BIDI_ML_INFO_EXTRACTION/BiddingKG/dl_dev/labelServer/label_web_server2.py

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

@author: DONG
"""
import sys
import os
import codecs
sys.path.append(os.path.abspath("../.."))
print(sys.path)
from flask import Flask, jsonify
from flask import abort
from flask import request
import logging
import time
import BiddingKG.dl.interface.predictor as predictor
import BiddingKG.dl.interface.Preprocessing as Preprocessing
from Entity2DB import *
import psycopg2
import glob

os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" 
os.environ["CUDA_VISIBLE_DEVICES"] = ""

premPredict = predictor.PREMPredict()
epcPredict = predictor.EPCPredict()
codeNamePredict = predictor.CodeNamePredict()


for file in glob.glob("C:\\Users\\User\\Desktop\\20190416要素\\*.html"):
    
    try:
        conn = psycopg2.connect(dbname="article_label",user="postgres",password="postgres",host="192.168.2.101")
        
        #id = "比地_101_61298166.html"
        #content = codecs.open("C:\\Users\\User\\Desktop\\20190416要素\\"+id,"r",encoding="utf8").read()
        id = file.split("\\")[-1]
        content = codecs.open(file,"r",encoding="utf8").read()
        
        sql = " select count(1) from articles_processed where id='"+id+"' "
        cursor = conn.cursor()
        cursor.execute(sql)
        rows = cursor.fetchall()
        if rows[0][0]>0:
            continue
        
                       
        list_articles,list_sentences,list_entitys = Preprocessing.get_preprocessed([[id,content]])
        
        role_datas = Preprocessing.search_role_data(list_sentences,list_entitys)
        money_datas = Preprocessing.search_money_data(list_sentences,list_entitys)
        person_datas = Preprocessing.search_person_data(list_sentences,list_entitys)
        
        premPredict.predict(role_datas,money_datas)
        epcPredict.predict(person_datas)
            
        
        codeName = codeNamePredict.predict(list_articles)
        
        
        persistArticle(conn, list_articles,codeName)
        for sentences in list_sentences:
            persistSentence(conn, sentences)
        for entitys in list_entitys:
            persistEntity(conn, entitys)
    
    except Exception as e:
        pass
    
    finally:    
    
        conn.commit()
        conn.close()