更改第一次配置和其他词运行参数
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liurui
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1ddbd5badc
commit
bd59033555
@ -234,6 +234,9 @@ is_update_eta = False # 预测结果上传到eta
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is_update_report = False # 是否上传报告
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is_update_warning_data = False # 是否上传预警数据
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is_del_corr = 0.6 # 是否删除相关性高的特征,取值为 0-1 ，0 为不删除，0.6 表示删除相关性小于0.6的特征
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is_del_tow_month = True # 是否删除两个月不更新的特征
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# 连接到数据库
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db_mysql = MySQLDB(host=host, user=dbusername, password=password, database=dbname)
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@ -242,7 +245,7 @@ print("数据库连接成功",host,dbname,dbusername)
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# 数据截取日期
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start_year = 2018 # 数据开始年份
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start_year = 2020 # 数据开始年份
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end_time = '2024-12-04' # 数据截取日期
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freq = 'B' # 时间频率，"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日
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delweekenday = True if freq == 'B' else False # 是否删除周末数据
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@ -700,6 +700,7 @@ def datachuli(df_zhibiaoshuju,df_zhibiaoliebiao,datecol='date',end_time='',y='y'
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# if is_update_warning_data:
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# upload_warning_info(last_update_times_df,y_last_update_time)
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# 去掉近最后数据对应的日期在六月以前的列，删除近2月的数据是常熟的列
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if is_del_tow_month:
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current_date = datetime.datetime.now()
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two_months_ago = current_date - timedelta(days=180)
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logger.info(f'删除两月不更新特征前数据量：{df.shape}')
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@ -9,7 +9,7 @@ torch.set_float32_matmul_precision("high")
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def predict_main(end_time):
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def predict_main():
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"""
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主预测函数，用于从 ETA 获取数据、处理数据、训练模型并进行预测。
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@ -238,8 +238,12 @@ def predict_main(end_time):
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if __name__ == '__main__':
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is_on = True
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# 遍历2024-11-25 到 2024-12-3 之间的工作日日期
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for i_time in pd.date_range('2024-12-02', '2024-12-16', freq='B'):
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for i_time in pd.date_range('2024-10-07', '2024-12-16', freq='B'):
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end_time = i_time.strftime('%Y-%m-%d')
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# print(e_time)
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predict_main(end_time)
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predict_main()
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if is_on:
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is_train = False
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is_on = False
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is_fivemodels = True
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@ -357,9 +357,6 @@ def model_losss(sqlitedb,end_time):
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# 取前五最佳模型的最大最小值作为上下边界值
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df_combined3[['min_within_quantile','max_within_quantile']]= df_combined3[modelnames].apply(add_upper_lower_bound, axis=1)
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def find_closest_values(row):
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x = row.y
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if x is None or np.isnan(x):
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@ -439,16 +436,16 @@ def model_losss(sqlitedb,end_time):
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# 准确率基准与绘图上下界逻辑一致
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# predict_y[['min_price','max_price']] = predict_y[['min_within_quantile','max_within_quantile']]
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# 模型评估前五均值
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# predict_y['min_price'] = predict_y[modelnames].mean(axis=1) -1
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# predict_y['max_price'] = predict_y[modelnames].mean(axis=1) +1
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predict_y['min_price'] = predict_y[modelnames].mean(axis=1) -1
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predict_y['max_price'] = predict_y[modelnames].mean(axis=1) +1
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# 模型评估前十均值
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# predict_y['min_price'] = predict_y[allmodelnames[0:10]].mean(axis=1) -1
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# predict_y['max_price'] = predict_y[allmodelnames[0:10]].mean(axis=1) +1
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# 模型评估前十最大最小
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# allmodelnames 和 predict_y 列 重复的
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allmodelnames = [col for col in allmodelnames if col in predict_y.columns]
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predict_y['min_price'] = predict_y[allmodelnames[0:10]].min(axis=1)
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predict_y['max_price'] = predict_y[allmodelnames[0:10]].max(axis=1)
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# allmodelnames = [col for col in allmodelnames if col in predict_y.columns]
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# predict_y['min_price'] = predict_y[allmodelnames[0:10]].min(axis=1)
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# predict_y['max_price'] = predict_y[allmodelnames[0:10]].max(axis=1)
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for id in ids:
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row = predict_y[predict_y['id'] == id]
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try:
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@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 13,
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"id": "9daadf20-caa6-4b25-901c-6cc3ef563f58",
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"metadata": {},
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"outputs": [
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@ -11,7 +11,7 @@
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"output_type": "stream",
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"text": [
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"(85, 28)\n",
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"(20, 4)\n",
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"(22, 4)\n",
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"(85, 31)\n",
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" ds NHITS Informer LSTM iTransformer TSMixer \\\n",
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"0 2024-11-25 75.714300 75.523370 73.614220 75.27068 75.03936 \n",
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@ -35,11 +35,11 @@
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"4 73.96690 74.81860 5 2024-11-22 73.521570 \n",
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"\n",
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" max_price 序号 LOW_PRICE HIGH_PRICE \n",
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"0 75.959854 10.0 72.30 74.83 \n",
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"1 77.182580 9.0 71.63 73.80 \n",
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"2 78.378624 8.0 71.71 72.85 \n",
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"3 79.415400 7.0 71.85 72.96 \n",
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"4 79.576970 6.0 71.75 73.34 \n",
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"0 75.959854 15.0 72.30 74.83 \n",
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"1 77.182580 14.0 71.63 73.80 \n",
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"2 78.378624 13.0 71.71 72.85 \n",
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"3 79.415400 12.0 71.85 72.96 \n",
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"4 79.576970 11.0 71.75 73.34 \n",
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"\n",
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"[5 rows x 31 columns]\n",
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" ds NHITS Informer LSTM iTransformer TSMixer \\\n",
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@ -79,6 +79,10 @@
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"import os\n",
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"import pandas as pd\n",
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"\n",
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"# dataset = r'D:\\liurui\\dev\\code\\PriceForecast\\yuanyoudataset'\n",
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"\n",
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"dataset = r'C:\\Users\\Administrator\\Desktop' \n",
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"\n",
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"# 预测价格数据\n",
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"# dbfilename = os.path.join(r'D:\\code\\PriceForecast\\yuanyoudataset','jbsh_yuanyou.db')\n",
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"# conn = sqlite3.connect(dbfilename)\n",
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@ -89,12 +93,12 @@
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"# print(df1.shape)\n",
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"\n",
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"# 预测价格数据\n",
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"dfcsvfilename = os.path.join(r'D:\\code\\PriceForecast\\yuanyoudataset','accuracy_ten.csv')\n",
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"dfcsvfilename = os.path.join(dataset,'accuracy_ten.csv')\n",
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"df1 = pd.read_csv(dfcsvfilename)\n",
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"print(df1.shape)\n",
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"\n",
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"# 最高最低价\n",
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"xlsfilename = os.path.join(r'D:\\code\\PriceForecast\\yuanyoudataset','数据项下载.xls')\n",
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"xlsfilename = os.path.join(dataset,'数据项下载.xls')\n",
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"df2 = pd.read_excel(xlsfilename)[5:]\n",
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"df2 = df2.rename(columns = {'数据项名称':'ds','布伦特最低价':'LOW_PRICE','布伦特最高价':'HIGH_PRICE'})\n",
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"print(df2.shape)\n",
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@ -108,8 +112,9 @@
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"df = df.reindex()\n",
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"\n",
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"print(df.shape)\n",
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"\n",
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"df.to_csv(os.path.join(r'D:\\code\\PriceForecast\\yuanyoudataset','123.csv'))\n",
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"# from datetime import datetime\n",
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"import time\n",
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"df.to_csv(os.path.join(dataset,f'预测数据-{time.time()}.csv'))\n",
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"# df = df[['ds','min_within_quantile','max_within_quantile']]\n",
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"\n",
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"\n",
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@ -121,53 +126,128 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 27,
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"id": "0d77ab7d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# 模型评估前五均值 \n",
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"df['min_price'] = df.iloc[:,1:11].mean(axis=1) -2\n",
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"df['max_price'] = df.iloc[:,1:11].mean(axis=1) +2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"id": "e51c3fd0-6bff-45de-b8b6-971e7986c7a7",
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"metadata": {},
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"outputs": [
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{
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"ename": "KeyError",
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"evalue": "\"None of [Index(['HIGH_PRICE_y', 'LOW_PRICE_y', 'MIN_PRICE', 'MAX_PRICE'], dtype='object')] are in the [columns]\"",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[1;32mIn[3], line 15\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[38;5;66;03m# 使用 apply 函数来应用计算准确率的函数\u001b[39;00m\n\u001b[0;32m 14\u001b[0m columns \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mHIGH_PRICE_y\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mLOW_PRICE_y\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMIN_PRICE\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMAX_PRICE\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m---> 15\u001b[0m df[columns] \u001b[38;5;241m=\u001b[39m df[columns]\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mfloat\u001b[39m)\n\u001b[0;32m 16\u001b[0m df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mACCURACY\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m df\u001b[38;5;241m.\u001b[39mapply(calculate_accuracy, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m 19\u001b[0m \u001b[38;5;66;03m# 打印结果\u001b[39;00m\n",
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"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\frame.py:3899\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 3897\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_iterator(key):\n\u001b[0;32m 3898\u001b[0m key \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(key)\n\u001b[1;32m-> 3899\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39m_get_indexer_strict(key, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcolumns\u001b[39m\u001b[38;5;124m\"\u001b[39m)[\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m 3901\u001b[0m \u001b[38;5;66;03m# take() does not accept boolean indexers\u001b[39;00m\n\u001b[0;32m 3902\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(indexer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mbool\u001b[39m:\n",
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"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:6115\u001b[0m, in \u001b[0;36mIndex._get_indexer_strict\u001b[1;34m(self, key, axis_name)\u001b[0m\n\u001b[0;32m 6112\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 6113\u001b[0m keyarr, indexer, new_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reindex_non_unique(keyarr)\n\u001b[1;32m-> 6115\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_raise_if_missing(keyarr, indexer, axis_name)\n\u001b[0;32m 6117\u001b[0m keyarr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtake(indexer)\n\u001b[0;32m 6118\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, Index):\n\u001b[0;32m 6119\u001b[0m \u001b[38;5;66;03m# GH 42790 - Preserve name from an Index\u001b[39;00m\n",
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"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:6176\u001b[0m, in \u001b[0;36mIndex._raise_if_missing\u001b[1;34m(self, key, indexer, axis_name)\u001b[0m\n\u001b[0;32m 6174\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m use_interval_msg:\n\u001b[0;32m 6175\u001b[0m key \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(key)\n\u001b[1;32m-> 6176\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNone of [\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkey\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m] are in the [\u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m]\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 6178\u001b[0m not_found \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(ensure_index(key)[missing_mask\u001b[38;5;241m.\u001b[39mnonzero()[\u001b[38;5;241m0\u001b[39m]]\u001b[38;5;241m.\u001b[39munique())\n\u001b[0;32m 6179\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnot_found\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not in index\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
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"\u001b[1;31mKeyError\u001b[0m: \"None of [Index(['HIGH_PRICE_y', 'LOW_PRICE_y', 'MIN_PRICE', 'MAX_PRICE'], dtype='object')] are in the [columns]\""
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-08 2024-11-15 0\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-15 2024-11-22 0\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-15 2024-11-22 0\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-15 2024-11-22 0\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-15 2024-11-22 0\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-15 2024-11-22 0\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-22 2024-11-29 0.808456\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-22 2024-11-29 0.808456\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-22 2024-11-29 0.808456\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-22 2024-11-29 0.808456\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-22 2024-11-29 0.808456\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-29 2024-12-06 0.955061\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-29 2024-12-06 0.955061\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-29 2024-12-06 0.955061\n",
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" 开始日期 结束日期 准确率\n",
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"0 2024-11-29 2024-12-06 0.955061\n",
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" 开始日期 结束日期 准确率\n",
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||||
"0 2024-11-29 2024-12-06 0.955061\n",
|
||||
" 开始日期 结束日期 准确率\n",
|
||||
"0 2024-12-06 2024-12-13 0.905554\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# 定义一个函数来计算准确率\n",
|
||||
"# 比较真实最高最低，和预测最高最低 计算准确率\n",
|
||||
"def calculate_accuracy(row):\n",
|
||||
" if row['HIGH_PRICE_y'] > row['MIN_PRICE']:\n",
|
||||
" sorted_prices = sorted([row['LOW_PRICE_y'], row['MIN_PRICE'], row['MAX_PRICE'], row['HIGH_PRICE_y']])\n",
|
||||
" # 全子集情况：\n",
|
||||
" if (row['max_price'] >= row['HIGH_PRICE'] and row['min_price'] <= row['LOW_PRICE']) or \\\n",
|
||||
" (row['max_price'] <= row['HIGH_PRICE'] and row['min_price'] >= row['LOW_PRICE']):\n",
|
||||
" return 1 \n",
|
||||
" # 无交集情况：\n",
|
||||
" if row['max_price'] < row['LOW_PRICE'] or \\\n",
|
||||
" row['min_price'] > row['HIGH_PRICE']:\n",
|
||||
" return 0\n",
|
||||
" # 有交集情况：\n",
|
||||
" else:\n",
|
||||
" sorted_prices = sorted([row['LOW_PRICE'], row['min_price'], row['max_price'], row['HIGH_PRICE']])\n",
|
||||
" middle_diff = sorted_prices[2] - sorted_prices[1]\n",
|
||||
" price_range = row['HIGH_PRICE_y'] - row['LOW_PRICE_y']\n",
|
||||
" price_range = row['HIGH_PRICE'] - row['LOW_PRICE']\n",
|
||||
" accuracy = middle_diff / price_range\n",
|
||||
" return accuracy\n",
|
||||
" else:\n",
|
||||
" return 0\n",
|
||||
"import datetime\n",
|
||||
"weight_dict = [0.4,0.15,0.1,0.1,0.25] # 权重\n",
|
||||
"\n",
|
||||
"# 使用 apply 函数来应用计算准确率的函数\n",
|
||||
"\n",
|
||||
"columns = ['HIGH_PRICE_y','LOW_PRICE_y','MIN_PRICE','MAX_PRICE']\n",
|
||||
"columns = ['HIGH_PRICE','LOW_PRICE','min_price','max_price']\n",
|
||||
"df[columns] = df[columns].astype(float)\n",
|
||||
"df['ACCURACY'] = df.apply(calculate_accuracy, axis=1)\n",
|
||||
"# df['ACCURACY'] = df.apply(is_within_range, axis=1)\n",
|
||||
"# 取结束日期上一周的日期\n",
|
||||
"def get_week_date(end_time):\n",
|
||||
" endtime = end_time\n",
|
||||
" endtimeweek = datetime.datetime.strptime(endtime, '%Y-%m-%d')\n",
|
||||
" up_week = endtimeweek - datetime.timedelta(days=endtimeweek.weekday() + 14)\n",
|
||||
" up_week_dates = [up_week + datetime.timedelta(days=i) for i in range(14)][4:-2]\n",
|
||||
" up_week_dates = [date.strftime('%Y-%m-%d') for date in up_week_dates]\n",
|
||||
" return up_week_dates\n",
|
||||
"\n",
|
||||
"# 计算准确率并保存结果\n",
|
||||
"def _get_accuracy_rate(df,up_week_dates,endtime):\n",
|
||||
" df3 = df.copy()\n",
|
||||
" df3 = df3[df3['CREAT_DATE'].isin(up_week_dates)]\n",
|
||||
" df3 = df3[df3['ds'].isin(up_week_dates)]\n",
|
||||
" accuracy_rote = 0\n",
|
||||
" for i,group in df3.groupby('ds'):\n",
|
||||
" # print('权重：',weight_dict[len(group)-1])\n",
|
||||
" # print('准确率：',(group['ACCURACY'].sum()/len(group))*weight_dict[len(group)-1])\n",
|
||||
" accuracy_rote += (group['ACCURACY'].sum()/len(group))*weight_dict[len(group)-1]\n",
|
||||
" df3.to_csv(os.path.join(dataset,f'accuracy_{endtime}.csv'),index=False)\n",
|
||||
" df4 = pd.DataFrame(columns=['开始日期','结束日期','准确率'])\n",
|
||||
" df4.loc[len(df4)] = {'开始日期':up_week_dates[0],'结束日期':up_week_dates[-1],'准确率':accuracy_rote}\n",
|
||||
" df4.to_csv(os.path.join(dataset,f'accuracy_rote_{endtime}.csv'),index=False)\n",
|
||||
" print(df4)\n",
|
||||
" # df4.to_sql(\"accuracy_rote\", con=sqlitedb.connection, if_exists='append', index=False)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"end_times = df['CREAT_DATE'].unique()\n",
|
||||
"for endtime in end_times:\n",
|
||||
" up_week_dates = get_week_date(endtime)\n",
|
||||
" _get_accuracy_rate(df,up_week_dates,end_time)\n",
|
||||
"\n",
|
||||
"# 打印结果\n",
|
||||
"print(df[['ds','ACCURACY',]+columns])\n",
|
||||
"\n",
|
||||
"df = df[['ds','ACCURACY','PREDICT_DATE','CREAT_DATE']+columns]"
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 138,
|
||||
"execution_count": null,
|
||||
"id": "0f942c69",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
@ -180,7 +260,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 139,
|
||||
"execution_count": null,
|
||||
"id": "a7b05510",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -407,7 +487,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 140,
|
||||
"execution_count": null,
|
||||
"id": "1374e354",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -445,7 +525,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 141,
|
||||
"execution_count": null,
|
||||
"id": "8aa47e90",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
||||
@ -2,10 +2,25 @@
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 25,
|
||||
"execution_count": 1,
|
||||
"id": "31c0e11d-c87a-4e95-92a0-d1d09625e255",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"ERROR:root:Error connecting to the database: (2003, \"Can't connect to MySQL server on '192.168.101.27' (timed out)\")\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"数据库连接成功 192.168.101.27 jingbo_test root\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from config_jingbo import *\n",
|
||||
"import requests\n",
|
||||
@ -15,7 +30,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 26,
|
||||
"execution_count": 2,
|
||||
"id": "83c81b9e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -25,7 +40,7 @@
|
||||
"'http://192.168.100.53:8080/jingbo-dev/api/server/login'"
|
||||
]
|
||||
},
|
||||
"execution_count": 26,
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -44,7 +59,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 27,
|
||||
"execution_count": 3,
|
||||
"id": "2b330ee3-c006-4ab1-8558-59c51ac8d86f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -59,7 +74,7 @@
|
||||
" 'funcOperation': '获取token'}"
|
||||
]
|
||||
},
|
||||
"execution_count": 27,
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -70,7 +85,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 28,
|
||||
"execution_count": 4,
|
||||
"id": "dcb6100a-ed2b-4077-a1a9-361c6cb565f9",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
@ -87,15 +102,48 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 29,
|
||||
"execution_count": 5,
|
||||
"id": "22c0c7c4",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{'confirmFlg': False, 'data': {'accessToken': 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJhcGlfdGVzdCIsInRoIjoiOGE0NTc3ZGJkOTE5Njc1NzU4ZDU3OTk5YTFlODkxZmUiLCJsdCI6ImFwaSIsImlzcyI6IiIsInRtIjoiUEMiLCJleHAiOjE3MzM4NjAyODMsImp0aSI6IjliYTc4MzVkNmQyNDRjNTk4ODc0MjQ3OGU0ZDljNTJmIn0.ZvwSQ9_AoQ1Kn3Tdu8aZudrhC0aXzOsPUNkPP8DaDxo', 'md5Token': '2ca765c5b7aafb19c474b00a26c9fb3c'}, 'status': True}\n"
|
||||
"ename": "ConnectTimeout",
|
||||
"evalue": "HTTPConnectionPool(host='192.168.100.53', port=8080): Max retries exceeded with url: /jingbo-dev/api/server/login (Caused by ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x00000180160A7E50>, 'Connection to 192.168.100.53 timed out. (connect timeout=3)'))",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[1;31mTimeoutError\u001b[0m Traceback (most recent call last)",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connection.py:196\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 195\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 196\u001b[0m sock \u001b[38;5;241m=\u001b[39m connection\u001b[38;5;241m.\u001b[39mcreate_connection(\n\u001b[0;32m 197\u001b[0m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dns_host, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mport),\n\u001b[0;32m 198\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtimeout,\n\u001b[0;32m 199\u001b[0m source_address\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msource_address,\n\u001b[0;32m 200\u001b[0m socket_options\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msocket_options,\n\u001b[0;32m 201\u001b[0m )\n\u001b[0;32m 202\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m socket\u001b[38;5;241m.\u001b[39mgaierror \u001b[38;5;28;01mas\u001b[39;00m e:\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\util\\connection.py:85\u001b[0m, in \u001b[0;36mcreate_connection\u001b[1;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[0;32m 84\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m---> 85\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m err\n\u001b[0;32m 86\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m 87\u001b[0m \u001b[38;5;66;03m# Break explicitly a reference cycle\u001b[39;00m\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\util\\connection.py:73\u001b[0m, in \u001b[0;36mcreate_connection\u001b[1;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[0;32m 72\u001b[0m sock\u001b[38;5;241m.\u001b[39mbind(source_address)\n\u001b[1;32m---> 73\u001b[0m sock\u001b[38;5;241m.\u001b[39mconnect(sa)\n\u001b[0;32m 74\u001b[0m \u001b[38;5;66;03m# Break explicitly a reference cycle\u001b[39;00m\n",
|
||||
"\u001b[1;31mTimeoutError\u001b[0m: timed out",
|
||||
"\nThe above exception was the direct cause of the following exception:\n",
|
||||
"\u001b[1;31mConnectTimeoutError\u001b[0m Traceback (most recent call last)",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:789\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[1;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[0;32m 788\u001b[0m \u001b[38;5;66;03m# Make the request on the HTTPConnection object\u001b[39;00m\n\u001b[1;32m--> 789\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_request(\n\u001b[0;32m 790\u001b[0m conn,\n\u001b[0;32m 791\u001b[0m method,\n\u001b[0;32m 792\u001b[0m url,\n\u001b[0;32m 793\u001b[0m timeout\u001b[38;5;241m=\u001b[39mtimeout_obj,\n\u001b[0;32m 794\u001b[0m body\u001b[38;5;241m=\u001b[39mbody,\n\u001b[0;32m 795\u001b[0m headers\u001b[38;5;241m=\u001b[39mheaders,\n\u001b[0;32m 796\u001b[0m chunked\u001b[38;5;241m=\u001b[39mchunked,\n\u001b[0;32m 797\u001b[0m retries\u001b[38;5;241m=\u001b[39mretries,\n\u001b[0;32m 798\u001b[0m response_conn\u001b[38;5;241m=\u001b[39mresponse_conn,\n\u001b[0;32m 799\u001b[0m preload_content\u001b[38;5;241m=\u001b[39mpreload_content,\n\u001b[0;32m 800\u001b[0m decode_content\u001b[38;5;241m=\u001b[39mdecode_content,\n\u001b[0;32m 801\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mresponse_kw,\n\u001b[0;32m 802\u001b[0m )\n\u001b[0;32m 804\u001b[0m \u001b[38;5;66;03m# Everything went great!\u001b[39;00m\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:495\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[1;34m(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[0;32m 494\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 495\u001b[0m conn\u001b[38;5;241m.\u001b[39mrequest(\n\u001b[0;32m 496\u001b[0m method,\n\u001b[0;32m 497\u001b[0m url,\n\u001b[0;32m 498\u001b[0m body\u001b[38;5;241m=\u001b[39mbody,\n\u001b[0;32m 499\u001b[0m headers\u001b[38;5;241m=\u001b[39mheaders,\n\u001b[0;32m 500\u001b[0m chunked\u001b[38;5;241m=\u001b[39mchunked,\n\u001b[0;32m 501\u001b[0m preload_content\u001b[38;5;241m=\u001b[39mpreload_content,\n\u001b[0;32m 502\u001b[0m decode_content\u001b[38;5;241m=\u001b[39mdecode_content,\n\u001b[0;32m 503\u001b[0m enforce_content_length\u001b[38;5;241m=\u001b[39menforce_content_length,\n\u001b[0;32m 504\u001b[0m )\n\u001b[0;32m 506\u001b[0m \u001b[38;5;66;03m# We are swallowing BrokenPipeError (errno.EPIPE) since the server is\u001b[39;00m\n\u001b[0;32m 507\u001b[0m \u001b[38;5;66;03m# legitimately able to close the connection after sending a valid response.\u001b[39;00m\n\u001b[0;32m 508\u001b[0m \u001b[38;5;66;03m# With this behaviour, the received response is still readable.\u001b[39;00m\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connection.py:398\u001b[0m, in \u001b[0;36mHTTPConnection.request\u001b[1;34m(self, method, url, body, headers, chunked, preload_content, decode_content, enforce_content_length)\u001b[0m\n\u001b[0;32m 397\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mputheader(header, value)\n\u001b[1;32m--> 398\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mendheaders()\n\u001b[0;32m 400\u001b[0m \u001b[38;5;66;03m# If we're given a body we start sending that in chunks.\u001b[39;00m\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\http\\client.py:1289\u001b[0m, in \u001b[0;36mHTTPConnection.endheaders\u001b[1;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[0;32m 1288\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m CannotSendHeader()\n\u001b[1;32m-> 1289\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_send_output(message_body, encode_chunked\u001b[38;5;241m=\u001b[39mencode_chunked)\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\http\\client.py:1048\u001b[0m, in \u001b[0;36mHTTPConnection._send_output\u001b[1;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[0;32m 1047\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer[:]\n\u001b[1;32m-> 1048\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msend(msg)\n\u001b[0;32m 1050\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m message_body \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 1051\u001b[0m \n\u001b[0;32m 1052\u001b[0m \u001b[38;5;66;03m# create a consistent interface to message_body\u001b[39;00m\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\http\\client.py:986\u001b[0m, in \u001b[0;36mHTTPConnection.send\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m 985\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mauto_open:\n\u001b[1;32m--> 986\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconnect()\n\u001b[0;32m 987\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connection.py:236\u001b[0m, in \u001b[0;36mHTTPConnection.connect\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 235\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 236\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_new_conn()\n\u001b[0;32m 237\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host:\n\u001b[0;32m 238\u001b[0m \u001b[38;5;66;03m# If we're tunneling it means we're connected to our proxy.\u001b[39;00m\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connection.py:205\u001b[0m, in \u001b[0;36mHTTPConnection._new_conn\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 204\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SocketTimeout \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m--> 205\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ConnectTimeoutError(\n\u001b[0;32m 206\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 207\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnection to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhost\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m timed out. (connect timeout=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtimeout\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 208\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m 210\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
|
||||
"\u001b[1;31mConnectTimeoutError\u001b[0m: (<urllib3.connection.HTTPConnection object at 0x00000180160A7E50>, 'Connection to 192.168.100.53 timed out. (connect timeout=3)')",
|
||||
"\nThe above exception was the direct cause of the following exception:\n",
|
||||
"\u001b[1;31mMaxRetryError\u001b[0m Traceback (most recent call last)",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\requests\\adapters.py:667\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[1;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[0;32m 666\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 667\u001b[0m resp \u001b[38;5;241m=\u001b[39m conn\u001b[38;5;241m.\u001b[39murlopen(\n\u001b[0;32m 668\u001b[0m method\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mmethod,\n\u001b[0;32m 669\u001b[0m url\u001b[38;5;241m=\u001b[39murl,\n\u001b[0;32m 670\u001b[0m body\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mbody,\n\u001b[0;32m 671\u001b[0m headers\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mheaders,\n\u001b[0;32m 672\u001b[0m redirect\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m 673\u001b[0m assert_same_host\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m 674\u001b[0m preload_content\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m 675\u001b[0m decode_content\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m 676\u001b[0m retries\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_retries,\n\u001b[0;32m 677\u001b[0m timeout\u001b[38;5;241m=\u001b[39mtimeout,\n\u001b[0;32m 678\u001b[0m chunked\u001b[38;5;241m=\u001b[39mchunked,\n\u001b[0;32m 679\u001b[0m )\n\u001b[0;32m 681\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (ProtocolError, \u001b[38;5;167;01mOSError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\connectionpool.py:843\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[1;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)\u001b[0m\n\u001b[0;32m 841\u001b[0m new_e \u001b[38;5;241m=\u001b[39m ProtocolError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnection aborted.\u001b[39m\u001b[38;5;124m\"\u001b[39m, new_e)\n\u001b[1;32m--> 843\u001b[0m retries \u001b[38;5;241m=\u001b[39m retries\u001b[38;5;241m.\u001b[39mincrement(\n\u001b[0;32m 844\u001b[0m method, url, error\u001b[38;5;241m=\u001b[39mnew_e, _pool\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m, _stacktrace\u001b[38;5;241m=\u001b[39msys\u001b[38;5;241m.\u001b[39mexc_info()[\u001b[38;5;241m2\u001b[39m]\n\u001b[0;32m 845\u001b[0m )\n\u001b[0;32m 846\u001b[0m retries\u001b[38;5;241m.\u001b[39msleep()\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\urllib3\\util\\retry.py:519\u001b[0m, in \u001b[0;36mRetry.increment\u001b[1;34m(self, method, url, response, error, _pool, _stacktrace)\u001b[0m\n\u001b[0;32m 518\u001b[0m reason \u001b[38;5;241m=\u001b[39m error \u001b[38;5;129;01mor\u001b[39;00m ResponseError(cause)\n\u001b[1;32m--> 519\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m MaxRetryError(_pool, url, reason) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mreason\u001b[39;00m \u001b[38;5;66;03m# type: ignore[arg-type]\u001b[39;00m\n\u001b[0;32m 521\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIncremented Retry for (url=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m): \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, url, new_retry)\n",
|
||||
"\u001b[1;31mMaxRetryError\u001b[0m: HTTPConnectionPool(host='192.168.100.53', port=8080): Max retries exceeded with url: /jingbo-dev/api/server/login (Caused by ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x00000180160A7E50>, 'Connection to 192.168.100.53 timed out. (connect timeout=3)'))",
|
||||
"\nDuring handling of the above exception, another exception occurred:\n",
|
||||
"\u001b[1;31mConnectTimeout\u001b[0m Traceback (most recent call last)",
|
||||
"Cell \u001b[1;32mIn[5], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m token \u001b[38;5;241m=\u001b[39m get_head_auth_report()\n",
|
||||
"Cell \u001b[1;32mIn[4], line 2\u001b[0m, in \u001b[0;36mget_head_auth_report\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_head_auth_report\u001b[39m():\n\u001b[1;32m----> 2\u001b[0m login_res \u001b[38;5;241m=\u001b[39m requests\u001b[38;5;241m.\u001b[39mpost(url\u001b[38;5;241m=\u001b[39mlogin_pushreport_url, json\u001b[38;5;241m=\u001b[39mlogin_data, timeout\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m5\u001b[39m))\n\u001b[0;32m 3\u001b[0m text \u001b[38;5;241m=\u001b[39m json\u001b[38;5;241m.\u001b[39mloads(login_res\u001b[38;5;241m.\u001b[39mtext)\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(text)\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\requests\\api.py:115\u001b[0m, in \u001b[0;36mpost\u001b[1;34m(url, data, json, **kwargs)\u001b[0m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(url, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, json\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 104\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Sends a POST request.\u001b[39;00m\n\u001b[0;32m 105\u001b[0m \n\u001b[0;32m 106\u001b[0m \u001b[38;5;124;03m :param url: URL for the new :class:`Request` object.\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 112\u001b[0m \u001b[38;5;124;03m :rtype: requests.Response\u001b[39;00m\n\u001b[0;32m 113\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 115\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m request(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpost\u001b[39m\u001b[38;5;124m\"\u001b[39m, url, data\u001b[38;5;241m=\u001b[39mdata, json\u001b[38;5;241m=\u001b[39mjson, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\requests\\api.py:59\u001b[0m, in \u001b[0;36mrequest\u001b[1;34m(method, url, **kwargs)\u001b[0m\n\u001b[0;32m 55\u001b[0m \u001b[38;5;66;03m# By using the 'with' statement we are sure the session is closed, thus we\u001b[39;00m\n\u001b[0;32m 56\u001b[0m \u001b[38;5;66;03m# avoid leaving sockets open which can trigger a ResourceWarning in some\u001b[39;00m\n\u001b[0;32m 57\u001b[0m \u001b[38;5;66;03m# cases, and look like a memory leak in others.\u001b[39;00m\n\u001b[0;32m 58\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m sessions\u001b[38;5;241m.\u001b[39mSession() \u001b[38;5;28;01mas\u001b[39;00m session:\n\u001b[1;32m---> 59\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m session\u001b[38;5;241m.\u001b[39mrequest(method\u001b[38;5;241m=\u001b[39mmethod, url\u001b[38;5;241m=\u001b[39murl, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\requests\\sessions.py:589\u001b[0m, in \u001b[0;36mSession.request\u001b[1;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[0;32m 584\u001b[0m send_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 585\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeout\u001b[39m\u001b[38;5;124m\"\u001b[39m: timeout,\n\u001b[0;32m 586\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_redirects\u001b[39m\u001b[38;5;124m\"\u001b[39m: allow_redirects,\n\u001b[0;32m 587\u001b[0m }\n\u001b[0;32m 588\u001b[0m send_kwargs\u001b[38;5;241m.\u001b[39mupdate(settings)\n\u001b[1;32m--> 589\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msend(prep, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39msend_kwargs)\n\u001b[0;32m 591\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\requests\\sessions.py:703\u001b[0m, in \u001b[0;36mSession.send\u001b[1;34m(self, request, **kwargs)\u001b[0m\n\u001b[0;32m 700\u001b[0m start \u001b[38;5;241m=\u001b[39m preferred_clock()\n\u001b[0;32m 702\u001b[0m \u001b[38;5;66;03m# Send the request\u001b[39;00m\n\u001b[1;32m--> 703\u001b[0m r \u001b[38;5;241m=\u001b[39m adapter\u001b[38;5;241m.\u001b[39msend(request, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 705\u001b[0m \u001b[38;5;66;03m# Total elapsed time of the request (approximately)\u001b[39;00m\n\u001b[0;32m 706\u001b[0m elapsed \u001b[38;5;241m=\u001b[39m preferred_clock() \u001b[38;5;241m-\u001b[39m start\n",
|
||||
"File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\requests\\adapters.py:688\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[1;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[0;32m 685\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, ConnectTimeoutError):\n\u001b[0;32m 686\u001b[0m \u001b[38;5;66;03m# TODO: Remove this in 3.0.0: see #2811\u001b[39;00m\n\u001b[0;32m 687\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, NewConnectionError):\n\u001b[1;32m--> 688\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ConnectTimeout(e, request\u001b[38;5;241m=\u001b[39mrequest)\n\u001b[0;32m 690\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e\u001b[38;5;241m.\u001b[39mreason, ResponseError):\n\u001b[0;32m 691\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m RetryError(e, request\u001b[38;5;241m=\u001b[39mrequest)\n",
|
||||
"\u001b[1;31mConnectTimeout\u001b[0m: HTTPConnectionPool(host='192.168.100.53', port=8080): Max retries exceeded with url: /jingbo-dev/api/server/login (Caused by ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x00000180160A7E50>, 'Connection to 192.168.100.53 timed out. (connect timeout=3)'))"
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -105,7 +153,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 30,
|
||||
"execution_count": null,
|
||||
"id": "12077ead",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
@ -115,7 +163,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 31,
|
||||
"execution_count": null,
|
||||
"id": "a7ae21d1",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
||||
Loading…
Reference in New Issue
Block a user