diff --git a/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb b/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb index b8c3e8b..46b3a96 100644 --- a/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb +++ b/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb @@ -5,37 +5,36 @@ "execution_count": null, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING:tensorflow:From C:\\Users\\EDY\\AppData\\Roaming\\Python\\Python311\\site-packages\\keras\\src\\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.\n", - "\n" - ] - }, { "data": { "text/html": [ " \n", + " \n", " " ] }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "获取的token: eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJhcGlfZGV2IiwidGgiOiI4YTQ1NzdkYmQ5MTk2NzU3NThkNTc5OTlhMWU4OTFmZSIsImx0IjoiYXBpIiwiaXNzIjoiIiwidG0iOiJQQyIsImV4cCI6MTc0MzEwNTAxMCwianRpIjoiN2QwMjE1N2Q0NzIwNDZjMjk3NTE4ODMzNjA3NzY3OTQifQ.F2QXnRxR_YUmQ8w2GIWkvjy0xLMTZg93rJ-wHkuyIzw\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\h5218\\AppData\\Local\\Temp\\ipykernel_31728\\3153608672.py:885: 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" + ] } ], "source": [ @@ -49,6 +48,7 @@ "login_url = \"http://10.200.32.39/jingbo-api/api/server/login\"\n", "search_url = \"http://10.200.32.39/jingbo-api/api/warehouse/dwDataItem/queryByItemNos\"\n", "# search_url = \"http://10.200.32.39/jingbo-api/api/warehouse/dwDataItem/queryDataListItemNos\" \n", + "queryDataListItemNos_url = \"http://10.200.32.39/jingbo-api//api/warehouse/dwDataItem/queryDataListItemNos\"\n", "\n", "\n", "login_push_url = \"http://10.200.32.39/jingbo-api/api/server/login\"\n", @@ -835,12 +835,146 @@ "\n", " # 保存新的xls文件\n", " new_workbook.save(\"液化气数据.xls\")\n", - "\n" + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "def get_queryDataListItemNos_value(token, url, dataItemNoList, dateStart, dateEnd):\n", + "\n", + " search_data = {\n", + " \"funcModule\": \"数据项\",\n", + " \"funcOperation\": \"查询\",\n", + " \"data\": {\n", + " \"dateStart\": dateStart,\n", + " \"dateEnd\": dateEnd,\n", + " \"dataItemNoList\": dataItemNoList # 数据项编码,代表 brent最低价和最高价\n", + " }\n", + " }\n", + "\n", + " headers = {\"Authorization\": token}\n", + " search_res = requests.post(url=url, headers=headers, json=search_data, timeout=(3, 5))\n", + " search_value = json.loads(search_res.text)[\"data\"]\n", + " if search_value:\n", + " return search_value\n", + " else:\n", + " return None\n", + "\n", + "\n", + "\n", + "def save_queryDataListItemNos_xls(data_df,dataItemNoList):\n", + "\n", + " current_year_month = datetime.now().strftime('%Y-%m')\n", + " grouped = data_df.groupby(\"dataDate\")\n", + "\n", + " # 打开xls文件\n", + " workbook = xlrd.open_workbook('液化气数据.xls')\n", + "\n", + " # 获取所有sheet的个数\n", + " sheet_count = len(workbook.sheet_names())\n", + "\n", + " # 获取所有sheet的名称\n", + " sheet_names = workbook.sheet_names()\n", + "\n", + " new_workbook = xlwt.Workbook()\n", + " for i in range(sheet_count):\n", + " # 获取当前sheet\n", + " sheet = workbook.sheet_by_index(i)\n", + "\n", + " # 获取sheet的行数和列数\n", + " row_count = sheet.nrows\n", + " col_count = sheet.ncols\n", + " # 获取原有数据\n", + " data = []\n", + " for row in range(row_count):\n", + " row_data = []\n", + " for col in range(col_count):\n", + " row_data.append(sheet.cell_value(row, col))\n", + " data.append(row_data)\n", + "\n", + " # 创建xlwt的Workbook对象\n", + " # 创建sheet\n", + " new_sheet = new_workbook.add_sheet(sheet_names[i])\n", + "\n", + "\n", + " current_year_month_row = 0\n", + " # 将原有的数据写入新的sheet\n", + " for row in range(row_count):\n", + " for col in range(col_count):\n", + " col0 = data[row][0]\n", + " # print(\"col0\",col0[:7])\n", + " if col0[:7] == current_year_month:\n", + " current_year_month_row += 1\n", + " break\n", + " new_sheet.write(row, col, data[row][col])\n", + "\n", + "\n", + " # print(\"current_year_month_row\",current_year_month_row)\n", + " if i == 0:\n", + " rowFlag = 0\n", + " # 查看每组数据\n", + " for date, group in grouped:\n", + " new_sheet.write(row_count + rowFlag - current_year_month_row, 0, date)\n", + " for j in range(len(dataItemNoList)):\n", + " dataItemNo = dataItemNoList[j]\n", + "\n", + " # for dataItemNo in dataItemNoList:\n", + " if group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values and (not str(group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values[0]) == 'nan'):\n", + " # if group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values:\n", + "\n", + " new_sheet.write(row_count + rowFlag - current_year_month_row, j + 1, group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values[0])\n", + "\n", + " rowFlag += 1\n", + "\n", + "\n", + " # 保存新的xls文件\n", + " new_workbook.save(\"液化气数据.xls\")\n", + "\n", + "\n", + "\n", + "\n", + "def queryDataListItemNos():\n", + " df = pd.read_excel('液化气数据.xls')\n", + " dataItemNoList = df.iloc[0].tolist()[1:]\n", + "\n", + " token = get_head_auth()\n", + " if not token:\n", + " return\n", + "\n", + " # 获取当前日期\n", + " current_date = datetime.now()\n", + "\n", + " # 获取当月1日\n", + " first_day_of_month = current_date.replace(day=1)\n", + "\n", + " # 格式化为 YYYYMMDD 格式\n", + " dateEnd = current_date.strftime('%Y%m%d')\n", + " dateStart = first_day_of_month.strftime('%Y%m%d')\n", + "\n", + " search_value = get_queryDataListItemNos_value(token, queryDataListItemNos_url, dataItemNoList, dateStart, dateEnd)\n", + "\n", + "\n", + " data_df = pd.DataFrame(search_value)\n", + "\n", + " 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", + "\n", + "\n", + "\n", + "\n", + "# if __name__ == \"__main__\":\n", + "\n", + "# # 获取当月的数据写入到指定文件\n", + "# queryDataListItemNos()\n" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "scrolled": true }, @@ -862,6 +996,11 @@ "# current_time_1 = time.strftime(\"%H:%M:%S\", time.localtime())\n", "# # print(current_time_1)\n", "\n", + "\n", + " # 获取当月的数据写入到指定文件\n", + " # queryDataListItemNos()\n", + "\n", + "\n", "# # 判断当前时间是否为执行任务的时间点\n", "# if current_time == \"09:15:00\":\n", "# print(\"执行定时任务\")\n", @@ -927,7 +1066,7 @@ ], "metadata": { "kernelspec": { - "display_name": "base", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -941,7 +1080,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/aisenzhecode/液化石油气/液化气数据.xls b/aisenzhecode/液化石油气/液化气数据.xls index e211593..549d483 100644 Binary files a/aisenzhecode/液化石油气/液化气数据.xls and b/aisenzhecode/液化石油气/液化气数据.xls differ diff --git a/aisenzhecode/石油苯/纯苯价格预测-自定义日期ytj.ipynb b/aisenzhecode/石油苯/纯苯价格预测-自定义日期ytj.ipynb index 7ffd738..b2e2801 100644 --- a/aisenzhecode/石油苯/纯苯价格预测-自定义日期ytj.ipynb +++ b/aisenzhecode/石油苯/纯苯价格预测-自定义日期ytj.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -11,23 +11,23 @@ " \n", + " \n", " " ] }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\h5218\\AppData\\Local\\Temp\\ipykernel_35936\\3451377547.py:725: 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" + ] } ], "source": [ @@ -43,6 +43,7 @@ "\n", "login_push_url = \"http://10.200.32.39/jingbo-api/api/server/login\"\n", "upload_url = \"http://10.200.32.39/jingbo-api/api/dw/dataValue/pushDataValueList\"\n", + "queryDataListItemNos_url = \"http://10.200.32.39/jingbo-api//api/warehouse/dwDataItem/queryDataListItemNos\"\n", "\n", "login_data = {\n", " \"data\": {\n", @@ -674,7 +675,132 @@ " new_workbook.save(\"纯苯数据项.xls\")\n", "\n", "\n", + "\n", + "\n", + "def get_queryDataListItemNos_value(token, url, dataItemNoList, dateStart, dateEnd):\n", + "\n", + " search_data = {\n", + " \"funcModule\": \"数据项\",\n", + " \"funcOperation\": \"查询\",\n", + " \"data\": {\n", + " \"dateStart\": dateStart,\n", + " \"dateEnd\": dateEnd,\n", + " \"dataItemNoList\": dataItemNoList # 数据项编码,代表 brent最低价和最高价\n", + " }\n", + " }\n", + "\n", + " headers = {\"Authorization\": token}\n", + " search_res = requests.post(url=url, headers=headers, json=search_data, timeout=(3, 5))\n", + " search_value = json.loads(search_res.text)[\"data\"]\n", + " if search_value:\n", + " return search_value\n", + " else:\n", + " return None\n", + "\n", + "\n", + "\n", + "def save_queryDataListItemNos_xls(data_df,dataItemNoList):\n", + "\n", + " current_year_month = datetime.datetime.now().strftime('%Y-%m')\n", + " grouped = data_df.groupby(\"dataDate\")\n", + "\n", + " # 打开xls文件\n", + " workbook = xlrd.open_workbook('纯苯数据项.xls')\n", + "\n", + " # 获取所有sheet的个数\n", + " sheet_count = len(workbook.sheet_names())\n", + "\n", + " # 获取所有sheet的名称\n", + " sheet_names = workbook.sheet_names()\n", + "\n", + " new_workbook = xlwt.Workbook()\n", + " for i in range(sheet_count):\n", + " # 获取当前sheet\n", + " sheet = workbook.sheet_by_index(i)\n", + "\n", + " # 获取sheet的行数和列数\n", + " row_count = sheet.nrows\n", + " col_count = sheet.ncols\n", + " # 获取原有数据\n", + " data = []\n", + " for row in range(row_count):\n", + " row_data = []\n", + " for col in range(col_count):\n", + " row_data.append(sheet.cell_value(row, col))\n", + " data.append(row_data)\n", + "\n", + " # 创建xlwt的Workbook对象\n", + " # 创建sheet\n", + " new_sheet = new_workbook.add_sheet(sheet_names[i])\n", + "\n", + "\n", + " current_year_month_row = 0\n", + " # 将原有的数据写入新的sheet\n", + " for row in range(row_count):\n", + " for col in range(col_count):\n", + " col0 = data[row][0]\n", + " # print(\"col0\",col0[:7])\n", + " if col0[:7] == current_year_month:\n", + " current_year_month_row += 1\n", + " break\n", + " new_sheet.write(row, col, data[row][col])\n", + "\n", + "\n", + " # print(\"current_year_month_row\",current_year_month_row)\n", + " if i == 0:\n", + " rowFlag = 0\n", + " # 查看每组数据\n", + " for date, group in grouped:\n", + " new_sheet.write(row_count + rowFlag - current_year_month_row, 0, date)\n", + " for j in range(len(dataItemNoList)):\n", + " dataItemNo = dataItemNoList[j]\n", + "\n", + " if group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values and (not str(group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values[0]) == 'nan'):\n", + "\n", + " new_sheet.write(row_count + rowFlag - current_year_month_row, j + 1, group[group[\"dataItemNo\"] == dataItemNo][\"dataValue\"].values[0])\n", + "\n", + " rowFlag += 1\n", + "\n", + "\n", + " # 保存新的xls文件\n", + " new_workbook.save(\"纯苯数据项.xls\")\n", + "\n", + "\n", + "\n", + "\n", + "def queryDataListItemNos():\n", + " df = pd.read_excel('纯苯数据项.xls')\n", + " dataItemNoList = df.iloc[0].tolist()[1:]\n", + "\n", + " token = get_head_auth()\n", + " if not token:\n", + " return\n", + "\n", + " # 获取当前日期\n", + " current_date = datetime.datetime.now()\n", + "\n", + " # 获取当月1日\n", + " first_day_of_month = current_date.replace(day=1)\n", + "\n", + " # 格式化为 YYYYMMDD 格式\n", + " dateEnd = current_date.strftime('%Y%m%d')\n", + " dateStart = first_day_of_month.strftime('%Y%m%d')\n", + "\n", + " search_value = get_queryDataListItemNos_value(token, queryDataListItemNos_url, dataItemNoList, dateStart, dateEnd)\n", + "\n", + "\n", + " data_df = pd.DataFrame(search_value)\n", + "\n", + " 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", + "\n", + "\n", + "\n", + "\n", + "\n", "if __name__ == \"__main__\":\n", + " # queryDataListItemNos()\n", " pass\n", " # 需要单独运行放开\n", " # start_1()\n", @@ -684,6 +810,9 @@ " # # 获取当前时间\n", " # current_time = time.strftime(\"%H:%M:%S\", time.localtime())\n", " # current_time_1 = time.strftime(\"%H:%M:%S\", time.localtime())\n", + " # # 获取当月的数据写入到指定文件\n", + " # queryDataListItemNos()\n", + "\n", "\n", " # # 判断当前时间是否为执行任务的时间点\n", " # if current_time == \"09:15:00\":\n", @@ -1654,7 +1783,7 @@ ], "metadata": { "kernelspec": { - "display_name": "base", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -1668,7 +1797,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/aisenzhecode/石油苯/纯苯数据项.xls b/aisenzhecode/石油苯/纯苯数据项.xls index 076c47f..5594fe5 100644 Binary files a/aisenzhecode/石油苯/纯苯数据项.xls and b/aisenzhecode/石油苯/纯苯数据项.xls differ