先安装Flask,
pip install flask
在来个脚本
# -*- coding: utf-8 -*-
from flask import Flask,request
from pickle import load
from jieba import cut
from sklearn.feature_extraction.text import TfidfVectorizer
app = Flask(__name__)
if 'clfpa' not in dir():
# 加载模型
with open('../model/clfpa.model',mode='rb') as f:
clfpa = load(f)
if 'a_list' not in dir():
# 加载词汇列表
with open('../data/blogswordslist.pickle',mode='rb') as f2:
vocabulary = list(load(f2))
print("加载模型与词汇表成功")
@app.route('/',methods=['POST'])
def docclassify():
docu = request.get_json()
stop_words = list(['\n','','。',',','|','【','】',':',' ','...','/','.','_','+','=','[',']','-'