python - 无法使用 Facebook Marketing API 获取暂停的广告见解

Question

我编写了这个脚本，该脚本返回广告列表及其统计信息，但显然我只获得了事件广告的见解，而不是暂停的广告 - 对于暂停的广告，我只是获取广告系列名称及其 ID!

我尝试使用如下所示的过滤，但它不起作用:

''

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

然后我检查使用:

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

这是我得到的输出示例:

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

只有事件名称，没有见解!之前是否有人检索过暂停的广告/广告事件的统计数据/见解？

谢谢!

请查看我的 python 脚本的其他帖子:I can't fetch stats for all my facebook campaigns using Python and Facebook Marketing API

Answer 1

经过几天的挖掘，我终于想出了一个脚本，我确实运行了该脚本来提取 3 年的 Facebook 广告洞察，避免了 Facebook API 的速率限制。

首先，我们导入我们需要的库:

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

请注意，提取见解后，我会将它们保存在 Google Cloud 存储上，然后保存在 Big Query 表上。

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)

然后，以下脚本调用 api 并检查我们确实达到的速率限制:

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

现在，这是整个脚本，您可以运行它来提取过去 X 天的数据!

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)

这确实有效，但请注意，如果您计划提取 3 年的数据，则脚本将需要大量时间来运行!

感谢LucyTurtle和 Ashish Baid感谢他们的脚本在我的工作过程中对我的帮助!

如果您需要更多详细信息或需要提取不同广告帐户一天的数据，请参阅这篇文章:

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