#!/usr/bin/env python

import sys, json
sys.path.append('/home/sentiment-analyser/')

from threading import Thread

from src.utils.jsonLogger import setup_logging, log
import analyser.sentimentAnalyser as sentimentAnalyser

from flask import Flask, request

from probes.probes import runFlaskProbes

app = Flask(__name__)
analyser = sentimentAnalyser.get_sentiment()

@app.route('/sentiment', methods=['GET'])
def tweetPredict():
    tweet = request.args.get('tweet')
    syncId = request.headers.get('X-CRYPTO-Sync-ID')

    log("Receiving Tweet to classify [{}] for [{}]".format(tweet, syncId), 'INFO')

    result = analyser.get_vader_sentiment(tweet)

    log("Returning classification result of [{}]".format(result), 'INFO')

    return json.dumps({'result': result, 'tweet': tweet}), 200, {'ContentType':'application/json'}

@app.route('/sentimentProbeTest', methods=['GET'])
def sentimentProbeTest():
    return json.dumps({'result':  {'Score': {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0}, 'Compound': 0.0}, 'tweet': 'Fake Text'}), 200, {'ContentType':'application/json'}

def callSentimentAnalyser():
    analyser.set_newSentiment()

    app.run(port=9090, host="0.0.0.0")

def callProbes():
    runFlaskProbes()

if __name__ == '__main__':
    setup_logging()

    log("Starting Sentiment Analyser...", 'INFO')
    sys.stdout.flush()

    Thread(target=callProbes).start()

    Thread(target=callSentimentAnalyser).start()