#!/usr/bin/env python3
import os
from flask import request, jsonify
from flask_classful import FlaskView
from utils import json_required
import requests
import tempfile

from pyAudioAnalysis.audioTrainTest import load_model, load_model_knn, classifier_wrapper


class ClassifyView(FlaskView):

    @json_required
    def post(self):

        request.json

        _, temp_model_name = tempfile.mkstemp()
        temp_means_name = temp_model_name + "MEANS"

        r = requests.get("http://model-service/model/$default/details")
        r.raise_for_status()

        model_details = r.json()

        try:

            r = requests.get("http://model-service/model/$default")
            r.raise_for_status()

            with open(temp_model_name, 'wb') as f:
                f.write(r.content)

            r = requests.get("http://model-service/model/$default?means")
            r.raise_for_status()

            with open(temp_means_name, 'wb') as f:
                f.write(r.content)

            if model_details['type'] == 'knn':
                classifier, mean, std, classes, mid_window, mid_step, short_window, short_step, compute_beat \
                    = load_model_knn(temp_model_name)

            else:
                classifier, mean, std, classes, mid_window, mid_step, short_window, short_step, compute_beat \
                    = load_model(temp_model_name)

            # class_id, probability = classifier_wrapper(classifier, model_details['type'], feature_vector)

        finally:  # bruuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuh
            try:
                os.remove(temp_model_name)
            except FileNotFoundError:
                pass

            try:
                os.remove(temp_means_name)
            except FileNotFoundError:
                pass

        return jsonify({})