rest_server_with_ai.py

from flask import Flask, request
from flask_restful import Resource, Api
from sqlalchemy import create_engine
import json
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import load_iris



app = Flask(__name__)
api = Api(app)

class Employees(Resource):
    def get(self):
        return json.dumps({'employees': ['david','lili','jack']} )

class Tracks(Resource):
    def get(self):
        result = {1:'david', 2:'lili', 3:'jack'}
        return json.dumps(result)

class Employees_Name(Resource):
    def get(self, employee_id):
        employees = {1:'david', 2:'lili', 3:'jack'}
        employee_id = int(employee_id)
        if(employee_id in employees):
            return employees[employee_id]
        else:
            return 'no_employee_with_id_{0}'.format(employee_id)
        

class AiTest(Resource):
    def get(self):
        irisdata = load_iris()
        x_data = irisdata.data
        y_data = irisdata.target
        
        x_train, x_test, y_train, y_test = train_test_split(x_data, y_data, test_size=0.50, random_state=42)
        model = RandomForestClassifier()
        model.fit(x_train,y_train)
        score = model.score(x_test,y_test)
        return json.dumps({'score':score})

        
api.add_resource(Employees, '/employees') # Route_1
api.add_resource(Tracks, '/tracks') # Route_2
api.add_resource(Employees_Name, '/employees/<employee_id>') # Route_3
api.add_resource(AiTest, '/score') # Route_4


if __name__ == '__main__':
     app.run(port='5002')




'''
http://127.0.0.1:5002/employees shows ids of all the employees 
http://127.0.0.1:5002/tracks shows tracks details
http://127.0.0.1:5002/employees/3 shows details of employee whose employeeid is 3
'''