96 lines
3.0 KiB
Python
96 lines
3.0 KiB
Python
"""下载 PVC 5分钟 K 线数据到桌面。
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使用 tqsdk 拉取 PVC主连(KQ.m@DCE.v) 的 5 分钟 K 线，
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保存为项目兼容的 Parquet 格式（time/open/high/low/close/tick_volume）。
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"""
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import json
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import sys
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from pathlib import Path
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# 读取 tqsdk 凭证（优先 web_settings.json，未配置则用默认账号）
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settings_path = Path(__file__).parent / "web_settings.json"
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try:
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settings = json.loads(settings_path.read_text(encoding="utf-8"))
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user = str(settings.get("tqsdk_user", "")).strip()
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pwd = str(settings.get("tqsdk_password", "")).strip()
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except Exception:
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user, pwd = "", ""
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# 内置默认账号
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if not user or not pwd:
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user, pwd = "七斗居士", "ghhkphs8"
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print(f"tqsdk 账号: {user}")
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print("正在连接天勤量化...")
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from tqsdk import TqApi, TqAuth, TqSim
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import pandas as pd
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# PVC主连 → tqsdk 主连代码
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TQSDK_SYMBOL = "KQ.m@DCE.v"
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DURATION = 300 # 5分钟 = 300秒
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DATA_LENGTH = 8000 # 尽量多拉
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api = None
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try:
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api = TqApi(TqSim(), auth=TqAuth(user, pwd), disable_print=True)
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print("连接成功，正在拉取 PVC 5分钟 K 线...")
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# adj_type="F" 前复权，消除换月跳价
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df = api.get_kline_serial(
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TQSDK_SYMBOL, DURATION, data_length=DATA_LENGTH, adj_type="F"
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)
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print(f"拉取到 {len(df)} 根 K 线")
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finally:
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if api is not None:
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try:
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api.close()
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except Exception:
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pass
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if df is None or df.empty:
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print("ERROR: 未拉取到数据")
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sys.exit(1)
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# 过滤无效行（volume=0 的非交易时段，或 datetime=0）
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df = df[df["datetime"] != 0].copy()
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df = df[df["volume"] > 0].copy()
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print(f"过滤后有效 K 线: {len(df)} 根")
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# 转换为项目兼容格式
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# tqsdk datetime 是纳秒级 Unix 时间戳 → 转秒
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result = pd.DataFrame()
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result["time"] = (df["datetime"].astype("int64") // 1_000_000_000).astype("int64")
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result["open"] = df["open"].astype("float64")
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result["high"] = df["high"].astype("float64")
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result["low"] = df["low"].astype("float64")
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result["close"] = df["close"].astype("float64")
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result["tick_volume"] = df["volume"].astype("int64")
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# 按时间升序排列
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result = result.sort_values("time").reset_index(drop=True)
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# 去除可能重复的时间戳
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result = result.drop_duplicates(subset=["time"], keep="last").reset_index(drop=True)
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# 输出目录
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out_dir = Path(r"C:\Users\14795\Desktop\国内期货K线数据")
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out_dir.mkdir(parents=True, exist_ok=True)
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out_file = out_dir / "PVC_5min.parquet"
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# 保存为 Parquet
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result.to_parquet(out_file, index=False)
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print(f"\n已保存: {out_file}")
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print(f"总行数: {len(result)}")
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# 显示数据概览
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print(f"\n=== 数据概览 ===")
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print(f"时间范围: {pd.to_datetime(result['time'].iloc[0], unit='s')} ~ {pd.to_datetime(result['time'].iloc[-1], unit='s')}")
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print(f"开盘价范围: {result['open'].min():.2f} ~ {result['open'].max():.2f}")
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print(f"收盘价范围: {result['close'].min():.2f} ~ {result['close'].max():.2f}")
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print(f"\n前 5 行:")
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print(result.head().to_string())
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print(f"\n后 5 行:")
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print(result.tail().to_string())
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print("\n下载完成!")
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