#Download Facebook Comments

import requests

import requests

import pandas as pd

import os, sys

token = ""

try:

token = os.environ['FB_TOKEN']

except:

print ("Set FB_TOKEN variable")

#sys.exit(-1)

fb_pageid = "228735667216"

fb_postid = "10154922624762217"

commentlst = []

datelst = []

url = "https://graph.facebook.com/v2.9/"+ fb_pageid +"_"+ fb_postid +"/comments?limit=100&access_token="+token

while(True):

posts = requests.get(url)

posts_json = posts.json()

for x1 in posts_json['data']:

commentlst.append(x1.get('message').encode('utf-8').strip())

datelst.append(x1.get('created_time'))

next_page = ""

try:

next_page = posts_json['paging']['next']

url = next_page

except:

break

if not next_page: break

print ("Count: %s, Next Page: %s" % ( len(commentlst), url))

print ("\nGenerating JSON File")

df = pd.DataFrame({'comment': commentlst, 'dates': datelst})

df['dates'] = pd.to_datetime(df['dates'])

df['day_of_week'] = df['dates'].dt.weekday_name

df['year'] = df['dates'].dt.year

df['month'] = df['dates'].dt.month

df['count'] = 1

df.to_json('comment_data.json')

#Generate Sentimental Results

import requests

import json

from google.cloud import language, exceptions

client = language.Client()

# export GOOGLE_APPLICATION_CREDENTIALS environment variable

with open('comment_data.json') as data_file:

data = json.load(data_file)

sentiment_list = []

for x1,y1 in data['comment'].items():

try:

document = client.document_from_text(y1)

sentiment = document.analyze_sentiment().sentiment

sentiment_list.append({"id": x1, "comment": y1, "sentiment_score": sentiment.score, "sentiment_magnitude": sentiment.magnitude })

print ("Pass")

except:

print ("Fail")

with open('sentiment_comments.json', 'w') as outfile:

json.dump(sentiment_list, outfile)