Not getting paused ads insights using Facebook Marketing API

Question

I wrote this script that returns a list of ads with their stats but apprently I'm getting only insights for active ads and not paused ones - For paused ones, I'm just getting the campaign name and its id !

I tried using filtering like below but it's not working:

''

first = "https://graph.facebook.com/v3.2/act_105433210/campaigns?filtering=[{'field':'effective_status','operator':'IN','value':['PAUSED']}]&fields=created_time,name,effective_status,insights{spend,impressions,clicks}&access_token=%s"% token

Then I check using:

result = requests.get(first)
content_dict = json.loads(result.content)
print(content_dict)

and this is a sample of the output I get:

{'data': [{'created_time': '2019-02-15T17:24:29+0100', 'name': '20122301-FB-BOOST-EVENT-CC SDSDSD', 'effective_status': 'PAUSED', 'id': '6118169436761'}

There is only the name of the campaign and not insights ! Anyone did retrieve stats/insights for paused ads/campaigns before or not?

Thanks !

Please check my other post of my python script : I can't fetch stats for all my facebook campaigns using Python and Facebook Marketing API

Answer 1

After days of digging around, I finally come up with a script that I did run to extract 3 years of facebook ads insights avoiding the rate limit of the facebook API.

First, we import the lib we'll need :

from facebookads.api import FacebookAdsApi
from facebookads.adobjects.adsinsights import AdsInsights
from facebookads.adobjects.adaccount import AdAccount
from facebookads.adobjects.business import Business
import datetime
import csv
import re 
import pandas as pd
import numpy as np
import matplotlib as plt
from google.colab import files
import time

Please note that after extracting the insights, I'm saving them on Google Cloud storage then on Big Query tables.

access_token = 'my-token'
ad_account_id = 'act_id'
app_secret = 'app_s****'
app_id = 'app_id****'
FacebookAdsApi.init(app_id,app_secret, access_token=access_token, api_version='v3.2')
account = AdAccount(ad_account_id)

Then, the following scripts calls the api and check the rate limit we did reach:

import logging
import requests as rq

#Function to find the string between two strings or characters
def find_between( s, first, last ):
    try:
        start = s.index( first ) + len( first )
        end = s.index( last, start )
        return s[start:end]
    except ValueError:
        return ""

#Function to check how close you are to the FB Rate Limit
def check_limit():
    check=rq.get('https://graph.facebook.com/v3.1/'+ad_account_id+'/insights?access_token='+access_token)
    usage=float(find_between(check.headers['x-ad-account-usage'],':','}'))
    return usage

Now, this is the whole script that you can run to extract data of the last X days !

Y = number of days 
for x in range(1, Y):

  date_0 = datetime.datetime.now() - datetime.timedelta(days=x )
  date_ = date_0.strftime('%Y-%m-%d')
  date_compact = date_.replace('-', '')
  filename = 'fb_%s.csv'%date_compact
  filelocation = "./"+ filename
    # Open or create new file 
  try:
      csvfile = open(filelocation , 'w+', 777)
  except:
      print ("Cannot open file.")


  # To keep track of rows added to file
  rows = 0

  try:
      # Create file writer
      filewriter = csv.writer(csvfile, delimiter=',')
      filewriter.writerow(['date','ad_name', 'adset_id', 'adset_name', 'campaign_id', 'campaign_name', 'clicks', 'impressions', 'spend'])
  except Exception as err:
      print(err)
  # Iterate through all accounts in the business account

  ads = account.get_insights(params={'time_range': {'since':date_, 'until':date_}, 'level':'ad' }, fields=[AdsInsights.Field.ad_name, AdsInsights.Field.adset_id, AdsInsights.Field.adset_name, AdsInsights.Field.campaign_id, AdsInsights.Field.campaign_name, AdsInsights.Field.clicks, AdsInsights.Field.impressions, AdsInsights.Field.spend ])
  for ad in ads:

    # Set default values in case the insight info is empty
    date = date_
    adsetid = ""
    adname = ""
    adsetname = ""
    campaignid = ""
    campaignname = ""
    clicks = ""
    impressions = ""
    spend = ""

    # Set values from insight data
    if ('adset_id' in ad) :
        adsetid = ad[AdsInsights.Field.adset_id]
    if ('ad_name' in ad) :
        adname = ad[AdsInsights.Field.ad_name]
    if ('adset_name' in ad) :
        adsetname = ad[AdsInsights.Field.adset_name]
    if ('campaign_id' in ad) :
        campaignid = ad[AdsInsights.Field.campaign_id]
    if ('campaign_name' in ad) :
        campaignname = ad[AdsInsights.Field.campaign_name]
    if ('clicks' in ad) : # This is stored strangely, takes a few steps to break through the layers
        clicks = ad[AdsInsights.Field.clicks]
    if ('impressions' in ad) : # This is stored strangely, takes a few steps to break through the layers
        impressions = ad[AdsInsights.Field.impressions]
    if ('spend' in ad) :
        spend = ad[AdsInsights.Field.spend]

    # Write all ad info to the file, and increment the number of rows that will display
    filewriter.writerow([date_, adname, adsetid, adsetname, campaignid, campaignname, clicks, impressions, spend])
    rows += 1

  csvfile.close()

# Print report
  print (str(rows) + " rows added to the file " + filename)
  print(check_limit(), 'reached of rate limit')
## write to GCS and BQ
  blob = bucket.blob('fb_2/fb_%s.csv'%date_compact)
  blob.upload_from_filename(filelocation)
  load_job_config = bigquery.LoadJobConfig()
  table_name = '0_fb_ad_stats_%s' % date_compact
  load_job_config.write_disposition = 'WRITE_TRUNCATE'
  load_job_config.skip_leading_rows = 1

  # The source format defaults to CSV, so the line below is optional.
  load_job_config.source_format = bigquery.SourceFormat.CSV
  load_job_config.field_delimiter = ','
  load_job_config.autodetect = True
  uri = 'gs://my-project/fb_2/fb_%s.csv'%date_compact
  load_job = bq_client.load_table_from_uri(
    uri,
    dataset.table(table_name),
    job_config=load_job_config)  # API request
  print('Starting job {}'.format(load_job.job_id))
  load_job.result()  # Waits for table load to complete.
  print('Job finished.')

  if (check_limit()>=75):
    print('75% Rate Limit Reached. Cooling Time 5 Minutes.')
    logging.debug('75% Rate Limit Reached. Cooling Time Around 3 Minutes And Half.')
    time.sleep(225)

This did perfectly works but note that if you're planning to extract 3 years of data, the script will take a lot of time to run !

I'd like to thank LucyTurtle and Ashish Baid for their scripts that did help me during my work!

Please refer to this post if you need more details or if you need to extract data for one day for different ad accounts :

Facebook Marketing API - Python to get Insights - User Request Limit Reached

Answer 2

You could combine more filtering criteria as example, for filter paused campaign, that the name contain the string name and start from the 1 march you can use:

act_105433210/campaigns?filtering=[{'field':'effective_status','operator':'IN','value':['PAUSED']},{'field':'name','operator':'CONTAIN','value':'name'},{'field':'created_time','operator':'GREATER_THAN','value':'1551444673'}]&fields=created_time,name,effective_status,insights{spend,impressions,clicks}

the timestamp should be an epoch timestamp, in the example is the:

Epoch timestamp: 1551444673 Human time (GMT): Friday, March 1, 2019 12:51:13 PM