def get_friends():
# get friends
friends_ids = []
cursor = -1
while cursor != 0:
try:
# get friends
print "Get friends list: "+str(cursor)
response = client.api.friends.ids.get()
# update cursor
cursor = response.data.next_cursor
# collect ids from response
friends_ids = friends_ids + response.data.ids
# sleep between calls
if ( cursor != 0 ) :
interval = calc_interval(response.headers)
print "Sleep "+str(interval)+" s"
time.sleep(interval)
except TwitterApiError, e:
print "Exception: "+e._msg
# set interval to 60 in case of error
interval = 60
print "Sleep "+str(interval)+" s"
time.sleep(interval)
def get_followers():
# get followers
followers_ids = []
cursor = -1
while cursor != 0:
try:
# get followers
print "Get followers list: " + str(cursor)
response = client.api.followers.ids.get()
# update cursor
cursor = response.data.next_cursor
# collect ids from response
followers_ids = followers_ids + response.data.ids
# sleep between calls
if (cursor != 0):
interval = calc_interval(response.headers)
print "Sleep " + str(interval) + " s"
time.sleep(interval)
except TwitterApiError, e:
print "Exception: " + e._msg
# set interval to 60 in case of error
interval = 60
print "Sleep " + str(interval) + " s"
time.sleep(interval)
results = []
# for each user
for record in ud.iter_rows():
user_id = record.get(INPUT_COLUMN, None)
if user_id is None or len(user_id) == 0:
print "Empty user id, ignoring"
continue
print "Unfollow: %s" % user_id
userdata = client.api.friendships.destroy.post( screen_name=user_id )
# save results in output dataset
o = {}
o["row_dtime"] = datetime.datetime.today().strftime("%m/%d/%Y %H:%M:%S")
o["screen_name"] = userdata.data.screen_name
o["name"] = userdata.data.name
results.append(o)
# interval between calls
interval = calc_interval(userdata.headers)
print "Sleep "+str(interval)+" s"
time.sleep(interval)
odf = pd.DataFrame(results)
if odf.size > 0:
# Recipe outputs
twitter_output = dataiku.Dataset(output_dataset_name)
twitter_output.write_with_schema(odf)
continue
print "Follow user: "******"screen_name"] = user_id
# follow user
try:
response = client.api.friendships.create.post(screen_name=user_id)
print "Status: "+response.headers['Status']
# save response status
o["row_dtime"] = datetime.datetime.today().strftime("%m/%d/%Y %H:%M:%S")
o["status"] = response.headers['Status']
o["response_headers"] = response.headers
o["response_data"] = json.dumps(response.data)
interval = calc_interval(response.headers)
print "Sleep "+str(interval)+" s"
time.sleep(interval)
except TwitterApiError, e:
o["status"] = e._msg
print "Exception: %s" % str(e)
finally:
results.append(o)
odf = pd.DataFrame(results)
if odf.size > 0:
# Recipe outputs
twitter_following_output = dataiku.Dataset(output_dataset_name)
print "Follow user: "******"screen_name"] = user_id
# follow user
try:
response = client.api.friendships.create.post(screen_name=user_id)
print "Status: " + response.headers['Status']
# save response status
o["row_dtime"] = datetime.datetime.today().strftime(
"%m/%d/%Y %H:%M:%S")
o["status"] = response.headers['Status']
o["response_headers"] = response.headers
o["response_data"] = json.dumps(response.data)
interval = calc_interval(response.headers)
print "Sleep " + str(interval) + " s"
time.sleep(interval)
except TwitterApiError, e:
o["status"] = e._msg
print "Exception: %s" % str(e)
finally:
results.append(o)
odf = pd.DataFrame(results)
if odf.size > 0:
# Recipe outputs
twitter_following_output = dataiku.Dataset(output_dataset_name)
twitter_following_output.write_with_schema(odf)
results = []
# for each user
for record in ud.iter_rows():
user_id = record.get(INPUT_COLUMN, None)
if user_id is None or len(user_id) == 0:
print "Empty user id, ignoring"
continue
print "Unfollow: %s" % user_id
userdata = client.api.friendships.destroy.post(screen_name=user_id)
# save results in output dataset
o = {}
o["row_dtime"] = datetime.datetime.today().strftime("%m/%d/%Y %H:%M:%S")
o["screen_name"] = userdata.data.screen_name
o["name"] = userdata.data.name
results.append(o)
# interval between calls
interval = calc_interval(userdata.headers)
print "Sleep " + str(interval) + " s"
time.sleep(interval)
odf = pd.DataFrame(results)
if odf.size > 0:
# Recipe outputs
twitter_output = dataiku.Dataset(output_dataset_name)
twitter_output.write_with_schema(odf)
