get_sentiments.py

from flask import Flask, render_template, request, redirect, url_for
from joblib import load
from .get_tweets import get_related_tweets

# load the pipeline object
pipeline = load('text_classification.joblib')

# get result for each text query
def requestResults(name):
    # get tweet text
    tweets = get_related_tweets(name)
    # get prediction
    tweets['prediction'] = pipeline.predict(tweets['tweet_text'])
    # get the value counts of different labels predicted
    data = str(tweets.prediction.value_counts()) + '\n\n'
    return data + str(tweets)

# start Flask
app = Flask(__name__)

@app.route('/')
def home():
    return render_template('home.html')

# when the post method is detected, redirect to success function
@app.route('/', methods=['POST', 'GET'])
def get_data():
    if request.method == 'POST':
        user = request.form['search']
        return redirect(url_for('success',name=user))

# get data for requested query
@app.route('/success/<name>')
def success(name):
    return "<xmp>" + str(requestResults(name)) + " </xmp>"

if __name__ == '__main__':
    app.run(debug=True)