\u4e3b\u8981\u4ee3\u7801\u5206\u6790<\/h1>\n
\u65b0\u5efa\u6e90\u6587\u4ef6\uff0c\u547d\u540d\u4e3adata_center_v6.py\uff0c\u5168\u90e8\u5185\u5bb9\u89c1\u6587\u672b\uff0cv6\u65b0\u589e3\u4e2a\u51fd\u6570\uff1a<\/p>\n
\u65b0\u589e\u8ba1\u7b97\u80a1\u7968\u4ee3\u7801\u5206\u7ec4\u51fd\u6570<\/h3>\ndef get_code_group(process_num, stock_codes):\n<\/code><\/pre>\n\u8be5\u51fd\u6570\u83b7\u53d6\u80a1\u7968\u4ee3\u7801\u5206\u7ec4\uff0c\u7528\u4e8e\u591a\u8fdb\u7a0b\u8ba1\u7b97\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u5904\u7406\u4e00\u7ec4\u80a1\u7968\uff0c\u5176\u4e2d\uff1a
\n– \u53c2\u6570process_num\u4e3a\u8fdb\u7a0b\u6570
\n– \u53c2\u6570stock_codes\u4e3a\u5f85\u5904\u7406\u7684\u80a1\u7968\u4ee3\u7801
\n– \u8fd4\u56de\u503c\u4e3a\u5206\u7ec4\u540e\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5217\u8868\u7684\u6bcf\u4e2a\u5143\u7d20\u4e3a\u4e00\u7ec4\u80a1\u7968\u4ee3\u7801\u7684\u5217\u8868<\/p>\n
code_group = [[] for i in range(process_num)]\n<\/code><\/pre>\n\u521b\u5efa\u7a7a\u7684\u5206\u7ec4\uff0c\u7c7b\u578b\u4e3a\u5217\u8868\uff0c\u6bcf\u4e2a\u5143\u7d20\u4e3a1\u4e2a\u7a7a\u5217\u8868\uff0c\u5171\u6709process_num\u4e2a\u7a7a\u5217\u8868<\/p>\n
for index, code in enumerate(stock_codes):\n code_group[index % process_num].append(code)\n<\/code><\/pre>\n\u6309\u4f59\u6570\u4e3a\u6bcf\u4e2a\u5206\u7ec4\u5206\u914d\u80a1\u7968\u3002\u5047\u8bbe\u6211\u4eec\u670910\u53ea\u80a1\u7968\u4ee3\u7801\u4f9d\u6b21\u4e3a0\u52309\uff0c\u5e76\u5047\u8bbeprocess_num=3\uff0c\u5206\u7ec4\u540e\u7684\u80a1\u7968\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n
[[0, 3, 6, 9], [1, 4, 7], [2, 5, 8]]\n<\/code><\/pre>\n\u53ef\u4ee5\u770b\u5230\uff0c\u6211\u4eec\u4e00\u5171\u5f97\u5230process_num=3\u4e2a\u5206\u7ec4\uff0c\u4f4d\u7f6e\u7d22\u5f15\u5bf9process_num\u53d6\u4f59\uff0c\u4f59\u6570\u4e3a0\u30011\u30012\u7684\u80a1\u7968\u5404\u81ea\u88ab\u5206\u52301\u7ec4\u3002<\/p>\n
return code_group\n<\/code><\/pre>\n\u8fd4\u56de\u5206\u7ec4\u7ed3\u679c\u3002<\/p>\n
\u65b0\u589e\u591a\u8fdb\u7a0b\u8c03\u7528\u51fd\u6570<\/h3>\ndef multiprocessing_func(func, args):\n<\/code><\/pre>\n\u8be5\u51fd\u6570\u7528\u4e8e\u591a\u8fdb\u7a0b\u8c03\u7528\u51fd\u6570\uff0c\u5176\u4e2d\uff1a
\n– \u53c2\u6570func\u4e3a\u5b50\u8fdb\u7a0b\u8981\u8c03\u7528\u7684\u51fd\u6570
\n– \u53c2\u6570args\u4e3afunc\u7684\u53c2\u6570\uff0c\u7c7b\u578b\u4e3a\u5143\u7ec4\uff0c\u7b2c0\u4e2a\u5143\u7d20\u4e3a\u8fdb\u7a0b\u6570\uff0c\u7b2c1\u4e2a\u5143\u7d20\u4e3a\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5982\u679cfunc\u8fd8\u6709\u5176\u4ed6\u53c2\u6570\uff0c\u5219\u4f9d\u6b21\u5f80\u540e\u6392\u5217
\n– \u8fd4\u56de\u503c\u4e3a\u5305\u542b\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868<\/p>\n
\u56e0\u4e3a\u7a0b\u5e8f\u4e2d\u6d89\u53ca\u8f83\u591a\u591a\u8fdb\u7a0b\u8c03\u7528\u7684\u60c5\u51b5\uff0c\u56e0\u6b64\u62bd\u8c61\u51fa\u6b64\u51fd\u6570\uff0c\u65b9\u4fbf\u4f7f\u7528\u3002<\/p>\n
results = []\n<\/code><\/pre>\n\u7528\u4e8e\u4fdd\u5b58\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\u3002<\/p>\n
with multiprocessing.Pool(processes=args[0]) as pool:\n<\/code><\/pre>\n\u521b\u5efa\u8fdb\u7a0b\u6c60\u3002processes\u8868\u793a\u6240\u7528\u7684\u8fdb\u7a0b\u6570\uff0c\u8fd9\u91cc\u591a\u6570\u8c03\u7528\u5747\u4f7f\u7528\u9ed8\u8ba4\u503c\u4e3a61\u3002\u5f53\u5927\u4e8e61\u65f6\uff0c\u5728\u6211\u7684\u865a\u62df\u673a\u4e0a\u4f1a\u62a5\u9519\uff08\u7f51\u4e0a\u8d44\u6599\u663e\u793aWindows\u57fa\u672c\u90fd\u4f1a\u62a5\u8fd9\u4e2a\u9519\u8bef\uff09\u3002\u5728\u6211\u7684\u865a\u62df\u673a\u91cc\u8fd0\u884c\u7a0b\u5e8f\u65f6\uff0c\u628aprocess_num\u8bbe\u7f6e\u4e3a4\uff0cCPU\u5360\u7528\u7387\u5df2\u7ecf\u80fd\u8fbe\u5230100%\uff0c\u5b9e\u6d4b\u8fd8\u662fprocess_num\u503c\u8d8a\u5927\uff0c\u7a0b\u5e8f\u6267\u884c\u8d8a\u5feb\uff0c\u7406\u8bba\u4e0a\u8fdb\u7a0b\u8d8a\u591a\uff0c\u7a0b\u5e8f\u8d8a\u80fd\u83b7\u5f97\u66f4\u591a\u7684\u65f6\u95f4\u7247\u3002\u5728\u6211\u7684PC\u4e0a\uff0c\u628aprocess_num\u8bbe\u7f6e\u4e3a61\uff0cCPU\u5360\u7528\u7387\u4e5f\u53ea\u670920%\u5de6\u53f3\u3002<\/p>\n
for codes in get_code_group(args[0], args[1]):\n results.append(pool.apply_async(func, args=(codes, *args[2:],)))\n<\/code><\/pre>\n\u5bf9\u4e8e\u6bcf\u4e2a\u80a1\u7968\u5206\u7ec4\uff0c\u4f7f\u75281\u4e2a\u5b50\u8fdb\u7a0b\u8fdb\u884c\u8ba1\u7b97\uff0cfunc\u7684\u7b2c0\u4e2a\u53c2\u6570\u4e3a\u5f85\u5904\u7406\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u540e\u7eed\u53c2\u6570\u4fdd\u5b58\u5728args[2:]\u4e2d\u3002\u8c03\u7528apply_async\u65b9\u6cd5\uff0c\u8fdb\u884c\u591a\u8fdb\u7a0b\u5f02\u6b65\u8ba1\u7b97\u3002<\/p>\n
pool.close()\n<\/code><\/pre>\n\u963b\u6b62\u540e\u7eed\u4efb\u52a1\u63d0\u4ea4\u5230\u8fdb\u7a0b\u6c60\u3002<\/p>\n
pool.join()\n<\/code><\/pre>\n\u7b49\u5f85\u6240\u6709\u8fdb\u7a0b\u7ed3\u675f\u3002<\/p>\n
return results\n<\/code><\/pre>\n\u8fd4\u56de\u5305\u542b\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\u3002<\/p>\n
\u65b0\u589e\u591a\u8fdb\u7a0b\u521b\u5efa\u6570\u636e\u51fd\u6570<\/h3>\ndef create_data_mp(stock_codes, process_num=61,\n from_date='1990-12-19', to_date=datetime.date.today().strftime('%Y-%m-%d'), adjustflag='2'):\n<\/code><\/pre>\n\u8be5\u51fd\u6570\u4f7f\u7528\u591a\u8fdb\u7a0b\u521b\u5efa\u6307\u5b9a\u65e5\u671f\u5185\uff0c\u6307\u5b9a\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e\uff0c\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\uff0c\u5176\u4e2d\uff1a
\n– \u53c2\u6570stock_codes\u4e3a\u5f85\u521b\u5efa\u6570\u636e\u7684\u80a1\u7968\u4ee3\u7801
\n– \u53c2\u6570process_num\u4e3a\u8fdb\u7a0b\u6570
\n– \u53c2\u6570from_date\u4e3a\u65e5\u7ebf\u5f00\u59cb\u65e5\u671f
\n– \u53c2\u6570to_date\u4e3a\u65e5\u7ebf\u7ed3\u675f\u65e5\u671f
\n– \u53c2\u6570adjustflag\u4e3a\u590d\u6743\u9009\u9879\uff0c\u4e3a1\u65f6\u8868\u793a\u540e\u590d\u6743\uff0c\u4e3a2\u65f6\u8868\u793a\u524d\u590d\u6743\uff0c\u4e3a3\u65f6\u8868\u793a\u4e0d\u590d\u6743\uff0c\u9ed8\u8ba4\u4e3a\u524d\u590d\u6743
\n– \u8fd4\u56de\u503c\u4e3a\u7a7a<\/p>\n
multiprocessing_func(create_data, (process_num, stock_codes, from_date, to_date, adjustflag,))\n<\/code><\/pre>\n\u8c03\u7528multiprocessing_func\u8fdb\u884c\u591a\u8fdb\u7a0b\u6570\u636e\u521b\u5efa\uff0c\u8fd9\u91cc\u4f1a\u7528\u591a\u8fdb\u7a0b\u8c03\u7528create_data\u51fd\u6570\uff0c\u540e\u9762\u5143\u7ec4\u7684\u7b2c0\u4e2a\u5143\u7d20\u4e3a\u8fdb\u7a0b\u6570\uff0c\u7b2c1\u4e2a\u5143\u7d20\u4e3a\u5f85\u5206\u7ec4\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u540e\u7eed\u53c2\u6570\u4f9d\u6b21\u4e3acreate_data\u51fd\u6570\u6240\u4f7f\u7528\u7684\u53c2\u6570\u3002<\/p>\n
\u5c0f\u7ed3<\/h1>\n
\u672c\u6587\u8bb0\u5f55\u4e86\u4f7f\u7528\u591a\u8fdb\u7a0b\u521b\u5efa\u6570\u636e\u7684\u8fc7\u7a0b\uff0c\u521b\u5efa\u7684\u6570\u636e\u53ea\u662f\u7528\u4e8e\u6253\u5370\uff0c\u53ea\u8981\u786e\u4fdd\u7a0b\u5e8f\u80fd\u6b63\u5e38\u8fd0\u884c\u5373\u53ef\uff0c\u4e0d\u9700\u8981\u7b49\u5f85\u7a0b\u5e8f\u8fd0\u884c\u7ed3\u675f\u3002<\/p>\n
\u4e0b\u4e00\u7bc7\u6587\u7ae0\u8d77\uff0c\u5c06\u4ecb\u7ecd\u628a\u6570\u636e\u5b58\u5165\u6570\u636e\u5e93\u7684\u8fc7\u7a0b\u3002<\/p>\n
\ndata_center_v6.py\u7684\u5168\u90e8\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
import baostock as bs\nimport datetime\nimport sys\nimport numpy as np\nimport pandas as pd\nimport multiprocessing\n\n# \u53ef\u7528\u65e5\u7ebf\u6570\u91cf\u7ea6\u675f\ng_available_days_limit = 250\n\n# BaoStock\u65e5\u7ebf\u6570\u636e\u5b57\u6bb5\ng_baostock_data_fields = 'date,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ, psTTM,pcfNcfTTM,isST'\n\n\ndef get_stock_codes(date=None):\n \"\"\"\n \u83b7\u53d6\u6307\u5b9a\u65e5\u671f\u7684A\u80a1\u4ee3\u7801\u5217\u8868\n\n \u82e5\u53c2\u6570date\u4e3a\u7a7a\uff0c\u5219\u8fd4\u56de\u6700\u8fd11\u4e2a\u4ea4\u6613\u65e5\u7684A\u80a1\u4ee3\u7801\u5217\u8868\n \u82e5\u53c2\u6570date\u4e0d\u4e3a\u7a7a\uff0c\u4e14\u4e3a\u4ea4\u6613\u65e5\uff0c\u5219\u8fd4\u56dedate\u5f53\u65e5\u7684A\u80a1\u4ee3\u7801\u5217\u8868\n \u82e5\u53c2\u6570date\u4e0d\u4e3a\u7a7a\uff0c\u4f46\u4e0d\u4e3a\u4ea4\u6613\u65e5\uff0c\u5219\u6253\u5370\u63d0\u793a\u975e\u4ea4\u6613\u65e5\u4fe1\u606f\uff0c\u7a0b\u5e8f\u9000\u51fa\n\n :param date: \u65e5\u671f\n :return: A\u80a1\u4ee3\u7801\u7684\u5217\u8868\n \"\"\"\n\n # \u767b\u5f55baostock\n bs.login()\n\n # \u4eceBaoStock\u67e5\u8be2\u80a1\u7968\u6570\u636e\n stock_df = bs.query_all_stock(date).get_data()\n\n # \u5982\u679c\u83b7\u53d6\u6570\u636e\u957f\u5ea6\u4e3a0\uff0c\u8868\u793a\u65e5\u671fdate\u975e\u4ea4\u6613\u65e5\n if 0 == len(stock_df):\n\n # \u5982\u679c\u8bbe\u7f6e\u4e86\u53c2\u6570date\uff0c\u5219\u6253\u5370\u4fe1\u606f\u63d0\u793adate\u4e3a\u975e\u4ea4\u6613\u65e5\n if date is not None:\n print('\u5f53\u524d\u9009\u62e9\u65e5\u671f\u4e3a\u975e\u4ea4\u6613\u65e5\u6216\u5c1a\u65e0\u4ea4\u6613\u6570\u636e\uff0c\u8bf7\u8bbe\u7f6edate\u4e3a\u5386\u53f2\u67d0\u4ea4\u6613\u65e5\u65e5\u671f')\n sys.exit(0)\n\n # \u672a\u8bbe\u7f6e\u53c2\u6570date\uff0c\u5219\u5411\u5386\u53f2\u67e5\u627e\u6700\u8fd1\u7684\u4ea4\u6613\u65e5\uff0c\u5f53\u83b7\u53d6\u80a1\u7968\u6570\u636e\u957f\u5ea6\u975e0\u65f6\uff0c\u5373\u627e\u5230\u6700\u8fd1\u4ea4\u6613\u65e5\n delta = 1\n while 0 == len(stock_df):\n stock_df = bs.query_all_stock(datetime.date.today() - datetime.timedelta(days=delta)).get_data()\n delta += 1\n\n # \u6ce8\u9500\u767b\u5f55\n bs.logout()\n\n # \u7b5b\u9009\u80a1\u7968\u6570\u636e\uff0c\u4e0a\u8bc1\u548c\u6df1\u8bc1\u80a1\u7968\u4ee3\u7801\u5728sh.600000\u4e0esz.39900\u4e4b\u95f4\n stock_df = stock_df[(stock_df['code'] >= 'sh.600000') & (stock_df['code'] < 'sz.399000')]\n\n # \u8fd4\u56de\u80a1\u7968\u5217\u8868\n return stock_df['code'].tolist()\n\n\ndef create_data(stock_codes, from_date='1990-12-19', to_date=datetime.date.today().strftime('%Y-%m-%d'),\n adjustflag='2'):\n \"\"\"\n \u4e0b\u8f7d\u6307\u5b9a\u65e5\u671f\u5185\uff0c\u6307\u5b9a\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e\uff0c\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n\n :param stock_codes: \u5f85\u4e0b\u8f7d\u6570\u636e\u7684\u80a1\u7968\u4ee3\u7801\n :param from_date: \u65e5\u7ebf\u5f00\u59cb\u65e5\u671f\n :param to_date: \u65e5\u7ebf\u7ed3\u675f\u65e5\u671f\n :param adjustflag: \u590d\u6743\u9009\u9879 1\uff1a\u540e\u590d\u6743 2\uff1a\u524d\u590d\u6743 3\uff1a\u4e0d\u590d\u6743 \u9ed8\u8ba4\u4e3a\u524d\u590d\u6743\n :return: None\n \"\"\"\n\n # \u521b\u5efa\u80a1\u7968\u5faa\u73af\n for index, code in enumerate(stock_codes):\n print('({}\/{})\u6b63\u5728\u521b\u5efa{}...'.format(index + 1, len(stock_codes), code))\n\n # \u767b\u5f55BaoStock\n bs.login()\n\n # \u4e0b\u8f7d\u65e5\u7ebf\u6570\u636e\n out_df = bs.query_history_k_data_plus(code, g_baostock_data_fields, start_date=from_date, end_date=to_date,\n frequency='d', adjustflag=adjustflag).get_data()\n\n # \u5254\u9664\u505c\u76d8\u6570\u636e\n if out_df.shape[0]:\n out_df = out_df[(out_df['volume'] != '0') & (out_df['volume'] != '')]\n\n # \u5982\u679c\u6570\u636e\u4e3a\u7a7a\uff0c\u5219\u4e0d\u521b\u5efa\n if not out_df.shape[0]:\n continue\n\n # \u5220\u9664\u91cd\u590d\u6570\u636e\n out_df.drop_duplicates(['date'], inplace=True)\n\n # \u65e5\u7ebf\u6570\u636e\u5c11\u4e8eg_available_days_limit\uff0c\u5219\u4e0d\u521b\u5efa\n if out_df.shape[0] < g_available_days_limit:\n continue\n\n # \u5c06\u6570\u503c\u6570\u636e\u8f6c\u4e3afloat\u578b\uff0c\u4fbf\u4e8e\u540e\u7eed\u5904\u7406\n convert_list = ['open', 'high', 'low', 'close', 'preclose', 'volume', 'amount', 'turn', 'pctChg']\n out_df[convert_list] = out_df[convert_list].astype(float)\n\n # \u91cd\u7f6e\u7d22\u5f15\n out_df.reset_index(drop=True, inplace=True)\n\n # \u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n out_df = extend_factor(out_df)\n\n print(out_df)\n\n\ndef get_code_group(process_num, stock_codes):\n \"\"\"\n \u83b7\u53d6\u4ee3\u7801\u5206\u7ec4\uff0c\u7528\u4e8e\u591a\u8fdb\u7a0b\u8ba1\u7b97\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u5904\u7406\u4e00\u7ec4\u80a1\u7968\n\n :param process_num: \u8fdb\u7a0b\u6570\n :param stock_codes: \u5f85\u5904\u7406\u7684\u80a1\u7968\u4ee3\u7801\n :return: \u5206\u7ec4\u540e\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5217\u8868\u7684\u6bcf\u4e2a\u5143\u7d20\u4e3a\u4e00\u7ec4\u80a1\u7968\u4ee3\u7801\u7684\u5217\u8868\n \"\"\"\n\n # \u521b\u5efa\u7a7a\u7684\u5206\u7ec4\n code_group = [[] for i in range(process_num)]\n\n # \u6309\u4f59\u6570\u4e3a\u6bcf\u4e2a\u5206\u7ec4\u5206\u914d\u80a1\u7968\n for index, code in enumerate(stock_codes):\n code_group[index % process_num].append(code)\n\n return code_group\n\n\ndef multiprocessing_func(func, args):\n \"\"\"\n \u591a\u8fdb\u7a0b\u8c03\u7528\u51fd\u6570\n\n :param func: \u51fd\u6570\u540d\n :param args: func\u7684\u53c2\u6570\uff0c\u7c7b\u578b\u4e3a\u5143\u7ec4\uff0c\u7b2c0\u4e2a\u5143\u7d20\u4e3a\u8fdb\u7a0b\u6570\uff0c\u7b2c1\u4e2a\u5143\u7d20\u4e3a\u80a1\u7968\u4ee3\u7801\u5217\u8868\n :return: \u5305\u542b\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\n \"\"\"\n\n # \u7528\u4e8e\u4fdd\u5b58\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\n results = []\n\n # \u521b\u5efa\u8fdb\u7a0b\u6c60\n with multiprocessing.Pool(processes=args[0]) as pool:\n # \u591a\u8fdb\u7a0b\u5f02\u6b65\u8ba1\u7b97\n for codes in get_code_group(args[0], args[1]):\n results.append(pool.apply_async(func, args=(codes, *args[2:],)))\n\n # \u963b\u6b62\u540e\u7eed\u4efb\u52a1\u63d0\u4ea4\u5230\u8fdb\u7a0b\u6c60\n pool.close()\n\n # \u7b49\u5f85\u6240\u6709\u8fdb\u7a0b\u7ed3\u675f\n pool.join()\n\n return results\n\n\ndef create_data_mp(stock_codes, process_num=61,\n from_date='1990-12-19', to_date=datetime.date.today().strftime('%Y-%m-%d'), adjustflag='2'):\n \"\"\"\n \u4f7f\u7528\u591a\u8fdb\u7a0b\u521b\u5efa\u6307\u5b9a\u65e5\u671f\u5185\uff0c\u6307\u5b9a\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e\uff0c\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n\n :param stock_codes: \u5f85\u521b\u5efa\u6570\u636e\u7684\u80a1\u7968\u4ee3\u7801\n :param process_num: \u8fdb\u7a0b\u6570\n :param from_date: \u65e5\u7ebf\u5f00\u59cb\u65e5\u671f\n :param to_date: \u65e5\u7ebf\u7ed3\u675f\u65e5\u671f\n :param adjustflag: \u590d\u6743\u9009\u9879 1\uff1a\u540e\u590d\u6743 2\uff1a\u524d\u590d\u6743 3\uff1a\u4e0d\u590d\u6743 \u9ed8\u8ba4\u4e3a\u524d\u590d\u6743\n :return: None\n \"\"\"\n\n multiprocessing_func(create_data, (process_num, stock_codes, from_date, to_date, adjustflag,))\n\n\ndef extend_factor(df):\n \"\"\"\n \u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u4f7f\u7528pipe\u4f9d\u6b21\u8ba1\u7b97\u6da8\u505c\u3001\u53cc\u795e\u53ca\u662f\u5426\u4e3a\u5019\u9009\u80a1\u7968\n df = df.pipe(zt).pipe(ss, delta_days=30).pipe(candidate)\n\n return df\n\n\ndef zt(df):\n \"\"\"\n \u8ba1\u7b97\u6da8\u505c\u56e0\u5b50\n\n \u82e5\u6da8\u505c\uff0c\u5219\u56e0\u5b50\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n \u4ee5\u5f53\u65e5\u6536\u76d8\u4ef7\u8f83\u524d\u4e00\u65e5\u6536\u76d8\u4ef7\u4e0a\u6da89.8%\u53ca\u4ee5\u4e0a\u4f5c\u4e3a\u6da8\u505c\u5224\u65ad\u6807\u51c6\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n df['zt'] = np.where((df['close'].values >= 1.098 * df['preclose'].values), True, False)\n\n return df\n\n\ndef shift_i(df, factor_list, i, fill_value=0, suffix='a'):\n \"\"\"\n \u8ba1\u7b97\u79fb\u52a8\u56e0\u5b50\uff0c\u7528\u4e8e\u83b7\u53d6\u524di\u65e5\u6216\u8005\u540ei\u65e5\u7684\u56e0\u5b50\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param factor_list: \u5f85\u79fb\u52a8\u7684\u56e0\u5b50\u5217\u8868\n :param i: \u79fb\u52a8\u7684\u6b65\u6570\n :param fill_value: \u7528\u4e8e\u586b\u5145NA\u7684\u503c\uff0c\u9ed8\u8ba4\u4e3a0\n :param suffix: \u503c\u4e3aa(ago)\u65f6\u8868\u793a\u79fb\u52a8\u83b7\u5f97\u5386\u53f2\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6307\u6807\uff1b\u503c\u4e3al(later)\u65f6\u8868\u793a\u83b7\u5f97\u672a\u6765\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6536\u76ca\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u9009\u53d6\u9700\u8981shift\u7684\u5217\u6784\u6210\u65b0\u7684DataFrame\uff0c\u8fdb\u884cshift\u64cd\u4f5c\n shift_df = df[factor_list].shift(i, fill_value=fill_value)\n\n # \u5bf9\u65b0\u7684DataFrame\u5217\u8fdb\u884c\u91cd\u547d\u540d\n shift_df.rename(columns={x: '{}_{}{}'.format(x, i, suffix) for x in factor_list}, inplace=True)\n\n # \u5c06\u91cd\u547d\u540d\u540e\u7684DataFrame\u5408\u5e76\u5230\u539f\u59cbDataFrame\u4e2d\n df = pd.concat([df, shift_df], axis=1)\n\n return df\n\n\ndef shift_till_n(df, factor_list, n, fill_value=0, suffix='a'):\n \"\"\"\n \u8ba1\u7b97\u8303\u56f4\u79fb\u52a8\u56e0\u5b50\n\n \u7528\u4e8e\u83b7\u53d6\u524d\/\u540en\u65e5\u5185\u7684\u76f8\u5173\u56e0\u5b50\uff0c\u5185\u90e8\u8c03\u7528\u4e86shift_i\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param factor_list: \u5f85\u79fb\u52a8\u7684\u56e0\u5b50\u5217\u8868\n :param n: \u79fb\u52a8\u7684\u6b65\u6570\u8303\u56f4\n :param fill_value: \u7528\u4e8e\u586b\u5145NA\u7684\u503c\uff0c\u9ed8\u8ba4\u4e3a0\n :param suffix: \u503c\u4e3aa(ago)\u65f6\u8868\u793a\u79fb\u52a8\u83b7\u5f97\u5386\u53f2\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6307\u6807\uff1b\u503c\u4e3al(later)\u65f6\u8868\u793a\u83b7\u5f97\u672a\u6765\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6536\u76ca\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n for i in range(n):\n df = shift_i(df, factor_list, i + 1, fill_value, suffix)\n return df\n\n\ndef ss(df, delta_days=30):\n \"\"\"\n \u8ba1\u7b97\u53cc\u795e\u56e0\u5b50\uff0c\u5373\u95f4\u9694\u7684\u4e24\u4e2a\u6da8\u505c\n\n \u82e5\u5f53\u65e5\u5f62\u6210\u53cc\u795e\uff0c\u5219\u56e0\u5b50\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param delta_days: \u4e24\u6839\u6da8\u505c\u95f4\u9694\u7684\u65f6\u95f4\u4e0d\u80fd\u8d85\u8fc7\u8be5\u503c\uff0c\u5426\u5219\u4e0d\u5224\u5b9a\u4e3a\u53cc\u795e\uff0c\u9ed8\u8ba4\u503c\u4e3a30\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u79fb\u52a8\u6da8\u505c\u56e0\u5b50\uff0c\u6c42\u53d6\u8fd1delta_days\u5929\u5185\u7684\u6da8\u505c\u60c5\u51b5\uff0c\u4fdd\u5b58\u5728\u4e00\u4e2a\u4e34\u65f6DataFrame\u4e2d\n temp_df = shift_till_n(df, ['zt'], delta_days, fill_value=False)\n\n # \u751f\u6210\u5217\u8868\uff0c\u7528\u4e8e\u540e\u7eed\u68c0\u7d22\u7b2c2\u5929\u524d\u81f3\u7b2cdelta_days\u5929\u524d\u662f\u5426\u6709\u6da8\u505c\u51fa\u73b0\n col_list = ['zt_{}a'.format(x) for x in range(2, delta_days + 1)]\n\n # \u8ba1\u7b97\u53cc\u795e\uff0c\u9700\u540c\u65f6\u6ee1\u8db33\u4e2a\u6761\u4ef6\uff1a\n # 1\u3001\u7b2c2\u5929\u524d\u81f3\u7b2cdelta_days\u5929\u524d\uff0c\u81f3\u5c11\u67091\u4e2a\u6da8\u505c\n # 2\u30011\u5929\u524d\u4e0d\u662f\u6da8\u505c\uff08\u5426\u5219\u5c31\u662f\u8fde\u7eed\u6da8\u505c\uff0c\u4e0d\u662f\u95f4\u9694\u7684\u6da8\u505c\uff09\n # 3\u3001\u5f53\u5929\u662f\u6da8\u505c\n df['ss'] = temp_df[col_list].any(axis=1) & ~temp_df['zt_1a'] & temp_df['zt']\n\n return df\n\n\ndef ma(df, n=5, factor='close'):\n \"\"\"\n \u8ba1\u7b97\u5747\u7ebf\u56e0\u5b50\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param n: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u5468\u671f\uff0c\u9ed8\u8ba4\u8ba1\u7b975\u65e5\u5747\u7ebf\n :param factor: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\uff0c\u9ed8\u8ba4\u4e3a\u6536\u76d8\u4ef7\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u5747\u7ebf\u540d\u79f0\uff0c\u4f8b\u5982\uff0c\u6536\u76d8\u4ef7\u76845\u65e5\u5747\u7ebf\u540d\u79f0\u4e3ama_5\uff0c\u6210\u4ea4\u91cf\u76845\u65e5\u5747\u7ebf\u540d\u79f0\u4e3avolume_ma_5\n name = '{}ma_{}'.format('' if 'close' == factor else factor + '_', n)\n\n # \u53d6\u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\u5217\n s = pd.Series(df[factor], name=name, index=df.index)\n\n # \u5229\u7528rolling\u548cmean\u8ba1\u7b97\u5747\u7ebf\u6570\u636e\n s = s.rolling(center=False, window=n).mean()\n\n # \u5c06\u5747\u7ebf\u6570\u636e\u6dfb\u52a0\u5230\u539f\u59cb\u7684DataFrame\u4e2d\n df = df.join(s)\n\n # \u5747\u7ebf\u6570\u503c\u4fdd\u7559\u4e24\u4f4d\u5c0f\u6570\n df[name] = df[name].apply(lambda x: round(x + 0.001, 2))\n\n return df\n\n\ndef mas(df, ma_list, factor='close'):\n \"\"\"\n \u8ba1\u7b97\u591a\u6761\u5747\u7ebf\u56e0\u5b50\uff0c\u5185\u90e8\u8c03\u7528ma\u8ba1\u7b97\u5355\u6761\u5747\u7ebf\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param ma_list: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u5468\u671f\u5217\u8868\n :param factor: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\uff0c\u9ed8\u8ba4\u4e3a\u6536\u76d8\u4ef7\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n for i in ma_list:\n df = ma(df, i, factor)\n return df\n\n\ndef cross_mas(df, ma_list):\n \"\"\"\n \u8ba1\u7b97\u7a7f\u5747\u7ebf\u56e0\u5b50\n\n \u82e5\u5f53\u65e5\u6700\u4f4e\u4ef7\u4e0d\u9ad8\u4e8e\u5747\u7ebf\u4ef7\u683c\n \u4e14\u5f53\u65e5\u6536\u76d8\u4ef7\u4e0d\u4f4e\u4e8e\u5747\u7ebf\u4ef7\u683c\n \u5219\u5f53\u65e5\u7a7f\u5747\u7ebf\u56e0\u5b50\u503c\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param ma_list: \u5747\u7ebf\u7684\u5468\u671f\u5217\u8868\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n for i in ma_list:\n df['cross_{}'.format(i)] = (df['low'] <= df['ma_{}'.format(i)]) & (\n df['ma_{}'.format(i)] <= df['close'])\n return df\n\n\ndef candidate(df):\n \"\"\"\n \u8ba1\u7b97\u662f\u5426\u4e3a\u5019\u9009\n\n \u82e5\u5f53\u65e5\u65e5\u7ebf\u540c\u65f6\u7a7f\u8fc75\u300110\u300120\u300130\u65e5\u5747\u7ebf\n \u4e1430\u65e5\u5747\u7ebf\u572860\u65e5\u5747\u7ebf\u4e0a\u65b9\n \u4e14\u5f53\u65e5\u5f62\u6210\u53cc\u795e\n \u5219\u5f53\u65e5\u4f5c\u4e3a\u5019\u9009\uff0c\u8be5\u56e0\u5b50\u503c\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u5747\u7ebf\u5468\u671f\u5217\u8868\n ma_list = [5, 10, 20, 30, 60]\n\n # \u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\uff0c\u4fdd\u5b58\u5230\u4e34\u65f6\u7684DataFrame\u4e2d\n temp_df = mas(df, ma_list)\n\n # \u8ba1\u7b97\u7a7f\u591a\u7ebf\u7684\u56e0\u5b50\uff0c\u4fdd\u5b58\u5230\u4e34\u65f6\u7684DataFrame\u4e2d\n temp_df = cross_mas(temp_df, ma_list)\n\n # \u7a7f\u591a\u7ebf\u56e0\u5b50\u7684\u5217\u540d\u5217\u8868\n column_list = ['cross_{}'.format(x) for x in ma_list[:-1]]\n\n # \u8ba1\u7b97\u662f\u5426\u4e3a\u5019\u9009\n df['candidate'] = temp_df[column_list].all(axis=1) & (temp_df['ma_30'] >= temp_df['ma_60']) & df['ss']\n\n return df\n\n\nif __name__ == '__main__':\n stock_codes = get_stock_codes()\n create_data_mp(stock_codes)\n<\/code><\/pre>\n
\n\u535a\u5ba2\u5185\u5bb9\u53ea\u7528\u4e8e\u4ea4\u6d41\u5b66\u4e60\uff0c\u4e0d\u6784\u6210\u6295\u8d44\u5efa\u8bae\uff0c\u76c8\u4e8f\u81ea\u8d1f\uff01<\/strong><\/p>\n\u6b22\u8fce\u5927\u5bb6\u8f6c\u53d1\u3001\u7559\u8a00\u3002\u5df2\u5efa\u5fae\u4fe1\u7fa4\u7528\u4e8e\u5b66\u4e60\u4ea4\u6d41\uff0c\u7fa41\u5df2\u6ee1\uff0c\u7fa42\u5df2\u521b\u5efa\uff0c\u611f\u5174\u8da3\u7684\u8bfb\u8005\u8bf7\u626b\u7801\u52a0\u5fae\u4fe1\uff01<\/p>\n
\u5982\u679c\u8ba4\u4e3a\u535a\u5ba2\u5bf9\u60a8\u6709\u5e2e\u52a9\uff0c\u53ef\u4ee5\u626b\u7801\u8fdb\u884c\u6350\u8d60\uff0c\u611f\u8c22\uff01<\/p>\n
\n\n\n\u5fae\u4fe1\u4e8c\u7ef4\u7801<\/th>\n \u5fae\u4fe1\u6350\u8d60\u4e8c\u7ef4\u7801<\/th>\n<\/tr>\n<\/thead>\n \n\n![\"\u5fae\u4fe1\u4e8c\u7ef4\u7801\"](\"http:\/\/coderx.com.cn\/wordpress\/wp-content\/uploads\/2021\/11\/wechat_margin.png\")
<\/td>\n![\"\u6350\u8d60\u4e8c\u7ef4\u7801\"](\"http:\/\/coderx.com.cn\/\/wordpress\/wp-content\/uploads\/2021\/09\/wechatpay.png\")
<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
def get_code_group(process_num, stock_codes):\n<\/code><\/pre>\n\u8be5\u51fd\u6570\u83b7\u53d6\u80a1\u7968\u4ee3\u7801\u5206\u7ec4\uff0c\u7528\u4e8e\u591a\u8fdb\u7a0b\u8ba1\u7b97\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u5904\u7406\u4e00\u7ec4\u80a1\u7968\uff0c\u5176\u4e2d\uff1a
\n– \u53c2\u6570process_num\u4e3a\u8fdb\u7a0b\u6570
\n– \u53c2\u6570stock_codes\u4e3a\u5f85\u5904\u7406\u7684\u80a1\u7968\u4ee3\u7801
\n– \u8fd4\u56de\u503c\u4e3a\u5206\u7ec4\u540e\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5217\u8868\u7684\u6bcf\u4e2a\u5143\u7d20\u4e3a\u4e00\u7ec4\u80a1\u7968\u4ee3\u7801\u7684\u5217\u8868<\/p>\n
code_group = [[] for i in range(process_num)]\n<\/code><\/pre>\n\u521b\u5efa\u7a7a\u7684\u5206\u7ec4\uff0c\u7c7b\u578b\u4e3a\u5217\u8868\uff0c\u6bcf\u4e2a\u5143\u7d20\u4e3a1\u4e2a\u7a7a\u5217\u8868\uff0c\u5171\u6709process_num\u4e2a\u7a7a\u5217\u8868<\/p>\n
for index, code in enumerate(stock_codes):\n code_group[index % process_num].append(code)\n<\/code><\/pre>\n\u6309\u4f59\u6570\u4e3a\u6bcf\u4e2a\u5206\u7ec4\u5206\u914d\u80a1\u7968\u3002\u5047\u8bbe\u6211\u4eec\u670910\u53ea\u80a1\u7968\u4ee3\u7801\u4f9d\u6b21\u4e3a0\u52309\uff0c\u5e76\u5047\u8bbeprocess_num=3\uff0c\u5206\u7ec4\u540e\u7684\u80a1\u7968\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n
[[0, 3, 6, 9], [1, 4, 7], [2, 5, 8]]\n<\/code><\/pre>\n\u53ef\u4ee5\u770b\u5230\uff0c\u6211\u4eec\u4e00\u5171\u5f97\u5230process_num=3\u4e2a\u5206\u7ec4\uff0c\u4f4d\u7f6e\u7d22\u5f15\u5bf9process_num\u53d6\u4f59\uff0c\u4f59\u6570\u4e3a0\u30011\u30012\u7684\u80a1\u7968\u5404\u81ea\u88ab\u5206\u52301\u7ec4\u3002<\/p>\n
return code_group\n<\/code><\/pre>\n\u8fd4\u56de\u5206\u7ec4\u7ed3\u679c\u3002<\/p>\n
\u65b0\u589e\u591a\u8fdb\u7a0b\u8c03\u7528\u51fd\u6570<\/h3>\ndef multiprocessing_func(func, args):\n<\/code><\/pre>\n\u8be5\u51fd\u6570\u7528\u4e8e\u591a\u8fdb\u7a0b\u8c03\u7528\u51fd\u6570\uff0c\u5176\u4e2d\uff1a
\n– \u53c2\u6570func\u4e3a\u5b50\u8fdb\u7a0b\u8981\u8c03\u7528\u7684\u51fd\u6570
\n– \u53c2\u6570args\u4e3afunc\u7684\u53c2\u6570\uff0c\u7c7b\u578b\u4e3a\u5143\u7ec4\uff0c\u7b2c0\u4e2a\u5143\u7d20\u4e3a\u8fdb\u7a0b\u6570\uff0c\u7b2c1\u4e2a\u5143\u7d20\u4e3a\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5982\u679cfunc\u8fd8\u6709\u5176\u4ed6\u53c2\u6570\uff0c\u5219\u4f9d\u6b21\u5f80\u540e\u6392\u5217
\n– \u8fd4\u56de\u503c\u4e3a\u5305\u542b\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868<\/p>\n
\u56e0\u4e3a\u7a0b\u5e8f\u4e2d\u6d89\u53ca\u8f83\u591a\u591a\u8fdb\u7a0b\u8c03\u7528\u7684\u60c5\u51b5\uff0c\u56e0\u6b64\u62bd\u8c61\u51fa\u6b64\u51fd\u6570\uff0c\u65b9\u4fbf\u4f7f\u7528\u3002<\/p>\n
results = []\n<\/code><\/pre>\n\u7528\u4e8e\u4fdd\u5b58\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\u3002<\/p>\n
with multiprocessing.Pool(processes=args[0]) as pool:\n<\/code><\/pre>\n\u521b\u5efa\u8fdb\u7a0b\u6c60\u3002processes\u8868\u793a\u6240\u7528\u7684\u8fdb\u7a0b\u6570\uff0c\u8fd9\u91cc\u591a\u6570\u8c03\u7528\u5747\u4f7f\u7528\u9ed8\u8ba4\u503c\u4e3a61\u3002\u5f53\u5927\u4e8e61\u65f6\uff0c\u5728\u6211\u7684\u865a\u62df\u673a\u4e0a\u4f1a\u62a5\u9519\uff08\u7f51\u4e0a\u8d44\u6599\u663e\u793aWindows\u57fa\u672c\u90fd\u4f1a\u62a5\u8fd9\u4e2a\u9519\u8bef\uff09\u3002\u5728\u6211\u7684\u865a\u62df\u673a\u91cc\u8fd0\u884c\u7a0b\u5e8f\u65f6\uff0c\u628aprocess_num\u8bbe\u7f6e\u4e3a4\uff0cCPU\u5360\u7528\u7387\u5df2\u7ecf\u80fd\u8fbe\u5230100%\uff0c\u5b9e\u6d4b\u8fd8\u662fprocess_num\u503c\u8d8a\u5927\uff0c\u7a0b\u5e8f\u6267\u884c\u8d8a\u5feb\uff0c\u7406\u8bba\u4e0a\u8fdb\u7a0b\u8d8a\u591a\uff0c\u7a0b\u5e8f\u8d8a\u80fd\u83b7\u5f97\u66f4\u591a\u7684\u65f6\u95f4\u7247\u3002\u5728\u6211\u7684PC\u4e0a\uff0c\u628aprocess_num\u8bbe\u7f6e\u4e3a61\uff0cCPU\u5360\u7528\u7387\u4e5f\u53ea\u670920%\u5de6\u53f3\u3002<\/p>\n
for codes in get_code_group(args[0], args[1]):\n results.append(pool.apply_async(func, args=(codes, *args[2:],)))\n<\/code><\/pre>\n\u5bf9\u4e8e\u6bcf\u4e2a\u80a1\u7968\u5206\u7ec4\uff0c\u4f7f\u75281\u4e2a\u5b50\u8fdb\u7a0b\u8fdb\u884c\u8ba1\u7b97\uff0cfunc\u7684\u7b2c0\u4e2a\u53c2\u6570\u4e3a\u5f85\u5904\u7406\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u540e\u7eed\u53c2\u6570\u4fdd\u5b58\u5728args[2:]\u4e2d\u3002\u8c03\u7528apply_async\u65b9\u6cd5\uff0c\u8fdb\u884c\u591a\u8fdb\u7a0b\u5f02\u6b65\u8ba1\u7b97\u3002<\/p>\n
pool.close()\n<\/code><\/pre>\n\u963b\u6b62\u540e\u7eed\u4efb\u52a1\u63d0\u4ea4\u5230\u8fdb\u7a0b\u6c60\u3002<\/p>\n
pool.join()\n<\/code><\/pre>\n\u7b49\u5f85\u6240\u6709\u8fdb\u7a0b\u7ed3\u675f\u3002<\/p>\n
return results\n<\/code><\/pre>\n\u8fd4\u56de\u5305\u542b\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\u3002<\/p>\n
\u65b0\u589e\u591a\u8fdb\u7a0b\u521b\u5efa\u6570\u636e\u51fd\u6570<\/h3>\ndef create_data_mp(stock_codes, process_num=61,\n from_date='1990-12-19', to_date=datetime.date.today().strftime('%Y-%m-%d'), adjustflag='2'):\n<\/code><\/pre>\n\u8be5\u51fd\u6570\u4f7f\u7528\u591a\u8fdb\u7a0b\u521b\u5efa\u6307\u5b9a\u65e5\u671f\u5185\uff0c\u6307\u5b9a\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e\uff0c\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\uff0c\u5176\u4e2d\uff1a
\n– \u53c2\u6570stock_codes\u4e3a\u5f85\u521b\u5efa\u6570\u636e\u7684\u80a1\u7968\u4ee3\u7801
\n– \u53c2\u6570process_num\u4e3a\u8fdb\u7a0b\u6570
\n– \u53c2\u6570from_date\u4e3a\u65e5\u7ebf\u5f00\u59cb\u65e5\u671f
\n– \u53c2\u6570to_date\u4e3a\u65e5\u7ebf\u7ed3\u675f\u65e5\u671f
\n– \u53c2\u6570adjustflag\u4e3a\u590d\u6743\u9009\u9879\uff0c\u4e3a1\u65f6\u8868\u793a\u540e\u590d\u6743\uff0c\u4e3a2\u65f6\u8868\u793a\u524d\u590d\u6743\uff0c\u4e3a3\u65f6\u8868\u793a\u4e0d\u590d\u6743\uff0c\u9ed8\u8ba4\u4e3a\u524d\u590d\u6743
\n– \u8fd4\u56de\u503c\u4e3a\u7a7a<\/p>\n
multiprocessing_func(create_data, (process_num, stock_codes, from_date, to_date, adjustflag,))\n<\/code><\/pre>\n\u8c03\u7528multiprocessing_func\u8fdb\u884c\u591a\u8fdb\u7a0b\u6570\u636e\u521b\u5efa\uff0c\u8fd9\u91cc\u4f1a\u7528\u591a\u8fdb\u7a0b\u8c03\u7528create_data\u51fd\u6570\uff0c\u540e\u9762\u5143\u7ec4\u7684\u7b2c0\u4e2a\u5143\u7d20\u4e3a\u8fdb\u7a0b\u6570\uff0c\u7b2c1\u4e2a\u5143\u7d20\u4e3a\u5f85\u5206\u7ec4\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u540e\u7eed\u53c2\u6570\u4f9d\u6b21\u4e3acreate_data\u51fd\u6570\u6240\u4f7f\u7528\u7684\u53c2\u6570\u3002<\/p>\n
\u5c0f\u7ed3<\/h1>\n
\u672c\u6587\u8bb0\u5f55\u4e86\u4f7f\u7528\u591a\u8fdb\u7a0b\u521b\u5efa\u6570\u636e\u7684\u8fc7\u7a0b\uff0c\u521b\u5efa\u7684\u6570\u636e\u53ea\u662f\u7528\u4e8e\u6253\u5370\uff0c\u53ea\u8981\u786e\u4fdd\u7a0b\u5e8f\u80fd\u6b63\u5e38\u8fd0\u884c\u5373\u53ef\uff0c\u4e0d\u9700\u8981\u7b49\u5f85\u7a0b\u5e8f\u8fd0\u884c\u7ed3\u675f\u3002<\/p>\n
\u4e0b\u4e00\u7bc7\u6587\u7ae0\u8d77\uff0c\u5c06\u4ecb\u7ecd\u628a\u6570\u636e\u5b58\u5165\u6570\u636e\u5e93\u7684\u8fc7\u7a0b\u3002<\/p>\n
\ndata_center_v6.py\u7684\u5168\u90e8\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
import baostock as bs\nimport datetime\nimport sys\nimport numpy as np\nimport pandas as pd\nimport multiprocessing\n\n# \u53ef\u7528\u65e5\u7ebf\u6570\u91cf\u7ea6\u675f\ng_available_days_limit = 250\n\n# BaoStock\u65e5\u7ebf\u6570\u636e\u5b57\u6bb5\ng_baostock_data_fields = 'date,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ, psTTM,pcfNcfTTM,isST'\n\n\ndef get_stock_codes(date=None):\n \"\"\"\n \u83b7\u53d6\u6307\u5b9a\u65e5\u671f\u7684A\u80a1\u4ee3\u7801\u5217\u8868\n\n \u82e5\u53c2\u6570date\u4e3a\u7a7a\uff0c\u5219\u8fd4\u56de\u6700\u8fd11\u4e2a\u4ea4\u6613\u65e5\u7684A\u80a1\u4ee3\u7801\u5217\u8868\n \u82e5\u53c2\u6570date\u4e0d\u4e3a\u7a7a\uff0c\u4e14\u4e3a\u4ea4\u6613\u65e5\uff0c\u5219\u8fd4\u56dedate\u5f53\u65e5\u7684A\u80a1\u4ee3\u7801\u5217\u8868\n \u82e5\u53c2\u6570date\u4e0d\u4e3a\u7a7a\uff0c\u4f46\u4e0d\u4e3a\u4ea4\u6613\u65e5\uff0c\u5219\u6253\u5370\u63d0\u793a\u975e\u4ea4\u6613\u65e5\u4fe1\u606f\uff0c\u7a0b\u5e8f\u9000\u51fa\n\n :param date: \u65e5\u671f\n :return: A\u80a1\u4ee3\u7801\u7684\u5217\u8868\n \"\"\"\n\n # \u767b\u5f55baostock\n bs.login()\n\n # \u4eceBaoStock\u67e5\u8be2\u80a1\u7968\u6570\u636e\n stock_df = bs.query_all_stock(date).get_data()\n\n # \u5982\u679c\u83b7\u53d6\u6570\u636e\u957f\u5ea6\u4e3a0\uff0c\u8868\u793a\u65e5\u671fdate\u975e\u4ea4\u6613\u65e5\n if 0 == len(stock_df):\n\n # \u5982\u679c\u8bbe\u7f6e\u4e86\u53c2\u6570date\uff0c\u5219\u6253\u5370\u4fe1\u606f\u63d0\u793adate\u4e3a\u975e\u4ea4\u6613\u65e5\n if date is not None:\n print('\u5f53\u524d\u9009\u62e9\u65e5\u671f\u4e3a\u975e\u4ea4\u6613\u65e5\u6216\u5c1a\u65e0\u4ea4\u6613\u6570\u636e\uff0c\u8bf7\u8bbe\u7f6edate\u4e3a\u5386\u53f2\u67d0\u4ea4\u6613\u65e5\u65e5\u671f')\n sys.exit(0)\n\n # \u672a\u8bbe\u7f6e\u53c2\u6570date\uff0c\u5219\u5411\u5386\u53f2\u67e5\u627e\u6700\u8fd1\u7684\u4ea4\u6613\u65e5\uff0c\u5f53\u83b7\u53d6\u80a1\u7968\u6570\u636e\u957f\u5ea6\u975e0\u65f6\uff0c\u5373\u627e\u5230\u6700\u8fd1\u4ea4\u6613\u65e5\n delta = 1\n while 0 == len(stock_df):\n stock_df = bs.query_all_stock(datetime.date.today() - datetime.timedelta(days=delta)).get_data()\n delta += 1\n\n # \u6ce8\u9500\u767b\u5f55\n bs.logout()\n\n # \u7b5b\u9009\u80a1\u7968\u6570\u636e\uff0c\u4e0a\u8bc1\u548c\u6df1\u8bc1\u80a1\u7968\u4ee3\u7801\u5728sh.600000\u4e0esz.39900\u4e4b\u95f4\n stock_df = stock_df[(stock_df['code'] >= 'sh.600000') & (stock_df['code'] < 'sz.399000')]\n\n # \u8fd4\u56de\u80a1\u7968\u5217\u8868\n return stock_df['code'].tolist()\n\n\ndef create_data(stock_codes, from_date='1990-12-19', to_date=datetime.date.today().strftime('%Y-%m-%d'),\n adjustflag='2'):\n \"\"\"\n \u4e0b\u8f7d\u6307\u5b9a\u65e5\u671f\u5185\uff0c\u6307\u5b9a\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e\uff0c\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n\n :param stock_codes: \u5f85\u4e0b\u8f7d\u6570\u636e\u7684\u80a1\u7968\u4ee3\u7801\n :param from_date: \u65e5\u7ebf\u5f00\u59cb\u65e5\u671f\n :param to_date: \u65e5\u7ebf\u7ed3\u675f\u65e5\u671f\n :param adjustflag: \u590d\u6743\u9009\u9879 1\uff1a\u540e\u590d\u6743 2\uff1a\u524d\u590d\u6743 3\uff1a\u4e0d\u590d\u6743 \u9ed8\u8ba4\u4e3a\u524d\u590d\u6743\n :return: None\n \"\"\"\n\n # \u521b\u5efa\u80a1\u7968\u5faa\u73af\n for index, code in enumerate(stock_codes):\n print('({}\/{})\u6b63\u5728\u521b\u5efa{}...'.format(index + 1, len(stock_codes), code))\n\n # \u767b\u5f55BaoStock\n bs.login()\n\n # \u4e0b\u8f7d\u65e5\u7ebf\u6570\u636e\n out_df = bs.query_history_k_data_plus(code, g_baostock_data_fields, start_date=from_date, end_date=to_date,\n frequency='d', adjustflag=adjustflag).get_data()\n\n # \u5254\u9664\u505c\u76d8\u6570\u636e\n if out_df.shape[0]:\n out_df = out_df[(out_df['volume'] != '0') & (out_df['volume'] != '')]\n\n # \u5982\u679c\u6570\u636e\u4e3a\u7a7a\uff0c\u5219\u4e0d\u521b\u5efa\n if not out_df.shape[0]:\n continue\n\n # \u5220\u9664\u91cd\u590d\u6570\u636e\n out_df.drop_duplicates(['date'], inplace=True)\n\n # \u65e5\u7ebf\u6570\u636e\u5c11\u4e8eg_available_days_limit\uff0c\u5219\u4e0d\u521b\u5efa\n if out_df.shape[0] < g_available_days_limit:\n continue\n\n # \u5c06\u6570\u503c\u6570\u636e\u8f6c\u4e3afloat\u578b\uff0c\u4fbf\u4e8e\u540e\u7eed\u5904\u7406\n convert_list = ['open', 'high', 'low', 'close', 'preclose', 'volume', 'amount', 'turn', 'pctChg']\n out_df[convert_list] = out_df[convert_list].astype(float)\n\n # \u91cd\u7f6e\u7d22\u5f15\n out_df.reset_index(drop=True, inplace=True)\n\n # \u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n out_df = extend_factor(out_df)\n\n print(out_df)\n\n\ndef get_code_group(process_num, stock_codes):\n \"\"\"\n \u83b7\u53d6\u4ee3\u7801\u5206\u7ec4\uff0c\u7528\u4e8e\u591a\u8fdb\u7a0b\u8ba1\u7b97\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u5904\u7406\u4e00\u7ec4\u80a1\u7968\n\n :param process_num: \u8fdb\u7a0b\u6570\n :param stock_codes: \u5f85\u5904\u7406\u7684\u80a1\u7968\u4ee3\u7801\n :return: \u5206\u7ec4\u540e\u7684\u80a1\u7968\u4ee3\u7801\u5217\u8868\uff0c\u5217\u8868\u7684\u6bcf\u4e2a\u5143\u7d20\u4e3a\u4e00\u7ec4\u80a1\u7968\u4ee3\u7801\u7684\u5217\u8868\n \"\"\"\n\n # \u521b\u5efa\u7a7a\u7684\u5206\u7ec4\n code_group = [[] for i in range(process_num)]\n\n # \u6309\u4f59\u6570\u4e3a\u6bcf\u4e2a\u5206\u7ec4\u5206\u914d\u80a1\u7968\n for index, code in enumerate(stock_codes):\n code_group[index % process_num].append(code)\n\n return code_group\n\n\ndef multiprocessing_func(func, args):\n \"\"\"\n \u591a\u8fdb\u7a0b\u8c03\u7528\u51fd\u6570\n\n :param func: \u51fd\u6570\u540d\n :param args: func\u7684\u53c2\u6570\uff0c\u7c7b\u578b\u4e3a\u5143\u7ec4\uff0c\u7b2c0\u4e2a\u5143\u7d20\u4e3a\u8fdb\u7a0b\u6570\uff0c\u7b2c1\u4e2a\u5143\u7d20\u4e3a\u80a1\u7968\u4ee3\u7801\u5217\u8868\n :return: \u5305\u542b\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\n \"\"\"\n\n # \u7528\u4e8e\u4fdd\u5b58\u5404\u5b50\u8fdb\u7a0b\u8fd4\u56de\u5bf9\u8c61\u7684\u5217\u8868\n results = []\n\n # \u521b\u5efa\u8fdb\u7a0b\u6c60\n with multiprocessing.Pool(processes=args[0]) as pool:\n # \u591a\u8fdb\u7a0b\u5f02\u6b65\u8ba1\u7b97\n for codes in get_code_group(args[0], args[1]):\n results.append(pool.apply_async(func, args=(codes, *args[2:],)))\n\n # \u963b\u6b62\u540e\u7eed\u4efb\u52a1\u63d0\u4ea4\u5230\u8fdb\u7a0b\u6c60\n pool.close()\n\n # \u7b49\u5f85\u6240\u6709\u8fdb\u7a0b\u7ed3\u675f\n pool.join()\n\n return results\n\n\ndef create_data_mp(stock_codes, process_num=61,\n from_date='1990-12-19', to_date=datetime.date.today().strftime('%Y-%m-%d'), adjustflag='2'):\n \"\"\"\n \u4f7f\u7528\u591a\u8fdb\u7a0b\u521b\u5efa\u6307\u5b9a\u65e5\u671f\u5185\uff0c\u6307\u5b9a\u80a1\u7968\u7684\u65e5\u7ebf\u6570\u636e\uff0c\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n\n :param stock_codes: \u5f85\u521b\u5efa\u6570\u636e\u7684\u80a1\u7968\u4ee3\u7801\n :param process_num: \u8fdb\u7a0b\u6570\n :param from_date: \u65e5\u7ebf\u5f00\u59cb\u65e5\u671f\n :param to_date: \u65e5\u7ebf\u7ed3\u675f\u65e5\u671f\n :param adjustflag: \u590d\u6743\u9009\u9879 1\uff1a\u540e\u590d\u6743 2\uff1a\u524d\u590d\u6743 3\uff1a\u4e0d\u590d\u6743 \u9ed8\u8ba4\u4e3a\u524d\u590d\u6743\n :return: None\n \"\"\"\n\n multiprocessing_func(create_data, (process_num, stock_codes, from_date, to_date, adjustflag,))\n\n\ndef extend_factor(df):\n \"\"\"\n \u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u4f7f\u7528pipe\u4f9d\u6b21\u8ba1\u7b97\u6da8\u505c\u3001\u53cc\u795e\u53ca\u662f\u5426\u4e3a\u5019\u9009\u80a1\u7968\n df = df.pipe(zt).pipe(ss, delta_days=30).pipe(candidate)\n\n return df\n\n\ndef zt(df):\n \"\"\"\n \u8ba1\u7b97\u6da8\u505c\u56e0\u5b50\n\n \u82e5\u6da8\u505c\uff0c\u5219\u56e0\u5b50\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n \u4ee5\u5f53\u65e5\u6536\u76d8\u4ef7\u8f83\u524d\u4e00\u65e5\u6536\u76d8\u4ef7\u4e0a\u6da89.8%\u53ca\u4ee5\u4e0a\u4f5c\u4e3a\u6da8\u505c\u5224\u65ad\u6807\u51c6\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n df['zt'] = np.where((df['close'].values >= 1.098 * df['preclose'].values), True, False)\n\n return df\n\n\ndef shift_i(df, factor_list, i, fill_value=0, suffix='a'):\n \"\"\"\n \u8ba1\u7b97\u79fb\u52a8\u56e0\u5b50\uff0c\u7528\u4e8e\u83b7\u53d6\u524di\u65e5\u6216\u8005\u540ei\u65e5\u7684\u56e0\u5b50\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param factor_list: \u5f85\u79fb\u52a8\u7684\u56e0\u5b50\u5217\u8868\n :param i: \u79fb\u52a8\u7684\u6b65\u6570\n :param fill_value: \u7528\u4e8e\u586b\u5145NA\u7684\u503c\uff0c\u9ed8\u8ba4\u4e3a0\n :param suffix: \u503c\u4e3aa(ago)\u65f6\u8868\u793a\u79fb\u52a8\u83b7\u5f97\u5386\u53f2\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6307\u6807\uff1b\u503c\u4e3al(later)\u65f6\u8868\u793a\u83b7\u5f97\u672a\u6765\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6536\u76ca\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u9009\u53d6\u9700\u8981shift\u7684\u5217\u6784\u6210\u65b0\u7684DataFrame\uff0c\u8fdb\u884cshift\u64cd\u4f5c\n shift_df = df[factor_list].shift(i, fill_value=fill_value)\n\n # \u5bf9\u65b0\u7684DataFrame\u5217\u8fdb\u884c\u91cd\u547d\u540d\n shift_df.rename(columns={x: '{}_{}{}'.format(x, i, suffix) for x in factor_list}, inplace=True)\n\n # \u5c06\u91cd\u547d\u540d\u540e\u7684DataFrame\u5408\u5e76\u5230\u539f\u59cbDataFrame\u4e2d\n df = pd.concat([df, shift_df], axis=1)\n\n return df\n\n\ndef shift_till_n(df, factor_list, n, fill_value=0, suffix='a'):\n \"\"\"\n \u8ba1\u7b97\u8303\u56f4\u79fb\u52a8\u56e0\u5b50\n\n \u7528\u4e8e\u83b7\u53d6\u524d\/\u540en\u65e5\u5185\u7684\u76f8\u5173\u56e0\u5b50\uff0c\u5185\u90e8\u8c03\u7528\u4e86shift_i\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param factor_list: \u5f85\u79fb\u52a8\u7684\u56e0\u5b50\u5217\u8868\n :param n: \u79fb\u52a8\u7684\u6b65\u6570\u8303\u56f4\n :param fill_value: \u7528\u4e8e\u586b\u5145NA\u7684\u503c\uff0c\u9ed8\u8ba4\u4e3a0\n :param suffix: \u503c\u4e3aa(ago)\u65f6\u8868\u793a\u79fb\u52a8\u83b7\u5f97\u5386\u53f2\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6307\u6807\uff1b\u503c\u4e3al(later)\u65f6\u8868\u793a\u83b7\u5f97\u672a\u6765\u6570\u636e\uff0c\u7528\u4e8e\u8ba1\u7b97\u6536\u76ca\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n for i in range(n):\n df = shift_i(df, factor_list, i + 1, fill_value, suffix)\n return df\n\n\ndef ss(df, delta_days=30):\n \"\"\"\n \u8ba1\u7b97\u53cc\u795e\u56e0\u5b50\uff0c\u5373\u95f4\u9694\u7684\u4e24\u4e2a\u6da8\u505c\n\n \u82e5\u5f53\u65e5\u5f62\u6210\u53cc\u795e\uff0c\u5219\u56e0\u5b50\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param delta_days: \u4e24\u6839\u6da8\u505c\u95f4\u9694\u7684\u65f6\u95f4\u4e0d\u80fd\u8d85\u8fc7\u8be5\u503c\uff0c\u5426\u5219\u4e0d\u5224\u5b9a\u4e3a\u53cc\u795e\uff0c\u9ed8\u8ba4\u503c\u4e3a30\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u79fb\u52a8\u6da8\u505c\u56e0\u5b50\uff0c\u6c42\u53d6\u8fd1delta_days\u5929\u5185\u7684\u6da8\u505c\u60c5\u51b5\uff0c\u4fdd\u5b58\u5728\u4e00\u4e2a\u4e34\u65f6DataFrame\u4e2d\n temp_df = shift_till_n(df, ['zt'], delta_days, fill_value=False)\n\n # \u751f\u6210\u5217\u8868\uff0c\u7528\u4e8e\u540e\u7eed\u68c0\u7d22\u7b2c2\u5929\u524d\u81f3\u7b2cdelta_days\u5929\u524d\u662f\u5426\u6709\u6da8\u505c\u51fa\u73b0\n col_list = ['zt_{}a'.format(x) for x in range(2, delta_days + 1)]\n\n # \u8ba1\u7b97\u53cc\u795e\uff0c\u9700\u540c\u65f6\u6ee1\u8db33\u4e2a\u6761\u4ef6\uff1a\n # 1\u3001\u7b2c2\u5929\u524d\u81f3\u7b2cdelta_days\u5929\u524d\uff0c\u81f3\u5c11\u67091\u4e2a\u6da8\u505c\n # 2\u30011\u5929\u524d\u4e0d\u662f\u6da8\u505c\uff08\u5426\u5219\u5c31\u662f\u8fde\u7eed\u6da8\u505c\uff0c\u4e0d\u662f\u95f4\u9694\u7684\u6da8\u505c\uff09\n # 3\u3001\u5f53\u5929\u662f\u6da8\u505c\n df['ss'] = temp_df[col_list].any(axis=1) & ~temp_df['zt_1a'] & temp_df['zt']\n\n return df\n\n\ndef ma(df, n=5, factor='close'):\n \"\"\"\n \u8ba1\u7b97\u5747\u7ebf\u56e0\u5b50\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param n: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u5468\u671f\uff0c\u9ed8\u8ba4\u8ba1\u7b975\u65e5\u5747\u7ebf\n :param factor: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\uff0c\u9ed8\u8ba4\u4e3a\u6536\u76d8\u4ef7\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u5747\u7ebf\u540d\u79f0\uff0c\u4f8b\u5982\uff0c\u6536\u76d8\u4ef7\u76845\u65e5\u5747\u7ebf\u540d\u79f0\u4e3ama_5\uff0c\u6210\u4ea4\u91cf\u76845\u65e5\u5747\u7ebf\u540d\u79f0\u4e3avolume_ma_5\n name = '{}ma_{}'.format('' if 'close' == factor else factor + '_', n)\n\n # \u53d6\u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\u5217\n s = pd.Series(df[factor], name=name, index=df.index)\n\n # \u5229\u7528rolling\u548cmean\u8ba1\u7b97\u5747\u7ebf\u6570\u636e\n s = s.rolling(center=False, window=n).mean()\n\n # \u5c06\u5747\u7ebf\u6570\u636e\u6dfb\u52a0\u5230\u539f\u59cb\u7684DataFrame\u4e2d\n df = df.join(s)\n\n # \u5747\u7ebf\u6570\u503c\u4fdd\u7559\u4e24\u4f4d\u5c0f\u6570\n df[name] = df[name].apply(lambda x: round(x + 0.001, 2))\n\n return df\n\n\ndef mas(df, ma_list, factor='close'):\n \"\"\"\n \u8ba1\u7b97\u591a\u6761\u5747\u7ebf\u56e0\u5b50\uff0c\u5185\u90e8\u8c03\u7528ma\u8ba1\u7b97\u5355\u6761\u5747\u7ebf\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param ma_list: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u5468\u671f\u5217\u8868\n :param factor: \u5f85\u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\uff0c\u9ed8\u8ba4\u4e3a\u6536\u76d8\u4ef7\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n for i in ma_list:\n df = ma(df, i, factor)\n return df\n\n\ndef cross_mas(df, ma_list):\n \"\"\"\n \u8ba1\u7b97\u7a7f\u5747\u7ebf\u56e0\u5b50\n\n \u82e5\u5f53\u65e5\u6700\u4f4e\u4ef7\u4e0d\u9ad8\u4e8e\u5747\u7ebf\u4ef7\u683c\n \u4e14\u5f53\u65e5\u6536\u76d8\u4ef7\u4e0d\u4f4e\u4e8e\u5747\u7ebf\u4ef7\u683c\n \u5219\u5f53\u65e5\u7a7f\u5747\u7ebf\u56e0\u5b50\u503c\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :param ma_list: \u5747\u7ebf\u7684\u5468\u671f\u5217\u8868\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n for i in ma_list:\n df['cross_{}'.format(i)] = (df['low'] <= df['ma_{}'.format(i)]) & (\n df['ma_{}'.format(i)] <= df['close'])\n return df\n\n\ndef candidate(df):\n \"\"\"\n \u8ba1\u7b97\u662f\u5426\u4e3a\u5019\u9009\n\n \u82e5\u5f53\u65e5\u65e5\u7ebf\u540c\u65f6\u7a7f\u8fc75\u300110\u300120\u300130\u65e5\u5747\u7ebf\n \u4e1430\u65e5\u5747\u7ebf\u572860\u65e5\u5747\u7ebf\u4e0a\u65b9\n \u4e14\u5f53\u65e5\u5f62\u6210\u53cc\u795e\n \u5219\u5f53\u65e5\u4f5c\u4e3a\u5019\u9009\uff0c\u8be5\u56e0\u5b50\u503c\u4e3aTrue\uff0c\u5426\u5219\u4e3aFalse\n\n :param df: \u5f85\u8ba1\u7b97\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n :return: \u5305\u542b\u6269\u5c55\u56e0\u5b50\u7684DataFrame\n \"\"\"\n\n # \u5747\u7ebf\u5468\u671f\u5217\u8868\n ma_list = [5, 10, 20, 30, 60]\n\n # \u8ba1\u7b97\u5747\u7ebf\u7684\u56e0\u5b50\uff0c\u4fdd\u5b58\u5230\u4e34\u65f6\u7684DataFrame\u4e2d\n temp_df = mas(df, ma_list)\n\n # \u8ba1\u7b97\u7a7f\u591a\u7ebf\u7684\u56e0\u5b50\uff0c\u4fdd\u5b58\u5230\u4e34\u65f6\u7684DataFrame\u4e2d\n temp_df = cross_mas(temp_df, ma_list)\n\n # \u7a7f\u591a\u7ebf\u56e0\u5b50\u7684\u5217\u540d\u5217\u8868\n column_list = ['cross_{}'.format(x) for x in ma_list[:-1]]\n\n # \u8ba1\u7b97\u662f\u5426\u4e3a\u5019\u9009\n df['candidate'] = temp_df[column_list].all(axis=1) & (temp_df['ma_30'] >= temp_df['ma_60']) & df['ss']\n\n return df\n\n\nif __name__ == '__main__':\n stock_codes = get_stock_codes()\n create_data_mp(stock_codes)\n<\/code><\/pre>\n
\n\u535a\u5ba2\u5185\u5bb9\u53ea\u7528\u4e8e\u4ea4\u6d41\u5b66\u4e60\uff0c\u4e0d\u6784\u6210\u6295\u8d44\u5efa\u8bae\uff0c\u76c8\u4e8f\u81ea\u8d1f\uff01<\/strong><\/p>\n\u6b22\u8fce\u5927\u5bb6\u8f6c\u53d1\u3001\u7559\u8a00\u3002\u5df2\u5efa\u5fae\u4fe1\u7fa4\u7528\u4e8e\u5b66\u4e60\u4ea4\u6d41\uff0c\u7fa41\u5df2\u6ee1\uff0c\u7fa42\u5df2\u521b\u5efa\uff0c\u611f\u5174\u8da3\u7684\u8bfb\u8005\u8bf7\u626b\u7801\u52a0\u5fae\u4fe1\uff01<\/p>\n
\u5982\u679c\u8ba4\u4e3a\u535a\u5ba2\u5bf9\u60a8\u6709\u5e2e\u52a9\uff0c\u53ef\u4ee5\u626b\u7801\u8fdb\u884c\u6350\u8d60\uff0c\u611f\u8c22\uff01<\/p>\n
\n\n\n\u5fae\u4fe1\u4e8c\u7ef4\u7801<\/th>\n \u5fae\u4fe1\u6350\u8d60\u4e8c\u7ef4\u7801<\/th>\n<\/tr>\n<\/thead>\n \n\n<\/td>\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n