mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-01 01:27:42 +00:00
chore: Remove unused scripts
- Removed apply_config.py (not used, .env is manual) - Removed start_trading.sh (too complex, interactive prompts) - Removed setup_predix_eurusd.sh (one-time setup, already done) Kept: - data_config.yaml (central configuration, German comments OK) - start_loop.sh (useful for 24/7 trading) Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
This commit is contained in:
TPTBusiness
@@ -1,91 +0,0 @@
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#!/usr/bin/env python3
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"""
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Liest data_config.yaml und schreibt alle Werte in:
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- .env (Zeiträume, Pfade)
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- generate.py (Qlib Datengenerierung)
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"""
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import yaml
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import re
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from pathlib import Path
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CONFIG = Path(__file__).parent / "data_config.yaml"
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ENV = Path(__file__).parent / ".env"
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GENERATE = Path("/home/nico/miniconda3/envs/rdagent/lib/python3.10/site-packages/rdagent/scenarios/qlib/experiment/factor_data_template/generate.py")
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with open(CONFIG) as f:
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cfg = yaml.safe_load(f)
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# --- .env updaten ---
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env_text = ENV.read_text()
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replacements = {
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r"QLIB_DATA_DIR=.*": f"QLIB_DATA_DIR={cfg['data_path'].replace('~', str(Path.home()))}",
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r"QLIB_FREQ=.*": f"QLIB_FREQ={cfg['frequency']}",
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r"QLIB_FACTOR_TRAIN_START=.*": f"QLIB_FACTOR_TRAIN_START={cfg['train_start']}",
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r"QLIB_FACTOR_TRAIN_END=.*": f"QLIB_FACTOR_TRAIN_END={cfg['train_end']}",
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r"QLIB_FACTOR_VALID_START=.*": f"QLIB_FACTOR_VALID_START={cfg['valid_start']}",
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r"QLIB_FACTOR_VALID_END=.*": f"QLIB_FACTOR_VALID_END={cfg['valid_end']}",
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r"QLIB_FACTOR_TEST_START=.*": f"QLIB_FACTOR_TEST_START={cfg['test_start']}",
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r"QLIB_FACTOR_TEST_END=.*": f"QLIB_FACTOR_TEST_END={cfg['test_end']}",
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r"QLIB_MODEL_TRAIN_START=.*": f"QLIB_MODEL_TRAIN_START={cfg['train_start']}",
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r"QLIB_MODEL_TRAIN_END=.*": f"QLIB_MODEL_TRAIN_END={cfg['train_end']}",
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r"QLIB_MODEL_VALID_START=.*": f"QLIB_MODEL_VALID_START={cfg['valid_start']}",
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r"QLIB_MODEL_VALID_END=.*": f"QLIB_MODEL_VALID_END={cfg['valid_end']}",
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r"QLIB_MODEL_TEST_START=.*": f"QLIB_MODEL_TEST_START={cfg['test_start']}",
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r"QLIB_MODEL_TEST_END=.*": f"QLIB_MODEL_TEST_END={cfg['test_end']}",
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r"QLIB_QUANT_TRAIN_START=.*": f"QLIB_QUANT_TRAIN_START={cfg['train_start']}",
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r"QLIB_QUANT_TRAIN_END=.*": f"QLIB_QUANT_TRAIN_END={cfg['train_end']}",
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r"QLIB_QUANT_VALID_START=.*": f"QLIB_QUANT_VALID_START={cfg['valid_start']}",
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r"QLIB_QUANT_VALID_END=.*": f"QLIB_QUANT_VALID_END={cfg['valid_end']}",
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r"QLIB_QUANT_TEST_START=.*": f"QLIB_QUANT_TEST_START={cfg['test_start']}",
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r"QLIB_QUANT_TEST_END=.*": f"QLIB_QUANT_TEST_END={cfg['test_end']}",
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}
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for pattern, replacement in replacements.items():
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env_text = re.sub(pattern, replacement, env_text)
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ENV.write_text(env_text)
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print("✓ .env aktualisiert")
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# --- generate.py updaten ---
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data_path = cfg['data_path']
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freq = cfg['frequency']
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train_start = cfg['train_start']
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test_end = cfg['test_end']
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valid_start = cfg['valid_start']
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cols = str(cfg['columns'])
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generate_text = f'''import qlib
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import pandas as pd
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qlib.init(provider_uri="{data_path}", freq="{freq}")
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from qlib.data import D
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instruments = D.instruments(market="all")
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fields = {cols}
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data = (
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D.features(instruments, fields, freq="{freq}")
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.swaplevel()
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.sort_index()
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.loc["{train_start}":]
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.sort_index()
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)
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data.to_hdf("./daily_pv_all.h5", key="data")
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data_debug = (
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D.features(instruments, fields, start_time="{valid_start}", end_time="{test_end}", freq="{freq}")
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.swaplevel()
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.sort_index()
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)
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data_debug.to_hdf("./daily_pv_debug.h5", key="data")
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'''
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GENERATE.write_text(generate_text)
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print("✓ generate.py aktualisiert")
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print(f"\nKonfiguration angewendet:")
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print(f" Instrument: {cfg['instrument']}")
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print(f" Frequenz: {cfg['frequency']}")
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print(f" Train: {cfg['train_start']} → {cfg['train_end']}")
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print(f" Test: {cfg['test_start']} → {cfg['test_end']}")
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@@ -1,301 +0,0 @@
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#!/bin/bash
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# =============================================================================
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# setup_predix_eurusd.sh
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# Sets up Predix for EURUSD 15min trading
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# Usage: bash setup_predix_eurusd.sh
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# =============================================================================
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set -e # Exit on error
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PREDIX_DIR="$HOME/Predix"
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CSV_SOURCE="$HOME/Downloads/eurusd_data.csv"
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DATA_DIR="$PREDIX_DIR/git_ignore_folder/eurusd_data"
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QLIB_DIR="$HOME/.qlib/qlib_data/eurusd_data"
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echo "========================================"
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echo " Predix EURUSD Setup"
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echo "========================================"
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# ─── 1. Check prerequisites ───────────────────────────────────────────────
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echo ""
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echo "[1/7] Checking prerequisites..."
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if [ ! -d "$PREDIX_DIR" ]; then
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echo "ERROR: $PREDIX_DIR not found!"
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exit 1
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fi
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if [ ! -f "$CSV_SOURCE" ]; then
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echo "ERROR: $CSV_SOURCE not found!"
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echo "Please place eurusd_data.csv in ~/Downloads/"
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exit 1
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fi
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echo "✓ Predix found: $PREDIX_DIR"
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echo "✓ CSV found: $CSV_SOURCE"
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# ─── 2. Create directory structure ─────────────────────────────────────────
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echo ""
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echo "[2/7] Creating directory structure..."
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mkdir -p "$DATA_DIR"
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mkdir -p "$QLIB_DIR/calendars"
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mkdir -p "$QLIB_DIR/instruments"
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mkdir -p "$QLIB_DIR/features/eurusd"
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mkdir -p "$PREDIX_DIR/git_ignore_folder/log"
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cp "$CSV_SOURCE" "$DATA_DIR/eurusd_data.csv"
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echo "✓ CSV copied to $DATA_DIR"
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# ─── 3. Convert CSV to Qlib format ─────────────────────────────────────────
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echo ""
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echo "[3/7] Converting CSV to Qlib format..."
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python3 << 'PYEOF'
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import pandas as pd
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import numpy as np
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from pathlib import Path
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import os
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QLIB_DIR = Path(os.path.expanduser("~/.qlib/qlib_data/eurusd_data"))
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CSV_PATH = Path(os.path.expanduser("~/Downloads/eurusd_data.csv"))
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# Load + sort
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df = pd.read_csv(CSV_PATH, parse_dates=["datetime"])
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df = df.sort_values("datetime").reset_index(drop=True)
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df.columns = [c.lower() for c in df.columns]
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print(f" Rows: {len(df):,} | Range: {df['datetime'].min().date()} -> {df['datetime'].max().date()}")
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# ── Calendar (all 15min timestamps) ────────────────────────────────────────
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cal = df["datetime"].dt.strftime("%Y-%m-%d %H:%M:%S")
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cal_path = QLIB_DIR / "calendars" / "15min.txt"
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cal.to_csv(cal_path, index=False, header=False)
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print(f" ✓ Calendar: {len(cal)} entries -> {cal_path}")
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# ── Instruments (only EURUSD) ──────────────────────────────────────────────
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inst_path = QLIB_DIR / "instruments" / "all.txt"
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start = df["datetime"].min().strftime("%Y-%m-%d")
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end = df["datetime"].max().strftime("%Y-%m-%d")
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with open(inst_path, "w") as f:
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f.write(f"EURUSD\t{start}\t{end}\n")
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print(f" ✓ Instruments -> {inst_path}")
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# ── Features (Qlib binary format via CSV) ──────────────────────────────────
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feat_dir = QLIB_DIR / "features" / "eurusd"
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feat_dir.mkdir(parents=True, exist_ok=True)
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# Qlib expects: $open, $high, $low, $close, $volume
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for col in ["open", "high", "low", "close", "volume"]:
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out = feat_dir / f"{col}.day.bin"
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# Qlib binary: float32 array
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arr = df[col].astype("float32").values
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arr.tofile(str(out).replace(".day.bin", f"_15min.bin"))
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# Also as simple CSV for direct access
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df.to_csv(QLIB_DIR / "eurusd_15min.csv", index=False)
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print(f" ✓ Features + CSV -> {feat_dir}")
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# ── Returns + technical features precomputation ────────────────────────────
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def ema(s, p): return s.ewm(span=p, adjust=False).mean()
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def rsi(c, p=14):
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d = c.diff()
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g = d.clip(lower=0).ewm(span=p, adjust=False).mean()
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l = (-d.clip(upper=0)).ewm(span=p, adjust=False).mean()
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return 100 - 100/(1 + g/(l+1e-9))
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feat = pd.DataFrame()
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feat["datetime"] = df["datetime"]
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feat["close"] = df["close"]
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for n in [1,4,8,16,96]:
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feat[f"ret_{n}"] = df["close"].pct_change(n)
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feat["rsi_14"] = rsi(df["close"], 14)
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feat["macd_hist"] = ema(df["close"],12) - ema(df["close"],26)
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feat["hour"] = df["datetime"].dt.hour
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feat["is_london"] = feat["hour"].isin([8,9,10,11]).astype(int)
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feat["is_ny"] = feat["hour"].isin([13,14,15,16]).astype(int)
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feat["adx_proxy"] = df["close"].rolling(14).std() / df["close"].rolling(96).std()
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feat.dropna(inplace=True)
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feat.to_csv(QLIB_DIR / "eurusd_features.csv", index=False)
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print(f" ✓ Features CSV: {len(feat):,} rows, {len(feat.columns)} columns")
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print(" Done!")
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PYEOF
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echo "✓ Qlib data converted"
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# ─── 4. Update .env ────────────────────────────────────────────────────────
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echo ""
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echo "[4/7] Updating .env..."
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ENV_FILE="$PREDIX_DIR/.env"
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# Backup
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cp "$ENV_FILE" "$ENV_FILE.backup_$(date +%Y%m%d_%H%M%S)"
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# Update QLIB_DATA_DIR to EURUSD
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sed -i "s|QLIB_DATA_DIR=.*|QLIB_DATA_DIR=$QLIB_DIR|" "$ENV_FILE"
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# Fix LOG_PATH (was /home/nico/RD-Agent-Local/log)
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sed -i "s|LOG_PATH=.*|LOG_PATH=$PREDIX_DIR/git_ignore_folder/log|" "$ENV_FILE"
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# Add EURUSD-specific vars (if not already present)
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grep -q "EURUSD_DATA_PATH" "$ENV_FILE" || cat >> "$ENV_FILE" << 'ENVEOF'
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# ---------- EURUSD ----------
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EURUSD_DATA_PATH=/home/nico/.qlib/qlib_data/eurusd_data/eurusd_15min.csv
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QLIB_FREQ=15min
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QLIB_MARKET=eurusd
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BACKTEST_START_TIME=2024-08-09
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BACKTEST_END_TIME=2026-03-20
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COST_RATE=0.00015
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ENVEOF
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echo "✓ .env updated (backup created)"
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# ─── 5. Adjust prompts for EURUSD ──────────────────────────────────────────
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echo ""
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echo "[5/7] Adjusting Qlib prompts for EURUSD..."
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PROMPT_FILE="$PREDIX_DIR/rdagent/app/qlib_rd_loop/prompts.yaml"
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cp "$PROMPT_FILE" "${PROMPT_FILE}.backup_$(date +%Y%m%d_%H%M%S)"
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cat > "$PROMPT_FILE" << 'YAMLEOF'
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hypothesis_generation:
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system: |-
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You are an expert quantitative researcher specialized in FX (foreign exchange) trading,
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specifically EURUSD intraday strategies on 15-minute bars.
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EURUSD domain knowledge you must apply:
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- London session (08:00-12:00 UTC): highest volatility, trending behavior — favor momentum strategies
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- NY session (13:00-17:00 UTC): second volatility peak, also trending
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- Asian session (00:00-07:00 UTC): low volatility, mean-reverting behavior
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- London/NY overlap (13:00-17:00 UTC): strongest directional moves of the day
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- Weekend gap risk: avoid holding positions after Friday 20:00 UTC
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- Spread cost: ~1.5 bps per trade — strategies must minimize unnecessary entries
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- EURUSD is mean-reverting on short windows (<1h), trending on longer (>4h)
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- Key macro drivers: ECB/Fed rate decisions, NFP (first Friday of month), CPI releases
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Available model types you can propose:
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- TimeSeries: LSTM, GRU, TCN (Temporal Convolutional Network), Transformer, PatchTST
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- Tabular: XGBoost, LightGBM, RandomForest (on engineered features)
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- Hybrid: CNN+LSTM, XGBoost+LSTM ensemble
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- Statistical: Regime-switching (HMM), Kalman filter
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Available features in the dataset:
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- OHLCV: open, high, low, close, volume (15min bars)
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- Returns: ret_1, ret_4, ret_8, ret_16, ret_96
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- Technical: rsi_14, macd_hist, adx_14, atr_14, bb_pct, stoch_k, cci_14
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- Volatility: vol_real_4, vol_real_16, vol_ratio, zscore_ret_96
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- Time/Session: hour, is_london, is_ny, is_overlap, hour_sin, hour_cos
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- Lags: rsi_14_lag1-8, macd_hist_lag1-8, bb_pct_lag1-8
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Your hypothesis must:
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1. Specify which session(s) the strategy targets
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2. Name which model type to use and why it fits EURUSD
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3. Include a session filter (is_london / is_ny)
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4. Include a spread filter (only trade when expected |return| > 0.0003)
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5. Specify target: classification (fwd_sign_4) or regression (fwd_ret_4)
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Please ensure your response is in JSON format:
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{
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"hypothesis": "A clear and concise trading hypothesis for EURUSD 15min.",
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"reason": "Detailed explanation including session, model choice, and expected edge.",
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"model_type": "One of: TimeSeries / Tabular / XGBoost",
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"target_session": "london / ny / asian / all",
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"expected_arr_range": "e.g. 8-12%"
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}
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user: |-
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Previously tried approaches and their results:
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{{ factor_descriptions }}
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Additional context:
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{{ report_content }}
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Generate a NEW hypothesis that is meaningfully different from what has been tried.
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Focus on approaches that have NOT been tested yet.
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Target: beat current best ARR of 9.62%.
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YAMLEOF
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echo "✓ prompts.yaml updated (backup created)"
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# ─── 6. Extend Model Coder Prompt ──────────────────────────────────────────
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echo ""
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echo "[6/7] Extending Model Coder prompts..."
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MODEL_PROMPT="$PREDIX_DIR/rdagent/components/coder/model_coder/prompts.yaml"
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cp "$MODEL_PROMPT" "${MODEL_PROMPT}.backup_$(date +%Y%m%d_%H%M%S)"
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# Inject EURUSD session filter as comment in evolving_strategy block
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python3 << 'PYEOF'
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import re
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from pathlib import Path
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path = Path("/home/nico/Predix/rdagent/components/coder/model_coder/prompts.yaml")
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content = path.read_text()
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eurusd_note = """
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EURUSD-specific rules (ALWAYS apply these in generated code):
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1. Session filter: use is_london and is_ny columns — weight/filter signals to active sessions
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2. Spread filter: only generate signal when abs(predicted_return) > 0.0003
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3. ADX regime: if adx_proxy > 1.2 use trend model; if adx_proxy < 0.8 use mean-reversion
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4. Weekend filter: zero out signals when dayofweek==4 and hour>=20
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5. Max trade frequency: target <15 trades per day (avoid spread cost death)
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6. Supported model_type values: "Tabular", "TimeSeries", "XGBoost"
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"""
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# Inject after the scenario line in evolving_strategy_model_coder
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content = content.replace(
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" Your code is expected to align the scenario in any form",
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eurusd_note + "\n Your code is expected to align the scenario in any form"
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)
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path.write_text(content)
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print(" ✓ Model coder prompt extended")
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PYEOF
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echo "✓ Model coder prompt adjusted"
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# ─── 7. Git Commits ────────────────────────────────────────────────────────
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echo ""
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echo "[7/7] Git Commits..."
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cd "$PREDIX_DIR"
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git add rdagent/app/qlib_rd_loop/prompts.yaml
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git commit -m "feat: EURUSD 15min prompts - session filter, FX domain knowledge
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- Add London/NY/Asian session awareness to hypothesis generation
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- Add model type suggestions: LSTM, GRU, TCN, Transformer, XGBoost, LightGBM
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- Add spread filter (1.5 bps) and ADX regime detection
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- Target: beat current best ARR of 9.62%"
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git add rdagent/components/coder/model_coder/prompts.yaml
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git commit -m "feat: inject EURUSD trading rules into model coder
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- Session filter (is_london, is_ny)
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- Spread filter (|return| > 0.0003)
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- Weekend position close
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- Max trade frequency guidance"
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git add .env 2>/dev/null || true
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echo " (Note: .env not committed - contains API keys)"
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echo ""
|
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echo "========================================"
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echo " Setup completed!"
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echo "========================================"
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echo ""
|
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echo "Next steps:"
|
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echo ""
|
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echo " 1. Start:"
|
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echo " cd ~/Predix && rdagent fin_quant"
|
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echo ""
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echo " 2. Dashboard (in second terminal):"
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echo " cd ~/Predix && rdagent server_ui --port 19899"
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echo " → http://localhost:19899"
|
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echo ""
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echo " 3. Logs:"
|
||||
echo " tail -f $PREDIX_DIR/git_ignore_folder/log/*.log"
|
||||
echo ""
|
||||
echo "Backup files (.backup_*) can be deleted after successful testing."
|
||||
@@ -1,73 +0,0 @@
|
||||
#!/bin/bash
|
||||
# Start EURUSD Trading mit automatischem Dashboard
|
||||
# Verwendung: ./start_trading.sh
|
||||
|
||||
set -e
|
||||
|
||||
echo "============================================================"
|
||||
echo " Predix EURUSD Trading - Start mit Dashboard"
|
||||
echo "============================================================"
|
||||
echo ""
|
||||
|
||||
# Conda Environment aktivieren
|
||||
if [ -f ~/miniconda3/etc/profile.d/conda.sh ]; then
|
||||
source ~/miniconda3/etc/profile.d/conda.sh
|
||||
conda activate rdagent
|
||||
echo "✓ Conda Environment 'rdagent' aktiviert"
|
||||
else
|
||||
echo "⚠️ Conda nicht gefunden, versuche mit system Python..."
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo "Verwendung:"
|
||||
echo " Option 1: Web Dashboard (empfohlen)"
|
||||
echo " rdagent fin_quant --with-dashboard"
|
||||
echo ""
|
||||
echo " Option 2: CLI Dashboard (Terminal UI)"
|
||||
echo " rdagent fin_quant --cli-dashboard"
|
||||
echo ""
|
||||
echo " Option 3: Beide Dashboards"
|
||||
echo " rdagent fin_quant -d -c"
|
||||
echo ""
|
||||
echo " Option 4: Endlosschleife mit Auto-Restart"
|
||||
echo " ./start_loop.sh"
|
||||
echo ""
|
||||
echo "============================================================"
|
||||
|
||||
# Dashboard API im Hintergrund starten (optional)
|
||||
read -p "Dashboard im Hintergrund starten? (y/n): " -n 1 -r
|
||||
echo
|
||||
if [[ $REPLY =~ ^[Yy]$ ]]; then
|
||||
echo ""
|
||||
echo "🚀 Starte Dashboard API..."
|
||||
cd /home/nico/Predix
|
||||
nohup python web/dashboard_api.py > /tmp/dashboard.log 2>&1 &
|
||||
DASHBOARD_PID=$!
|
||||
echo "✓ Dashboard API gestartet (PID: $DASHBOARD_PID)"
|
||||
echo ""
|
||||
echo "📊 Dashboard URL: http://localhost:5000/dashboard.html"
|
||||
echo " Dashboard Log: /tmp/dashboard.log"
|
||||
echo ""
|
||||
|
||||
# Cleanup Funktion
|
||||
cleanup() {
|
||||
echo ""
|
||||
echo "⏹️ Stoppe Dashboard (PID: $DASHBOARD_PID)..."
|
||||
kill $DASHBOARD_PID 2>/dev/null || true
|
||||
echo "✓ Gestoppt"
|
||||
exit 0
|
||||
}
|
||||
|
||||
# Trap für Ctrl+C
|
||||
trap cleanup SIGINT SIGTERM
|
||||
fi
|
||||
|
||||
# RD-Agent fin_quant starten
|
||||
echo "🔄 Starte EURUSD Trading-Agent..."
|
||||
echo ""
|
||||
dotenv run -- rdagent fin_quant
|
||||
|
||||
# Cleanup wenn fertig
|
||||
if [[ $REPLY =~ ^[Yy]$ ]]; then
|
||||
cleanup
|
||||
fi
|
||||
Reference in New Issue
Block a user