原油日度预测，推送数据调整
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workpc
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c3e8eef4c9
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89b83c6d2a
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\4165952193.py:294: UserWarning:\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
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"\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\4165952193.py:296: UserWarning:\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"d:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\magics\\pylab.py:162: UserWarning:\n",
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"\n",
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"pylab import has clobbered these variables: ['plot', '__version__', 'random', 'datetime']\n",
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"`%matplotlib` prevents importing * from pylab and numpy\n",
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"text": [
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"Using matplotlib backend: QtAgg\n",
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"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
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"Populating the interactive namespace from numpy and matplotlib\n",
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"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
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]
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
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"\n",
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"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
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"text": [
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"Date\n",
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"2025-03-01 5476.566406\n",
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"Name: 日度预测价格, dtype: float32\n",
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"预测值： 5476.57\n",
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"20250302 <class 'str'>\n",
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"2025-03-02 00:00:00 <class 'datetime.datetime'>\n",
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"{'data': {'date': '20250302', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
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"[{'dataDate': '20250302', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8441.0}, {'dataDate': '20250302', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250302', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250302', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250302', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250302', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4700.0}, {'dataDate': '20250302', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250302', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250302', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250302', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5518.0}, {'dataDate': '20250302', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250302', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5485.0}, {'dataDate': '20250302', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5510.0}, {'dataDate': '20250302', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5520.0}, {'dataDate': '20250302', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 445.7282}, {'dataDate': '20250302', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250302', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 500.0}, {'dataDate': '20250302', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250302', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250302', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250302', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6500.0}]\n",
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"{'dataDate': '20250302', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
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"text": [
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
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"\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"text": [
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"d:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\magics\\pylab.py:162: UserWarning:\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
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"\n",
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"\n",
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"pylab import has clobbered these variables: ['plot', '__version__', 'random', 'datetime']\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"`%matplotlib` prevents importing * from pylab and numpy\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
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"\n",
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"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
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"\n"
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"output_type": "stream",
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"text": [
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"text": [
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"Date\n",
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"Date\n",
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"2025-03-01 5408.340332\n",
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"2025-03-02 5478.945312\n",
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"Name: 日度预测价格, dtype: float32\n"
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"Name: 日度预测价格, dtype: float32\n",
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"预测值： 5478.95\n",
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"20250303 <class 'str'>\n",
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"2025-03-03 00:00:00 <class 'datetime.datetime'>\n",
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"{'data': {'date': '20250303', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
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"[{'dataDate': '20250303', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8381.0}, {'dataDate': '20250303', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5440.0}, {'dataDate': '20250303', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250303', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250303', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250303', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250303', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4700.0}, {'dataDate': '20250303', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250303', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250303', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250303', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5518.0}, {'dataDate': '20250303', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250303', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5485.0}, {'dataDate': '20250303', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5510.0}, {'dataDate': '20250303', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5540.0}, {'dataDate': '20250303', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 429.3767}, {'dataDate': '20250303', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250303', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 500.0}, {'dataDate': '20250303', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250303', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250303', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5310.0}, {'dataDate': '20250303', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250303', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250303', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6200.0}]\n",
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"{'dataDate': '20250303', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\4165952193.py:244: UserWarning:\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"text": [
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"Using matplotlib backend: QtAgg\n",
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"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
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"Populating the interactive namespace from numpy and matplotlib\n",
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"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
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]
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},
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{
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"name": "stderr",
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"text": [
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
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"\n",
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"\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
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"\n",
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"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\4165952193.py:276: FutureWarning:\n",
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
"\n",
|
"\n",
|
||||||
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
"\n"
|
"\n"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"ename": "KeyError",
|
"name": "stdout",
|
||||||
"evalue": "0",
|
"output_type": "stream",
|
||||||
"output_type": "error",
|
"text": [
|
||||||
"traceback": [
|
"Date\n",
|
||||||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
"2025-03-03 5488.296875\n",
|
||||||
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
"Cell \u001b[1;32mIn[9], line 7\u001b[0m\n\u001b[0;32m 5\u001b[0m date \u001b[38;5;241m=\u001b[39m start_date\u001b[38;5;241m.\u001b[39mstrftime(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mY\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mm\u001b[39m\u001b[38;5;132;01m%d\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 6\u001b[0m \u001b[38;5;28mprint\u001b[39m(date,\u001b[38;5;28mtype\u001b[39m(date))\n\u001b[1;32m----> 7\u001b[0m start(date)\n\u001b[0;32m 8\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# start_2(start_date)\u001b[39;00m\n",
|
"预测值： 5488.3\n",
|
||||||
"Cell \u001b[1;32mIn[7], line 519\u001b[0m, in \u001b[0;36mstart\u001b[1;34m(date)\u001b[0m\n\u001b[0;32m 517\u001b[0m save_xls(append_rows)\n\u001b[0;32m 518\u001b[0m optimize_Model()\n\u001b[1;32m--> 519\u001b[0m upload_data_to_system(token_push,cur_time)\n",
|
"20250304 <class 'str'>\n",
|
||||||
"Cell \u001b[1;32mIn[7], line 215\u001b[0m, in \u001b[0;36mupload_data_to_system\u001b[1;34m(token_push, date)\u001b[0m\n\u001b[0;32m 200\u001b[0m data \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 201\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfuncModule\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m数据表信息列表\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 202\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfuncOperation\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m新增\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 210\u001b[0m ]\n\u001b[0;32m 211\u001b[0m }\n\u001b[0;32m 212\u001b[0m \u001b[38;5;66;03m# headers = {\"Authorization\": token_push}\u001b[39;00m\n\u001b[0;32m 213\u001b[0m \u001b[38;5;66;03m# res = requests.post(url=upload_url, headers=headers, json=data, timeout=(3, 5))\u001b[39;00m\n\u001b[0;32m 214\u001b[0m \u001b[38;5;66;03m# print(res.text)\u001b[39;00m\n\u001b[1;32m--> 215\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m预测值：\u001b[39m\u001b[38;5;124m'\u001b[39m,data[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdataValue\u001b[39m\u001b[38;5;124m'\u001b[39m])\n",
|
"2025-03-04 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
"\u001b[1;31mKeyError\u001b[0m: 0"
|
"{'data': {'date': '20250304', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250304', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8345.0}, {'dataDate': '20250304', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5440.0}, {'dataDate': '20250304', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250304', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250304', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250304', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250304', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4700.0}, {'dataDate': '20250304', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250304', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250304', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250304', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5518.0}, {'dataDate': '20250304', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250304', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5485.0}, {'dataDate': '20250304', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5540.0}, {'dataDate': '20250304', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5540.0}, {'dataDate': '20250304', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 434.243}, {'dataDate': '20250304', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250304', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 500.0}, {'dataDate': '20250304', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250304', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250304', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5310.0}, {'dataDate': '20250304', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250304', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8350.0}, {'dataDate': '20250304', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6175.0}]\n",
|
||||||
|
"{'dataDate': '20250304', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-04 5480.574707\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5480.57\n",
|
||||||
|
"20250305 <class 'str'>\n",
|
||||||
|
"2025-03-05 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
|
"{'data': {'date': '20250305', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250305', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8262.0}, {'dataDate': '20250305', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5440.0}, {'dataDate': '20250305', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250305', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250305', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250305', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250305', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4700.0}, {'dataDate': '20250305', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250305', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5530.0}, {'dataDate': '20250305', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250305', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5558.0}, {'dataDate': '20250305', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250305', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5535.0}, {'dataDate': '20250305', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5540.0}, {'dataDate': '20250305', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5540.0}, {'dataDate': '20250305', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 418.0574}, {'dataDate': '20250305', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250305', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 1500.0}, {'dataDate': '20250305', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250305', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250305', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250305', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250305', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8350.0}, {'dataDate': '20250305', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6100.0}]\n",
|
||||||
|
"{'dataDate': '20250305', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-05 5483.269531\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5483.27\n",
|
||||||
|
"20250306 <class 'str'>\n",
|
||||||
|
"2025-03-06 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
|
"{'data': {'date': '20250306', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250306', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8208.0}, {'dataDate': '20250306', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5440.0}, {'dataDate': '20250306', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250306', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250306', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250306', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250306', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4700.0}, {'dataDate': '20250306', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250306', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5580.0}, {'dataDate': '20250306', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250306', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5588.0}, {'dataDate': '20250306', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250306', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5585.0}, {'dataDate': '20250306', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5580.0}, {'dataDate': '20250306', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5580.0}, {'dataDate': '20250306', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 420.1378}, {'dataDate': '20250306', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250306', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 200.0}, {'dataDate': '20250306', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250306', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250306', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250306', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250306', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8250.0}, {'dataDate': '20250306', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6100.0}]\n",
|
||||||
|
"{'dataDate': '20250306', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
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|
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|
||||||
|
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|
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|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
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|
||||||
|
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|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-06 5485.089355\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5485.09\n",
|
||||||
|
"20250307 <class 'str'>\n",
|
||||||
|
"2025-03-07 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
|
"{'data': {'date': '20250307', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250307', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8165.0}, {'dataDate': '20250307', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5440.0}, {'dataDate': '20250307', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250307', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250307', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250307', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250307', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4700.0}, {'dataDate': '20250307', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250307', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5580.0}, {'dataDate': '20250307', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250307', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250307', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250307', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250307', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250307', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5600.0}, {'dataDate': '20250307', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 413.8139}, {'dataDate': '20250307', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250307', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250307', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250307', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250307', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5140.0}, {'dataDate': '20250307', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250307', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8250.0}, {'dataDate': '20250307', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6200.0}]\n",
|
||||||
|
"{'dataDate': '20250307', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
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|
||||||
|
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|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-07 5487.358887\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5487.36\n",
|
||||||
|
"20250308 <class 'str'>\n",
|
||||||
|
"2025-03-08 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
|
"{'data': {'date': '20250308', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250308', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8183.0}, {'dataDate': '20250308', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250308', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250308', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250308', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250308', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4750.0}, {'dataDate': '20250308', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250308', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5580.0}, {'dataDate': '20250308', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250308', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250308', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250308', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250308', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250308', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5600.0}, {'dataDate': '20250308', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 444.6938}, {'dataDate': '20250308', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250308', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 150.0}, {'dataDate': '20250308', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250308', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250308', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250308', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6350.0}]\n",
|
||||||
|
"{'dataDate': '20250308', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-08 5521.991699\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5521.99\n",
|
||||||
|
"20250309 <class 'str'>\n",
|
||||||
|
"2025-03-09 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
|
"{'data': {'date': '20250309', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250309', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8183.0}, {'dataDate': '20250309', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250309', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250309', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250309', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250309', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4750.0}, {'dataDate': '20250309', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250309', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250309', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250309', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250309', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250309', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250309', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250309', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5600.0}, {'dataDate': '20250309', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 367.1581}, {'dataDate': '20250309', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250309', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 150.0}, {'dataDate': '20250309', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250309', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250309', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250309', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6350.0}]\n",
|
||||||
|
"{'dataDate': '20250309', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-09 5482.379395\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5482.38\n",
|
||||||
|
"20250310 <class 'str'>\n",
|
||||||
|
"2025-03-10 00:00:00 <class 'datetime.datetime'>\n",
|
||||||
|
"{'data': {'date': '20250310', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
|
||||||
|
"[{'dataDate': '20250310', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8183.0}, {'dataDate': '20250310', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250310', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250310', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250310', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250310', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250310', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250310', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250310', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5600.0}, {'dataDate': '20250310', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250310', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 150.0}, {'dataDate': '20250310', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250310', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250310', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6350.0}]\n",
|
||||||
|
"{'dataDate': '20250310', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:294: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:296: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Using matplotlib backend: QtAgg\n",
|
||||||
|
"%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
|
||||||
|
"Populating the interactive namespace from numpy and matplotlib\n",
|
||||||
|
"Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:242: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:244: UserWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
|
||||||
|
"\n",
|
||||||
|
"C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10264\\614562064.py:276: FutureWarning:\n",
|
||||||
|
"\n",
|
||||||
|
"Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Date\n",
|
||||||
|
"2025-03-10 5485.84375\n",
|
||||||
|
"Name: 日度预测价格, dtype: float32\n",
|
||||||
|
"预测值： 5485.84\n",
|
||||||
|
"[5476.57, 5478.95, 5488.3, 5480.57, 5483.27, 5485.09, 5487.36, 5521.99, 5482.38, 5485.84]\n"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
|
|||||||
@ -88,13 +88,17 @@ global_config = {
|
|||||||
'query_data_list_item_nos_url': None, # 数据项查询地址
|
'query_data_list_item_nos_url': None, # 数据项查询地址
|
||||||
'query_data_list_item_nos_data': None, # 数据项查询参数
|
'query_data_list_item_nos_data': None, # 数据项查询参数
|
||||||
|
|
||||||
|
# 上传数据项数据
|
||||||
|
'push_data_value_list_url': None,
|
||||||
|
'push_data_value_list_data': None,
|
||||||
|
|
||||||
# 字段映射
|
# 字段映射
|
||||||
'offsite_col': None, # 站点字段
|
'offsite_col': None, # 站点字段
|
||||||
'avg_col': None, # 平均值字段
|
'avg_col': None, # 平均值字段
|
||||||
'offsite': None, # 站点名称
|
'offsite': None, # 站点名称
|
||||||
'edbcodenamedict': None, # EDB编码映射
|
'edbcodenamedict': None, # EDB编码映射
|
||||||
'rote': None, # 绘图上下界阈值
|
'rote': None, # 绘图上下界阈值
|
||||||
'bdwd_items':None,
|
'bdwd_items': None,
|
||||||
|
|
||||||
# 接口配置（原有配置）
|
# 接口配置（原有配置）
|
||||||
'login_pushreport_url': None,
|
'login_pushreport_url': None,
|
||||||
@ -1064,6 +1068,7 @@ def getdata_juxiting(filename, datecol='date', y='y', dataset='', add_kdj=False,
|
|||||||
|
|
||||||
return df, df_zhibiaoliebiao
|
return df, df_zhibiaoliebiao
|
||||||
|
|
||||||
|
|
||||||
def getdata_zhoudu_juxiting(filename, datecol='date', y='y', dataset='', add_kdj=False, is_timefurture=False, end_time=''):
|
def getdata_zhoudu_juxiting(filename, datecol='date', y='y', dataset='', add_kdj=False, is_timefurture=False, end_time=''):
|
||||||
config.logger.info('getdata接收：'+filename+' '+datecol+' '+end_time)
|
config.logger.info('getdata接收：'+filename+' '+datecol+' '+end_time)
|
||||||
# 判断后缀名 csv或excel
|
# 判断后缀名 csv或excel
|
||||||
@ -1165,9 +1170,12 @@ class Config:
|
|||||||
self): return global_config['query_data_list_item_nos_data']
|
self): return global_config['query_data_list_item_nos_data']
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def push_data_value_list_url(self): return global_config['push_data_value_list_url']
|
def push_data_value_list_url(
|
||||||
|
self): return global_config['push_data_value_list_url']
|
||||||
|
|
||||||
@property
|
@property
|
||||||
def push_data_value_list_data(self): return global_config['push_data_value_list_data']
|
def push_data_value_list_data(
|
||||||
|
self): return global_config['push_data_value_list_data']
|
||||||
|
|
||||||
# 字段映射
|
# 字段映射
|
||||||
@property
|
@property
|
||||||
@ -2036,6 +2044,7 @@ def get_market_data(end_time, df):
|
|||||||
df = pd.merge(df, df2, how='left', on='date')
|
df = pd.merge(df, df2, how='left', on='date')
|
||||||
return df
|
return df
|
||||||
|
|
||||||
|
|
||||||
def push_market_data(data):
|
def push_market_data(data):
|
||||||
'''
|
'''
|
||||||
上传预测价格到市场信息平台
|
上传预测价格到市场信息平台
|
||||||
@ -2061,7 +2070,7 @@ def push_market_data(data):
|
|||||||
# 获取token
|
# 获取token
|
||||||
token = get_head_auth_report()
|
token = get_head_auth_report()
|
||||||
# 定义请求参数
|
# 定义请求参数
|
||||||
config.push_data_value_list_data['data'] = data
|
global_config['push_data_value_list_data']['data'] = data
|
||||||
# 发送请求
|
# 发送请求
|
||||||
headers = {"Authorization": token}
|
headers = {"Authorization": token}
|
||||||
config.logger.info('上传数据中...')
|
config.logger.info('上传数据中...')
|
||||||
@ -2071,6 +2080,7 @@ def push_market_data(data):
|
|||||||
config.logger.info(f"上传结果:{json_data}")
|
config.logger.info(f"上传结果:{json_data}")
|
||||||
return json_data
|
return json_data
|
||||||
|
|
||||||
|
|
||||||
def get_high_low_data(df):
|
def get_high_low_data(df):
|
||||||
# 读取excel 从第五行开始
|
# 读取excel 从第五行开始
|
||||||
df1 = pd.read_excel(os.path.join(config.dataset, '数据项下载.xls'), header=5, names=[
|
df1 = pd.read_excel(os.path.join(config.dataset, '数据项下载.xls'), header=5, names=[
|
||||||
|
|||||||
@ -29,7 +29,7 @@ global_config.update({
|
|||||||
'test_size': test_size,
|
'test_size': test_size,
|
||||||
'modelsindex': modelsindex,
|
'modelsindex': modelsindex,
|
||||||
'rote': rote,
|
'rote': rote,
|
||||||
'bdwd_items':bdwd_items,
|
'bdwd_items': bdwd_items,
|
||||||
|
|
||||||
# 特征工程开关
|
# 特征工程开关
|
||||||
'is_del_corr': is_del_corr,
|
'is_del_corr': is_del_corr,
|
||||||
@ -56,6 +56,10 @@ global_config.update({
|
|||||||
'query_data_list_item_nos_url': query_data_list_item_nos_url,
|
'query_data_list_item_nos_url': query_data_list_item_nos_url,
|
||||||
'query_data_list_item_nos_data': query_data_list_item_nos_data,
|
'query_data_list_item_nos_data': query_data_list_item_nos_data,
|
||||||
|
|
||||||
|
# 上传数据项
|
||||||
|
'push_data_value_list_url': push_data_value_list_url,
|
||||||
|
'push_data_value_list_data': push_data_value_list_data,
|
||||||
|
|
||||||
# eta 配置
|
# eta 配置
|
||||||
'APPID': APPID,
|
'APPID': APPID,
|
||||||
'SECRET': SECRET,
|
'SECRET': SECRET,
|
||||||
@ -337,8 +341,6 @@ def predict_main():
|
|||||||
|
|
||||||
# logger.info('模型训练完成')
|
# logger.info('模型训练完成')
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
# logger.info('训练数据绘图ing')
|
# logger.info('训练数据绘图ing')
|
||||||
# model_results3 = model_losss(sqlitedb, end_time=end_time)
|
# model_results3 = model_losss(sqlitedb, end_time=end_time)
|
||||||
# logger.info('训练数据绘图end')
|
# logger.info('训练数据绘图end')
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user