#!/usr/bin/env python3
import os
import logging
import tempfile
import requests

from urllib.parse import urljoin

from cnn_classifier import Classifier


def run_everything(parameters: dict):
    tag = parameters['tag']

    sample_file_handle, sample_file_path = tempfile.mkstemp(prefix=f"{tag}_", suffix=".wav")
    model_file_handle, model_file_path = tempfile.mkstemp(suffix=".json")
    weights_file_handle, weights_file_path = tempfile.mkstemp(suffix=".h5")

    try:

        # Download Sample

        logging.info(f"Downloading sample: {tag}")
        r = requests.get(f"http://storage-service/object/{tag}")
        with open(sample_file_handle, 'wb') as f:
            f.write(r.content)

        logging.debug(f"Downloaded sample to {sample_file_path}")

        # Download model

        model_root_url = "http://model-service/model/cnn/$default"

        logging.debug("Fetching model info...")
        r = requests.get(model_root_url)
        r.raise_for_status()

        model_details = r.json()

        logging.debug("Fetching model file...")
        r = requests.get(urljoin(model_root_url, model_details['files']['model']))  # Fun fact: this would support external urls
        r.raise_for_status()

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

        logging.debug("Fetching weights file...")
        r = requests.get(urljoin(model_root_url, model_details['files']['weights']))
        r.raise_for_status()

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

        # magic happens here
        classifier = Classifier(model_file_path, weights_file_path)
        results = classifier.predict(sample_file_path)

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

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

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

    response = {
        "tag": tag,
        "probability": 1.0 if results[0] == model_details['target_class_name'] else 0.0,
        "model": model_details['id']
    }

    logging.info(f"Classification done!")
    logging.debug(f"Results: {response}")

    return response