cache_dir=tmp_path) - req = OHLCVRequest( - symbol="BTC/USDT", - timeframe="1h", - start=datetime(2024, 1, 1, tzinfo=UTC), - end=datetime(2024, 1, 3, tzinfo=UTC), - ) - df = loader.load(req) - - assert isinstance(df, pd.DataFrame) - assert list(df.columns) == ["open", "high", "low", "close", "volume"] - assert len(df) == 48 - assert df.index.is_monotonic_increasing - cache_files = list(tmp_path.glob("*.parquet")) - assert len(cache_files) == 1 - - -def test_loader_uses_cache_on_second_call(tmp_path: Path, mocker, sample_ohlcv_rows): - fake_exchange = mocker.MagicMock() - fake_exchange.fetch_ohlcv.return_value = sample_ohlcv_rows - mocker.patch("multi_swarm.data.ohlcv_loader.ccxt.binance", return_value=fake_exchange) - - loader = OHLCVLoader(cache_dir=tmp_path) - req = OHLCVRequest( - symbol="BTC/USDT", - timeframe="1h", - start=datetime(2024, 1, 1, tzinfo=UTC), - end=datetime(2024, 1, 3, tzinfo=UTC), - ) - df1 = loader.load(req) - df2 = loader.load(req) - - assert fake_exchange.fetch_ohlcv.call_count == 1 # 48 < limit, single batch - pd.testing.assert_frame_equal(df1, df2) - # Seconda chiamata legge da cache, non chiama exchange - fake_exchange.fetch_ohlcv.reset_mock() - df3 = loader.load(req) - assert fake_exchange.fetch_ohlcv.call_count == 0 - pd.testing.assert_frame_equal(df1, df3) diff --git a/uv.lock b/uv.lock index 4d0d537..1a1306f 100644 --- a/uv.lock +++ b/uv.lock @@ -13,107 +13,6 @@ resolution-markers = [ "python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'", ] -[[package]] -name = "aiodns" -version = "4.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - 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