BIDI_ML_INFO_EXTRACTION/BiddingKG/run_extract_server.py

# -*- coding: utf-8 -*-
"""
Created on Fri Jun  1 18:03:03 2018

@author: DONG
"""
import sys
import os
from flask import Flask, jsonify
from flask import abort
from flask import request


sys.path.append(os.path.dirname(__file__)+"/..")
os.environ["KERAS_BACKEND"] = "tensorflow"

app = Flask(__name__)
app.config['JSON_AS_ASCII'] = False

limit_num = "4"
os.environ["OMP_NUM_THREADS"] = limit_num # 1为一个核，设置为5的时候，系统显示用了10个核，不太清楚之间的具体数量关系
os.environ["OMP_NUM_THREADS"] = limit_num # export OMP_NUM_THREADS=1
os.environ["OPENBLAS_NUM_THREADS"] = limit_num # export OPENBLAS_NUM_THREADS=1
os.environ["MKL_NUM_THREADS"] = limit_num # export MKL_NUM_THREADS=1
os.environ["VECLIB_MAXIMUM_THREADS"] = limit_num # export VECLIB_MAXIMUM_THREADS=1
os.environ["NUMEXPR_NUM_THREADS"] = limit_num # export NUMEXPR_NUM_THREADS=1

import time
import uuid
import numpy as np
import ctypes
import inspect
from threading import Thread
import traceback
import json

os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
sys.path.append(os.path.abspath("."))


#自定义jsonEncoder
class MyEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        elif isinstance(obj, bytes):
            return str(obj, encoding='utf-8')
        elif isinstance(obj, (np.float_, np.float16, np.float32,
                              np.float64)):
            return float(obj)
        return json.JSONEncoder.default(self, obj)

def _async_raise(tid, exctype):
    """raises the exception, performs cleanup if needed"""
    tid = ctypes.c_long(tid)
    if not inspect.isclass(exctype):
        exctype = type(exctype)
    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(exctype))
    if res == 0:
        raise ValueError("invalid thread id")
    elif res != 1:
        ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, None)
        raise SystemError("PyThreadState_SetAsyncExc failed")

def stop_thread(thread):
    _async_raise(thread.ident, SystemExit)


def run_thread(data,list_result):
    # data = data.decode("utf8")
    # data = json.loads(data,encoding="utf8")
    k = str(uuid.uuid4())
    cost_time = dict()
    _doc_id = data.get("doc_id","")
    _title = data.get("title","")
    _content = data.get("content","")
    _page_time = data.get("page_time","")
    data_res = ""

    web_source_no = data.get("web_source_no","")
    web_source_name = data.get("web_source_name","")
    original_docchannel = data.get("original_docchannel","")
    # print("web_source_name:",web_source_name)
    is_fail = False
    try:
        if _content!="":
            data_res  = predict(_doc_id,_content,_title,_page_time,web_source_no=web_source_no,web_source_name=web_source_name,original_docchannel=original_docchannel)
        else:
            data_res = json.dumps({"success":False,"msg":"content not passed"})
            # is_fail = True


    except Exception as e:
        traceback.print_exc()
        data_res = json.dumps({"success":False,"msg":str(e)})
        is_fail = True
    # 以json形式返回结果
    #_resp = json.dumps(data_res,cls=MyEncoder)
    #log(str(data["flag"])+str(data))
    # log("done for doc_id:%s with result:%s"%(_doc_id,str(data_res)))
    list_result.append(data_res)
    if is_fail:
        list_result.append(is_fail)

@app.route("/test",methods=['POST'])
def test():
    from BiddingKG.dl.common.Utils import log
    from BiddingKG.dl.interface.extract import predict
    global predict,log
    _time = time.time()
    a = request.form.get("content")
    log("get form takes %.2fs"%(time.time()-_time))
    return json.dumps(sys.getsizeof(request.form)),201



@app.route('/content_extract', methods=['POST'])
def text_predict():
    from BiddingKG.dl.common.Utils import log
    from BiddingKG.dl.interface.extract import predict
    global predict,log
    _time = time.time()
    data = request.json

    status_code = 200
    list_result = []
    _timeout = data.get("timeout",400)
    log("get data cost:%.2fs"%((time.time()-_time)))
    t = Thread(target=run_thread,args=(data,list_result))
    start_time = time.time()
    t.start()
    t.join(_timeout)
    if t.is_alive():
        stop_thread(t)
        status_code = 302#超时被kill
        data_res = json.dumps({"success":False,"msg":"timeout"})
    else:
        # status_code += int((time.time()-start_time)%10+1)
        status_code = 201
        data_res = list_result[0]
        if len(list_result)>1 and list_result[1] ==True:
            status_code = 500
    _resp = data_res
    # _resp = predict(doc_id=_doc_id,text=_content,title=_title,page_time=_page_time)

    return _resp,status_code

def getPort(argv):
    port = 15030
    print(argv)
    for item in argv:
        _l = str(item).split("port=")
        if len(_l)>1:
            port = int(_l[-1])
            break
    return port

def getWorkers(argv):
    worker = 15
    for item in argv:
        _l = str(item).split("worker=")
        if len(_l)>1:
            worker = int(_l[-1])
            break
    return worker

def start_with_tornado(port,process_num):
    from tornado.wsgi import WSGIContainer
    from tornado.httpserver import HTTPServer
    from tornado.ioloop import IOLoop

    print("import ")
    http_server = HTTPServer(WSGIContainer(app))
    # http_server.listen(port) #shortcut for bind and start
    http_server.bind(port)
    http_server.start(process_num)
    IOLoop.instance().start()

def start_with_flask():
    port = getPort(argv=sys.argv)
    app.run(host='0.0.0.0', port=port, threaded=True, debug=False)
    log("ContentExtractor running")
    # app.run()

if __name__ == '__main__':
    port = getPort(argv=sys.argv)
    workers = getWorkers(argv=sys.argv)
    start_with_tornado(port,workers)
    pass