chore: 移除不再使用的 ChanMacro、system、tests。
这些目录已废弃，从仓库中清理。 Co-authored-by: Cursor <cursoragent@cursor.com>
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jackyu66git
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"""
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fetchers/ohlcv.py — Fetches BTC daily OHLCV from the existing data_provider service.
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Also pre-computes EMA20/60/120, ATR(14), BB width, ADX(14).
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"""
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from datetime import date as Date, datetime, timedelta
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from typing import Optional
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import logging
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import pandas as pd
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import numpy as np
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import requests
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from .base import BaseFetcher
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from config import config
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class OHLCVFetcher(BaseFetcher):
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"""Fetches BTC daily K-line data from data_provider API."""
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def __init__(self, provider_url: Optional[str] = None):
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super().__init__(timeout=30, max_retries=3)
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self.provider_url = provider_url or config.provider_url
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self.symbol = config.btc_symbol
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self.logger = logging.getLogger(__name__)
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def fetch(self, target_date: Optional[Date] = None) -> pd.DataFrame:
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"""
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Fetch daily OHLCV for BTC. Returns DataFrame with computed indicators.
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Fetches enough history (200 bars) to compute EMAs/ATR/BB/ADX accurately.
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"""
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url = f"{self.provider_url}/api/candles"
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params = {
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"symbol": self.symbol,
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"tf": "1d",
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"limit": 200,
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}
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resp = requests.get(url, params=params, timeout=self.timeout)
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resp.raise_for_status()
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data = resp.json()
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if not data:
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self.logger.warning("OHLCV API returned empty data")
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return pd.DataFrame()
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df = pd.DataFrame(data)
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df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms", utc=True)
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df["date"] = df["timestamp"].dt.date
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df = df.drop_duplicates(subset="date").sort_values("date").reset_index(drop=True)
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# Rename columns to match expected format
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df = df.rename(columns={
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"open": "open", "high": "high", "low": "low", "close": "close",
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"volume": "volume",
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})
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# Compute indicators
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df = self._add_indicators(df)
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return df
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def _add_indicators(self, df: pd.DataFrame) -> pd.DataFrame:
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"""Add EMA, ATR, BB, ADX indicators."""
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close = df["close"].astype(float)
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high = df["high"].astype(float)
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low = df["low"].astype(float)
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# EMAs
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df["ema20"] = close.ewm(span=20, adjust=False).mean()
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df["ema60"] = close.ewm(span=60, adjust=False).mean()
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df["ema120"] = close.ewm(span=120, adjust=False).mean()
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# ATR(14)
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tr1 = high - low
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tr2 = (high - close.shift(1)).abs()
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tr3 = (low - close.shift(1)).abs()
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tr = pd.concat([tr1, tr2, tr3], axis=1).max(axis=1)
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df["atr_14"] = tr.rolling(14).mean()
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# Bollinger Bands width
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sma20 = close.rolling(20).mean()
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std20 = close.rolling(20).std()
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df["bb_width"] = (2 * std20) / sma20 * 100 # as percentage
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# ADX(14)
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df["adx_14"] = self._compute_adx(df, period=14)
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return df
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@staticmethod
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def _compute_adx(df: pd.DataFrame, period: int = 14) -> pd.Series:
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"""Compute ADX from OHLC data."""
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high = df["high"].astype(float)
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low = df["low"].astype(float)
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close = df["close"].astype(float)
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plus_dm = high.diff()
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minus_dm = low.diff().abs() * -1
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plus_dm = plus_dm.where(plus_dm > 0, 0)
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minus_dm = minus_dm.where(minus_dm < 0, 0).abs()
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tr1 = high - low
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tr2 = (high - close.shift(1)).abs()
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tr3 = (low - close.shift(1)).abs()
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tr = pd.concat([tr1, tr2, tr3], axis=1).max(axis=1)
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atr = tr.rolling(period).mean()
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plus_di = 100 * (plus_dm.rolling(period).mean() / atr)
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minus_di = 100 * (minus_dm.rolling(period).mean() / atr)
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dx = (abs(plus_di - minus_di) / (plus_di + minus_di)) * 100
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adx = dx.rolling(period).mean()
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return adx
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def store(self, db_path: str, records: list[dict]) -> int:
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"""Store OHLCV records into SQLite. Not used directly — see store_df."""
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return 0
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def store_df(self, df: pd.DataFrame, db_path: Optional[str] = None) -> int:
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"""Store the DataFrame into the ohlcv_daily table."""
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import sqlite3
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db_path = db_path or config.db_path
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conn = sqlite3.connect(db_path)
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count = 0
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for _, row in df.iterrows():
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if pd.isna(row.get("date")):
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continue
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date_str = str(row["date"])
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try:
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conn.execute("""
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INSERT OR REPLACE INTO ohlcv_daily
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(date, symbol, open, high, low, close, volume,
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ema20, ema60, ema120, atr_14, bb_width, adx_14)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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""", (
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date_str, self.symbol,
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float(row["open"]), float(row["high"]),
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float(row["low"]), float(row["close"]),
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float(row.get("volume", 0)),
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float(row["ema20"]) if not pd.isna(row.get("ema20")) else None,
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float(row["ema60"]) if not pd.isna(row.get("ema60")) else None,
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float(row["ema120"]) if not pd.isna(row.get("ema120")) else None,
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float(row["atr_14"]) if not pd.isna(row.get("atr_14")) else None,
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float(row["bb_width"]) if not pd.isna(row.get("bb_width")) else None,
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float(row["adx_14"]) if not pd.isna(row.get("adx_14")) else None,
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))
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count += 1
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except Exception as e:
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self.logger.debug(f"Skip row {date_str}: {e}")
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conn.commit()
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conn.close()
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self.logger.info(f"Stored {count} OHLCV rows")
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return count
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