Question

我编写了此脚本，该脚本返回了包含其统计信息的广告列表，但显然，我仅获得有效广告的见解，而不是暂停的见解-对于暂停的那些，我只是获得广告系列名称及其ID！

我尝试使用如下所示的过滤器，但是它不起作用：

''

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

然后我使用以下方法进行检查：

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'}

只有活动的名称，而没有见解！是否有人之前或之前曾检索过有关暂停的广告/广告系列的统计信息/见解？

谢谢！

请检查我的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

例如，对于过滤器已暂停的广告系列，您可以组合更多过滤条件，该名称包含字符串name，并从3月1日开始使用：

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}

时间戳记应该是一个纪元时间戳记，例如：

Epoch时间戳：1551444673 时间（GMT）：2019年3月1日，星期五下午12:51:13

Answer 2

经过几天的挖掘，我终于想出了一个脚本，该脚本确实用于提取3年的Facebook广告见解，从而避免了Facebook API的速率限制。

首先，我们导入所需的库：

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，我将它们保存在Google Cloud存储中，然后保存在Big Query表中。

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，这是您可以运行以提取最近X天的数据的整个脚本！

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)

这确实非常有效，但是请注意，如果您打算提取3年的数据，该脚本将需要大量时间来运行！

我要感谢LucyTurtle和Ashish Baid的脚本在我的工作中对我有帮助！

如果您需要更多详细信息或需要提取一天中不同广告帐户的数据，请参考这篇文章：

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

使用Facebook Marketing API不会暂停广告见解

2 个答案: