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get_fb_posts_fb_page.py
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get_fb_posts_fb_page.py
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import urllib2
import json
import datetime
import csv
import time
import settings
from MySQL_Actions import MySQL_Codes
app_id = settings.app_id
app_secret = settings.app_secret # DO NOT SHARE WITH ANYONE!
#page_id = settings.page_id_for_posts
access_token = app_id + "|" + app_secret
db_action = MySQL_Codes()
def work_as_scheduled(spage_id):
scrapeFacebookPageFeedStatus(spage_id, access_token)
def reset_deleted_tag():
db_action.ID_checker_already_deleted = {}
def request_until_succeed(url):
req = urllib2.Request(url)
success = False
while success is False:
try:
response = urllib2.urlopen(req)
if response.getcode() == 200:
success = True
except Exception, e:
print e
time.sleep(5)
print "Error for URL %s: %s" % (url, datetime.datetime.now())
print "Retrying."
return response.read()
# Needed to write tricky unicode correctly to csv
def unicode_normalize(text):
return text.translate({ 0x2018:0x27, 0x2019:0x27, 0x201C:0x22, 0x201D:0x22,
0xa0:0x20 }).encode('utf-8')
def getFacebookPageFeedData(page_id, access_token, num_statuses):
# Construct the URL string; see http://stackoverflow.com/a/37239851 for
# Reactions parameters
base = "https://graph.facebook.com/v2.6"
node = "/%s/posts" % page_id
fields = "/?fields=message,link,created_time,type,name,id," + \
"comments.limit(0).summary(true),shares,reactions" + \
".limit(0).summary(true)"
parameters = "&limit=%s&access_token=%s" % (num_statuses, access_token)
url = base + node + fields + parameters
# retrieve data
data = json.loads(request_until_succeed(url))
return data
def getReactionsForStatus(status_id, access_token):
# See http://stackoverflow.com/a/37239851 for Reactions parameters
# Reactions are only accessable at a single-post endpoint
base = "https://graph.facebook.com/v2.6"
node = "/%s" % status_id
reactions = "/?fields=" \
"reactions.type(LIKE).limit(0).summary(total_count).as(like)" \
",reactions.type(LOVE).limit(0).summary(total_count).as(love)" \
",reactions.type(WOW).limit(0).summary(total_count).as(wow)" \
",reactions.type(HAHA).limit(0).summary(total_count).as(haha)" \
",reactions.type(SAD).limit(0).summary(total_count).as(sad)" \
",reactions.type(ANGRY).limit(0).summary(total_count).as(angry)"
parameters = "&access_token=%s" % access_token
url = base + node + reactions + parameters
# retrieve data
data = json.loads(request_until_succeed(url))
return data
def processFacebookPageFeedStatus(status, access_token):
# 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
status_id = status['id']
status_message = '' if 'message' not in status.keys() else \
unicode_normalize(status['message'])
link_name = '' if 'name' not in status.keys() else \
unicode_normalize(status['name'])
status_type = status['type']
status_link = '' if 'link' not in status.keys() else \
unicode_normalize(status['link'])
status_author = ''
# Time needs special care since a) it's in UTC and
# b) it's not easy to use in statistical programs.
status_published = datetime.datetime.strptime(
status['created_time'],'%Y-%m-%dT%H:%M:%S+0000')
status_published = status_published + \
datetime.timedelta(hours=-5) # EST
status_published = status_published.strftime(
'%Y-%m-%d %H:%M:%S') # best time format for spreadsheet programs
# Nested items require chaining dictionary keys.
num_reactions = 0 if 'reactions' not in status else \
status['reactions']['summary']['total_count']
num_comments = 0 if 'comments' not in status else \
status['comments']['summary']['total_count']
num_shares = 0 if 'shares' not in status else status['shares']['count']
# Counts of each reaction separately; good for sentiment
# Only check for reactions if past date of implementation:
# http://newsroom.fb.com/news/2016/02/reactions-now-available-globally/
reactions = getReactionsForStatus(status_id, access_token) if \
status_published > '2016-02-24 00:00:00' else {}
num_likes = 0 if 'like' not in reactions else \
reactions['like']['summary']['total_count']
# Special case: Set number of Likes to Number of reactions for pre-reaction
# statuses
num_likes = num_reactions if status_published < '2016-02-24 00:00:00' \
else num_likes
def get_num_total_reactions(reaction_type, reactions):
if reaction_type not in reactions:
return 0
else:
return reactions[reaction_type]['summary']['total_count']
num_loves = get_num_total_reactions('love', reactions)
num_wows = get_num_total_reactions('wow', reactions)
num_hahas = get_num_total_reactions('haha', reactions)
num_sads = get_num_total_reactions('sad', reactions)
num_angrys = get_num_total_reactions('angry', reactions)
# Return a tuple of all processed data
return (status_id, status_message,status_author, link_name, status_type, status_link,
status_published, num_reactions, num_comments, num_shares,
num_likes, num_loves, num_wows, num_hahas, num_sads, num_angrys)
def scrapeFacebookPageFeedStatus(page_id, access_token):
#with open('%s_facebook_statuses.csv' % page_id, 'wb') as file:
# w = csv.writer(file)
# w.writerow(["status_id", "status_message", "link_name", "status_type",
# "status_link", "status_published", "num_reactions",
# "num_comments", "num_shares", "num_likes", "num_loves",
# "num_wows", "num_hahas", "num_sads", "num_angrys"])
has_next_page = True
num_processed = 0 # keep a count on how many we've processed
scrape_starttime = datetime.datetime.now()
print "Scraping %s Facebook Page: %s\n" % (page_id, scrape_starttime)
statuses = getFacebookPageFeedData(page_id, access_token, 100)
while has_next_page:
for status in statuses['data']:
# Ensure it is a status with the expected metadata
if 'reactions' in status:
db_action.save_to_db(processFacebookPageFeedStatus(status, access_token), 'status',page_id)
# output progress occasionally to make sure code is not
# stalling
num_processed += 1
if num_processed % 100 == 0:
print "%s Statuses Processed: %s" % \
(num_processed, datetime.datetime.now())
# if there is no next page, we're done.
if 'paging' in statuses.keys():
statuses = json.loads(request_until_succeed(
statuses['paging']['next']))
else:
has_next_page = False
#db_action.close_db_connection()
print "\nDone!\n%s Statuses Processed in %s" % \
(num_processed, datetime.datetime.now() - scrape_starttime)
if __name__ == '__main__':
print ('Invalid action! Please run "crawler_job.py" instead.')
#scrapeFacebookPageFeedStatus(page_id, access_token)
# The CSV can be opened in all major statistical programs. Have fun! :)