app.py

from sklearn import tree
from sklearn import neighbors
from flask import Flask, jsonify
import json

app = Flask(__name__)

@app.route('/v1/prediction', methods=['GET'])
def postData():
     #[size,weight, texture]
     X = [[181, 80, 44], [177, 70, 43], [160, 60, 38], [154, 54, 37], [166, 65, 40],
          [190, 90, 47], [175, 64, 39],
          [177, 70, 40], [159, 55, 37], [171, 75, 42], [181, 85, 43]]

     Y = ['apple', 'apple', 'orange', 'orange', 'apple', 'apple', 'orange', 'orange',
          'orange', 'apple', 'apple']

     #classifier - DecisionTreeClassifier
     clf_tree = tree.DecisionTreeClassifier();
     clf_tree = clf_tree.fit(X,Y);

     #classifier - neighbour
     clf_neighbors = neighbors.KNeighborsClassifier();
     clf_neighbors = clf_neighbors.fit(X,Y);

     #test_data
     test_data = [[190,70,42],[172,64,39],[182,80,42]];

     #prediction
     prediction_tree = clf_tree.predict(test_data);
     prediction_neighbors = clf_neighbors.predict(test_data);

     return json.dumps(prediction_neighbors[0])

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=80, debug=True)