diff --git a/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb b/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb index d13ce47..e0138f1 100644 --- a/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb +++ b/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 6, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -192,8 +192,7 @@ "\n", "def get_cur_time(date = ''):\n", " if date == '':\n", - " import datetime\n", - " now = datetime.datetime.now()\n", + " now = datetime.now()\n", " else:\n", " now = date\n", " year = now.year\n", @@ -545,6 +544,9 @@ " else:\n", " append_rows.append(\"\")\n", " save_xls(append_rows)\n", + " \n", + " # 获取当月的数据写入到指定文件\n", + " queryDataListItemNos(token)\n", " optimize_Model()\n", " upload_data_to_system(token_push)\n", " # data_list.append(three_cols)\n", @@ -582,8 +584,11 @@ " else:\n", " append_rows.append(\"\")\n", " save_xls(append_rows)\n", - " optimize_Model()\n", - " upload_data_to_system(token_push,date)\n", + "\n", + " # 获取当月的数据写入到指定文件\n", + " queryDataListItemNos(token)\n", + " # optimize_Model()\n", + " # upload_data_to_system(token_push,date)\n", " # data_list.append(three_cols)\n", " # write_xls(data_list)\n", "\n", @@ -786,7 +791,7 @@ "\n", "def save_queryDataListItemNos_xls(data_df,dataItemNoList):\n", "\n", - " current_year_month = datetime.datetime.now().strftime('%Y-%m')\n", + " current_year_month = datetime.now().strftime('%Y-%m')\n", " grouped = data_df.groupby(\"dataDate\")\n", "\n", " # 打开xls文件\n", @@ -854,16 +859,19 @@ "\n", "\n", "\n", - "def queryDataListItemNos():\n", + "def queryDataListItemNos(token=None):\n", " df = pd.read_excel('沥青数据项.xls')\n", " dataItemNoList = df.iloc[0].tolist()[1:]\n", + " \n", + " if token is None:\n", + " token = get_head_auth()\n", "\n", - " token = get_head_auth()\n", - " if not token:\n", - " return\n", + " if not token:\n", + " print('token获取失败')\n", + " return\n", "\n", " # 获取当前日期\n", - " current_date = datetime.datetime.now()\n", + " current_date = datetime.now()\n", "\n", " # 获取当月1日\n", " first_day_of_month = current_date.replace(day=1)\n", @@ -880,6 +888,7 @@ " data_df[\"dataDate\"] = pd.to_datetime(data_df[\"dataDate\"])\n", " data_df[\"dataDate\"] = data_df[\"dataDate\"].dt.strftime('%Y-%m-%d')\n", " save_queryDataListItemNos_xls(data_df,dataItemNoList)\n", + " print('当月数据更新完成')\n", "\n", "\n", "if __name__ == \"__main__\":\n", @@ -894,8 +903,7 @@ " # current_time = time.strftime(\"%H:%M:%S\", time.localtime())\n", " # current_time_1 = time.strftime(\"%H:%M:%S\", time.localtime())\n", "\n", - " # 获取当月的数据写入到指定文件\n", - " # queryDataListItemNos()\n", + "\n", " \n", "\n", " # # 判断当前时间是否为执行任务的时间点\n", @@ -906,7 +914,7 @@ " # 预测训练，\n", " # 预测结果上传\n", "\n", - " # start()\n", + " # start()\n", "\n", " # # 休眠1秒钟，避免过多占用CPU资源\n", " # time.sleep(1)\n", @@ -926,14 +934,37 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "20250401\n" + ] + }, + { + "ename": "PermissionError", + "evalue": "[Errno 13] Permission denied: '沥青数据项.xls'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mPermissionError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[12], line 11\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m start_date \u001b[38;5;241m<\u001b[39m end_date:\n\u001b[0;32m 10\u001b[0m \u001b[38;5;28mprint\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[1;32m---> 11\u001b[0m start_3(start_date,token,token_push)\n\u001b[0;32m 12\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m 13\u001b[0m start_2(start_date,token)\n", + "Cell \u001b[1;32mIn[11], line 553\u001b[0m, in \u001b[0;36mstart_3\u001b[1;34m(date, token, token_push)\u001b[0m\n\u001b[0;32m 551\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 552\u001b[0m append_rows\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m--> 553\u001b[0m save_xls(append_rows)\n\u001b[0;32m 555\u001b[0m \u001b[38;5;66;03m# 获取当月的数据写入到指定文件\u001b[39;00m\n\u001b[0;32m 556\u001b[0m queryDataListItemNos(token)\n", + "Cell \u001b[1;32mIn[11], line 731\u001b[0m, in \u001b[0;36msave_xls\u001b[1;34m(append_rows)\u001b[0m\n\u001b[0;32m 728\u001b[0m new_sheet\u001b[38;5;241m.\u001b[39mwrite(row_count, col, append_rows[col])\n\u001b[0;32m 730\u001b[0m \u001b[38;5;66;03m# 保存新的xls文件\u001b[39;00m\n\u001b[1;32m--> 731\u001b[0m new_workbook\u001b[38;5;241m.\u001b[39msave(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m沥青数据项.xls\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python311\\site-packages\\xlwt\\Workbook.py:710\u001b[0m, in \u001b[0;36mWorkbook.save\u001b[1;34m(self, filename_or_stream)\u001b[0m\n\u001b[0;32m 707\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m CompoundDoc\n\u001b[0;32m 709\u001b[0m doc \u001b[38;5;241m=\u001b[39m CompoundDoc\u001b[38;5;241m.\u001b[39mXlsDoc()\n\u001b[1;32m--> 710\u001b[0m doc\u001b[38;5;241m.\u001b[39msave(filename_or_stream, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_biff_data())\n", + "File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python311\\site-packages\\xlwt\\CompoundDoc.py:262\u001b[0m, in \u001b[0;36mXlsDoc.save\u001b[1;34m(self, file_name_or_filelike_obj, stream)\u001b[0m\n\u001b[0;32m 260\u001b[0m we_own_it \u001b[38;5;241m=\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(f, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwrite\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 261\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m we_own_it:\n\u001b[1;32m--> 262\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(file_name_or_filelike_obj, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mw+b\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 263\u001b[0m f\u001b[38;5;241m.\u001b[39mwrite(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mheader)\n\u001b[0;32m 264\u001b[0m f\u001b[38;5;241m.\u001b[39mwrite(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpacked_MSAT_1st)\n", + "\u001b[1;31mPermissionError\u001b[0m: [Errno 13] Permission denied: '沥青数据项.xls'" + ] + } + ], "source": [ "# from datetime import datetime, timedelta\n", "\n", - "# start_date = datetime(2025, 2, 1)\n", - "# end_date = datetime(2025, 3, 1)\n", + "# start_date = datetime(2025, 4, 1)\n", + "# end_date = datetime(2025, 4, 2)\n", "# token = get_head_auth()\n", "\n", "# token_push = get_head_push_auth()\n", @@ -945,74 +976,6 @@ "# start_2(start_date,token)\n", "# start_date += timedelta(days=1)" ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19596\\1389844199.py:811: DeprecationWarning:\n", - "\n", - "The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19596\\1389844199.py:302: 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", - "Best score: 0.997\n", - "Best parameters set:\n", - "\tlearning_rate: 0.1\n", - "\tmax_depth: 6\n", - "\tn_estimators: 100\n", - "日期\n", - "2025-03-26 3627.309326\n", - "Name: 日度预测价格, dtype: float32\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19596\\1389844199.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_19596\\1389844199.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" - ] - }, - { - "data": { - "text/plain": [ - "3627.31" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "queryDataListItemNos()\n", - "optimize_Model()\n", - "forecast_price()" - ] } ], "metadata": { diff --git a/aisenzhecode/沥青/沥青数据项.xls b/aisenzhecode/沥青/沥青数据项.xls index f8032d5..290b16e 100644 Binary files a/aisenzhecode/沥青/沥青数据项.xls and b/aisenzhecode/沥青/沥青数据项.xls differ