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get_fb_comments_from_fb.py
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get_fb_comments_from_fb.py
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import json
import datetime
import csv
import time
try:
from urllib.request import urlopen, Request
except ImportError:
from urllib2 import urlopen, Request
app_id = "377742929333901"
app_secret = "922375a7e0cd8aa306b214de0c1d2223" # DO NOT SHARE WITH ANYONE!
file_id = "184096565021911"
access_token = app_id + "|" + app_secret
def request_until_succeed(url):
req = Request(url)
success = False
while success is False:
try:
response = urlopen(req)
if response.getcode() == 200:
success = True
except Exception as e:
print(e)
time.sleep(5)
print("Error for URL {}: {}".format(url, datetime.datetime.now()))
print("Retrying.")
return response.read()
# Needed to write tricky unicode correctly to csv
def unicode_decode(text):
try:
return text.encode('utf-8').decode()
except UnicodeDecodeError:
return text.encode('utf-8')
def getFacebookCommentFeedUrl(base_url):
# Construct the URL string
fields = "&fields=id,message,reactions.limit(0).summary(true)" + \
",created_time,comments,from,attachment"
url = base_url + fields
return url
def getReactionsForComments(base_url):
reaction_types = ['like', 'love', 'wow', 'haha', 'sad', 'angry']
reactions_dict = {} # dict of {status_id: tuple<6>}
for reaction_type in reaction_types:
fields = "&fields=reactions.type({}).limit(0).summary(total_count)".format(
reaction_type.upper())
url = base_url + fields
data = json.loads(request_until_succeed(url))['data']
data_processed = set() # set() removes rare duplicates in statuses
for status in data:
id = status['id']
count = status['reactions']['summary']['total_count']
data_processed.add((id, count))
for id, count in data_processed:
if id in reactions_dict:
reactions_dict[id] = reactions_dict[id] + (count,)
else:
reactions_dict[id] = (count,)
return reactions_dict
def processFacebookComment(comment, status_id, parent_id=''):
# The status is now a Python dictionary, so for top-level items,
# we can simply call the key.
# Additionally, some items may not always exist,
# so must check for existence first
comment_id = comment['id']
comment_message = '' if 'message' not in comment or comment['message'] \
is '' else unicode_decode(comment['message'])
print(str(comment['message']).encode('unicode-escape'))
# comment_author = unicode_decode(comment['from']['name'])
num_reactions = 0 if 'reactions' not in comment else \
comment['reactions']['summary']['total_count']
if 'attachment' in comment:
attachment_type = comment['attachment']['type']
attachment_type = 'gif' if attachment_type == 'animated_image_share' \
else attachment_type
attach_tag = "[[{}]]".format(attachment_type.upper())
comment_message = attach_tag if comment_message is '' else \
comment_message + " " + attach_tag
# Time needs special care since a) it's in UTC and
# b) it's not easy to use in statistical programs.
comment_published = datetime.datetime.strptime(
comment['created_time'], '%Y-%m-%dT%H:%M:%S+0000')
comment_published = comment_published + datetime.timedelta(hours=-5) # EST
comment_published = comment_published.strftime(
'%Y-%m-%d %H:%M:%S') # best time format for spreadsheet programs
# Return a tuple of all processed data
return (comment_id, status_id, parent_id, comment_message,
comment_published, num_reactions)
def scrapeFacebookPageFeedComments(page_id, access_token):
with open('{}_facebook_comments.csv'.format(file_id), 'w') as file:
w = csv.writer(file)
w.writerow(["comment_id", "status_id", "parent_id", "comment_message",
"comment_published", "num_reactions",
"num_likes", "num_loves", "num_wows", "num_hahas",
"num_sads", "num_angrys", "num_special"])
num_processed = 0
scrape_starttime = datetime.datetime.now()
after = ''
base = "https://graph.facebook.com/v2.9"
parameters = "/?limit={}&access_token={}".format(
100, access_token)
print("Scraping {} Comments From Posts: {}\n".format(
file_id, scrape_starttime))
with open('{}_facebook_statuses.csv'.format(file_id), 'r') as csvfile:
reader = csv.DictReader(csvfile)
# Uncomment below line to scrape comments for a specific status_id
# reader = [dict(status_id='5550296508_10154352768246509')]
for status in reader:
has_next_page = True
while has_next_page:
node = "/{}/comments".format(status['status_id'])
after = '' if after is '' else "&after={}".format(after)
base_url = base + node + parameters + after
url = getFacebookCommentFeedUrl(base_url)
# print(url)
comments = json.loads(request_until_succeed(url))
reactions = getReactionsForComments(base_url)
for comment in comments['data']:
comment_data = processFacebookComment(
comment, status['status_id'])
reactions_data = reactions[comment_data[0]]
# calculate thankful/pride through algebra
num_special = comment_data[5] - sum(reactions_data)
w.writerow(comment_data + reactions_data +
(num_special, ))
if 'comments' in comment:
has_next_subpage = True
sub_after = ''
while has_next_subpage:
sub_node = "/{}/comments".format(comment['id'])
sub_after = '' if sub_after is '' else "&after={}".format(
sub_after)
sub_base_url = base + sub_node + parameters + sub_after
sub_url = getFacebookCommentFeedUrl(
sub_base_url)
sub_comments = json.loads(
request_until_succeed(sub_url))
sub_reactions = getReactionsForComments(
sub_base_url)
for sub_comment in sub_comments['data']:
sub_comment_data = processFacebookComment(
sub_comment, status['status_id'], comment['id'])
sub_reactions_data = sub_reactions[
sub_comment_data[0]]
num_sub_special = sub_comment_data[
5] - sum(sub_reactions_data)
w.writerow(str(sub_comment_data +
sub_reactions_data + (num_sub_special,)).encode('unicode-escape'))
num_processed += 1
if num_processed % 100 == 0:
print("{} Comments Processed: {}".format(
num_processed,
datetime.datetime.now()))
if 'paging' in sub_comments:
if 'next' in sub_comments['paging']:
sub_after = sub_comments[
'paging']['cursors']['after']
else:
has_next_subpage = False
else:
has_next_subpage = False
# output progress occasionally to make sure code is not
# stalling
num_processed += 1
if num_processed % 100 == 0:
print("{} Comments Processed: {}".format(
num_processed, datetime.datetime.now()))
if 'paging' in comments:
if 'next' in comments['paging']:
after = comments['paging']['cursors']['after']
else:
has_next_page = False
else:
has_next_page = False
print("\nDone!\n{} Comments Processed in {}".format(
num_processed, datetime.datetime.now() - scrape_starttime))
if __name__ == '__main__':
scrapeFacebookPageFeedComments(file_id, access_token)
# The CSV can be opened in all major statistical programs. Have fun! :)