/
starter.py
47 lines (36 loc) · 1.66 KB
/
starter.py
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#!/usr/bin/python
from flask import Flask, request, jsonify
from flask import render_template
from sentimental_analysis import Corpus
from sentimental_analysis import Classifier
app = Flask(__name__)
# @app.route("/co", methods=['GET', 'POST'])
# def co():
# if request.method == 'POST':
# positive_training_data_path = './data/positive_x'
# negative_training_data_path = './data/negative_x'
# positive_corpus = Corpus()
# negative_corpus = Corpus()
# positive_corpus.load_from_directory(positive_training_data_path)
# negative_corpus.load_from_directory(negative_training_data_path)
# classifier = Classifier(positive_corpus, negative_corpus)
# classifying_output = classifier.classify(request.form['nicedit-message'])
# print request.form
# return 'a'
# return jsonify(prob=classifying_output['probability'], sentiment=classifying_output['sentiment'], )
@app.route("/", methods=['GET', 'POST'])
def index():
if request.method == 'POST':
positive_training_data_path = './data/positive_x'
negative_training_data_path = './data/negative_x'
positive_corpus = Corpus()
negative_corpus = Corpus()
positive_corpus.load_from_directory(positive_training_data_path)
negative_corpus.load_from_directory(negative_training_data_path)
classifier = Classifier(positive_corpus, negative_corpus)
classifying_output = classifier.classify(request.form['nicedit-message'])
return render_template('index.html', co=classifying_output)
return render_template('index.html')
if __name__ == "__main__":
app.debug = True
app.run()