I want to make a batch request getting campaigns for a specific ad account. I created a simple code based on this issue but I've used some global arrays and I don't know if time.sleep(2) is necessary for this code. My code is as below:
from facebookads import FacebookAdsApi
from facebookads.api import FacebookRequest
import pandas as pd
import time
batch_body_responses = []
list_of_artists = [1]
def success_callback(response):
try:
pair = [response.json()['data']]
next = [response.json()['paging']['next']]
batch_body_responses.append(pair)
batch_body_responses.append(next)
except IndexError:
pass
except UnicodeEncodeError:
pass
def error_callback(response):
pass
def generate_batches(iterable, batch_size_limit):
# This function can be found in examples/batch_utils.py
batch = []
for item in iterable:
if len(batch) == batch_size_limit:
yield batch
batch = []
batch.append(item)
if len(batch):
yield batch
def get_id_list(art_search_list):
batches = []
your_app_id = '756885'
your_app_secret = '123456789'
your_access_token = 'EAA.....'
api = FacebookAdsApi.init(your_app_id, your_app_secret, your_access_token)
batch_limit = 25
for batch in generate_batches(art_search_list, batch_limit):
next_batch = api.new_batch()
for artt in batch:
requestss = [FacebookRequest(node_id='act_1234/campaigns',method="GET",endpoint="?fields=id,name")]
for req in requestss:
next_batch.add_request(req, success_callback, error_callback)
batches.append(next_batch)
for batch_request in batches:
batch_request.execute()
time.sleep(2)
print(batch_body_responses)
return batch_body_responses
df = pd.DataFrame(get_id_list(list_of_artists))
How can this code optimized by not using global arrays and how to execute without sleep statement and why it is needed sleep?
