algorithm_platform/post_processing/pre_post_processing.py

import pandas as pd
from flask import Flask,request,jsonify
import time
import logging
import traceback

from common.database_dml import get_data_from_mongo,insert_data_into_mongo

app = Flask('post_processing——service')


@app.route('/hello', methods=['POST'])
def hello():
    return jsonify(message='Hello, World!')


def  predict_result_adjustment(df, args):
    col_time = args['col_time']
    col_adjust = args['col_adjust']
    ratio_dict = eval(args['ratio'])
    df['hour'] = df[col_time].apply(lambda x:x[11:13])
    rates = ratio_dict.keys()
    for rate in rates:
        hours = ratio_dict[rate]
        df.loc[df['hour'].isin(hours), col_adjust] *= float(rate)
    return df.drop('hour', axis=1)


@app.route('/pre_post_processing', methods=['POST'])
def data_join():
    # 获取程序开始时间  
    start_time = time.time()  
    result = {}
    success = 0
    print("Program starts execution!")
    try:
        args = request.values.to_dict()
        print('args',args)
        logger.info(args)
        df_pre = get_data_from_mongo(args)
        res_df = predict_result_adjustment(df_pre, args)
        insert_data_into_mongo(res_df,args)
        success = 1
    except Exception as e:
        my_exception = traceback.format_exc()
        my_exception.replace("\n","\t")
        result['msg'] = my_exception
    end_time = time.time()
    result['success'] = success
    result['args'] = args
    result['start_time'] = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(start_time))
    result['end_time'] = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(end_time))
    print("Program execution ends!")
    return result


if __name__=="__main__":
    print("Program starts execution!")
    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
    logger = logging.getLogger("post_processing")
    from waitress import serve
    serve(app, host="0.0.0.0", port=10107)
    print("server start!")