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- #!/usr/bin/env python
- # -*- coding: utf-8 -*-
- # time: 2023/3/27 16:29
- # file: app.py.py
- # author: David
- # company: shenyang JY
- import os
- import numpy as np
- np.random.seed(42)
- import pandas as pd
- from flask import Flask, request
- from startup import start_up
- from cache.clocking import Clock
- import gunicorn.app.base
- import threading
- import json, time
- from datetime import datetime
- app = Flask(__name__)
- with app.app_context():
- # import tensorflow as tf
- # global graph, sess
- # tf.compat.v1.set_random_seed(1234)
- # graph = tf.compat.v1.get_default_graph()
- # session_conf = tf.compat.v1.ConfigProto(intra_op_parallelism_threads=1, inter_op_parallelism_threads=1)
- # sess = tf.compat.v1.Session(graph=graph, config=session_conf)
- logger, va, args, req, process, features, fmi = start_up() # 程序初始化
- # model = fmi.fmi_model
- # 实例化定时任务类
- clock = Clock(logger=logger, args=args, process=process, features=features, fmi=fmi)
- logger.info("定时任务类初始化")
- # clock.calculate_coe(cluster=True) # 实际场站中要先修模
- clock.update_thread() # 定时任务开启
- result = {
- "errorCode": 1,
- "msg": "无异常",
- "res": []
- }
- @app.before_request
- def update_config():
- print("-----------------beofore_request------------------")
- global opt
- opt = args.parse_args_and_yaml()
- va.opt = opt
- process.opt = opt
- va.status = 0
- class StandaloneApplication(gunicorn.app.base.BaseApplication):
- def __init__(self, app, options=None):
- self.options = options or {}
- self.application = app
- super().__init__()
- def load_config(self):
- config = {key: value for key, value in self.options.items()
- if key in self.cfg.settings and value is not None}
- for key, value in config.items():
- self.cfg.set(key.lower(), value)
- def load(self):
- return self.application
- @app.route('/neu', methods=['post'])
- def cdq():
- try:
- start = time.time()
- # 初始化请求处理类
- nwp, dq, history_dq, history_rp, env = req.get_form_data(request)
- print("----进入预处理算法----")
- history_rp = va.validate_power(history_rp, env)
- history_rp.drop(['C_REAL_VALUE'], axis=1, inplace=True)
- history_rp.rename(columns={'NEW_RP': 'C_REAL_VALUE'}, inplace=True)
- s1 = time.time()
- logger.info(f"1解析数据验证-执行时间:{(s1 - start) * 1000}毫秒")
- nwp = pd.merge(nwp, dq, on='C_TIME')
- his = pd.merge(history_rp, history_dq, on='C_TIME')
- his = pd.merge(env, his, on='C_TIME')
- nwp = va.validate_nwp(nwp)
- his = va.validate_env(his)
- va.validate_authentic(dq, history_dq)
- start1 = time.time()
- logger.info(f"2解析数据验证-执行时间:{(start1 - s1) * 1000}毫秒")
- mean = [opt.mean.get(x) for x in opt.nwp_columns if x not in ['C_TIME']]
- std = [opt.std.get(x) for x in opt.nwp_columns if x not in ['C_TIME']]
- nwp = nwp[opt.nwp_columns]
- _, _, nwp_features = clock.normalize(nwp, mean=mean, std=std)
- mean = [opt.mean.get(x) for x in opt.env_columns if x not in ['C_TIME']]
- std = [opt.std.get(x) for x in opt.env_columns if x not in ['C_TIME']]
- his = his[opt.env_columns]
- _, _, env_features = clock.normalize(his, mean=mean, std=std)
- start2 = time.time()
- logger.info(f"归一化-执行时间:{(start2 - start1) * 1000}毫秒")
- data_test, env = process.get_test_data(nwp_features, env_features)
- test_X = features.get_realtime_data(data_test, env)
- start3 = time.time()
- logger.info(f"特征处理-执行时间:{(start3 - start2) * 1000}毫秒")
- logger.info("-----进入超短期预测算法-----")
- # with graph.as_default():
- # with sess.as_default():
- res = fmi.fmi_model.predict(test_X, batch_size=1)[0]
- start4 = time.time()
- logger.info(f"算法推理-执行时间:{(start4 - start3) * 1000}毫秒")
- # res = fmi.fmi_model.predict(opt, test_X)[0]
- res = np.array([r*opt.std['C_REAL_VALUE'] + opt.mean['C_REAL_VALUE'] for r in res])
- res = np.array([r*opt.calculate['coe'] + opt.calculate['abs'] for r in res])
- res[res < 0] = 0
- res[res > opt.cap] = opt.cap
- res = np.around(res, decimals=2)
- times = dq['C_TIME'].dt.strftime('%Y-%m-%d %H:%M:%S').values
- res = [{"C_TIME": times[i], "CDQ_VALUE": x} for i, x in enumerate(res)]
- end = time.time()
- logger.info(f"反归一化-执行时间:{(end - start4) * 1000}毫秒")
- print(f"总时间:{(end - start) * 1000}毫秒")
- logger.info("----{}".format(res))
- result["errorCode"] = 1
- result["res"] = res
- result["msg"] = "无异常"
- return json.dumps(result, ensure_ascii=False)
- except Exception as e:
- logger.error(e.args)
- result["errorCode"] = va.status if va.status != 1 else 0
- result["res"] = None
- result["msg"] = e.args
- return json.dumps(result, ensure_ascii=False)
- @app.route('/forecastVersion', methods=['get'])
- def forecast_version():
- opt = args.parse_args_and_yaml()
- return opt.version
- def date_diff(current_dt, repair_dt):
- format_pattern = '%Y-%m-%d'
- difference = (datetime.strptime(current_dt, format_pattern) - datetime.strptime(repair_dt, format_pattern))
- return difference.days
- @app.route('/last_model_update', methods=['get'])
- def last_model_update():
- dt = time.strftime('%Y-%m-%d', time.localtime(time.time()))
- repair, repair_dt = int(opt.repair_model_cycle), opt.authentication['repair']
- if repair_dt == 'null':
- return {"model_status": 0, "time": 'null', "msg": "未修模"}
- elif date_diff(dt, repair_dt) > repair*2:
- return {"model_status": 1, "time": repair_dt, "msg": "距上次修模已过{}天".format(date_diff(dt, repair_dt))}
- else:
- return {"model_status": 2, "time": repair_dt, "msg": "修模正常"}
- if __name__ == "__main__":
- opt = args.parse_args_and_yaml()
- current_path = os.path.dirname(__file__)
- gunicorn_config = {
- 'bind': '%s:%s' % ('0.0.0.0', str(opt.port)),
- 'certfile': current_path + '/ssl/server.pem',
- 'keyfile': current_path + '/ssl/server.key',
- "check_config": True,
- "worker_class": "gthread",
- "workers": 1,
- "threads": 1,
- 'timeout': 100,
- "loglevel": "info",
- "access_log_format": "gunicorn %(h)s - %(t)s - %(r)s - %(s)s - %(f)s",
- "backlog": 30,
- }
- threading.Thread(target=clock.calculate_coe, args=(True,)).start()
- # # 启动服务
- StandaloneApplication(app, options=gunicorn_config).run()
- # app.run(host='0.0.0.0', port=7999, debug=False)
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