[增强] 自动下载填充指数数据1分钟bar

prod/jobs/refill_tdx_future_bars.py

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+# flake8: noqa
+"""
+下载通达信指数合约1分钟bar => vnpy项目目录/bar_data/
+"""
+import os
+import sys
+import json
+from collections import OrderedDict
+import pandas as pd
+
+vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+if vnpy_root not in sys.path:
+    sys.path.append(vnpy_root)
+
+os.environ["VNPY_TESTING"] = "1"
+
+from vnpy.data.tdx.tdx_future_data import *
+
+# 保存的1分钟指数 bar目录
+bar_data_folder = os.path.abspath(os.path.join(vnpy_root, 'bar_data'))
+
+# 开始日期（每年大概需要几分钟）
+start_date = '20160101'
+
+# 创建API对象
+api_01 = TdxFutureData()
+
+# 更新本地合约缓存信息
+api_01.update_mi_contracts()
+
+# 逐一指数合约下载并更新
+for underlying_symbol in api_01.future_contracts.keys():
+    index_symbol = underlying_symbol + '99'
+    print(f'开始更新:{index_symbol}')
+    # csv数据文件名
+    bar_file_path = os.path.abspath(os.path.join(bar_data_folder, f'{underlying_symbol}99_{start_date}_1m.csv'))
+
+    # 如果文件存在，
+    if os.path.exists(bar_file_path):
+
+        df_old = pd.read_csv(bar_file_path, index_col=0)
+        df_old = df_old.rename(lambda x: pd.to_datetime(x, format="%Y-%m-%d %H:%M:%S"))
+        # 取最后一条时间
+        last_dt = df_old.index[-1]
+        start_dt = last_dt - timedelta(days=1)
+        print(f'文件{bar_file_path}存在，最后时间:{start_date}')
+    else:
+        df_old = None
+        start_dt = datetime.strptime(start_date, '%Y%m%d')
+        print(f'文件{bar_file_path}不存在，开始时间:{start_date}')
+
+    result, bars = api_01.get_bars(symbol=index_symbol,
+                           period='1min',
+                           callback=None,
+                           start_dt=start_dt,
+                           return_bar=False)
+    # [dict] => dataframe
+    if not result or len(bars) == 0:
+        continue
+    df_extern = pd.DataFrame(bars)
+    df_extern.set_index('datetime', inplace=True)
+
+    if df_old is not None:
+        # 扩展数据
+        print('扩展数据')
+        data_df = pd.concat([df_old, df_extern], axis=0)
+    else:
+        data_df = df_extern
+
+    # 数据按时间戳去重
+    print('按时间戳去重')
+    data_df = data_df[~data_df.index.duplicated(keep='first')]
+    # 排序
+    data_df = data_df.sort_index()
+    # print(data_df.head())
+    print(data_df.tail())
+    data_df.to_csv(bar_file_path, index=True)
+    print(f'更新{index_symbol}数据 => 文件{bar_file_path}')
+
+print('更新完毕')
+os._exit(0)