Facebook API 线下转化事件参数数据必须是数组错误

Question

我正在尝试使用一些自定义字段将事件上传到 Facebook 的离线转化数据集，但我收到以下错误

Status:  400
  Response:
    {
      "error": {
        "message": "(#100) param data must be an array.",
        "type": "OAuthException",
        "code": 100,
        "fbtrace_id": "A5qsezd_MfvKEYYTVfPcu29"
      }
    }

我指的是上传线下活动的页面。

https://developers.facebook.com/docs/marketing-api/offline-conversions/

CSV结构

email,event_name,event_time,value,dept,brand,tx_type,cust_type,cust_trend
79FBB38FC843911533020FD8DE5B29CBA9958F,Purchase,2020-06-15T07:42:47Z,100.25, RENTAL,NAN,PA,Active,Growth (+15% to LY)
8EF89542E99BF7D8C0D4AA9F218,Purchase,2020-06-15T17:46:13Z,50,DEPOSITS, NAN,Other,Active,Declined (-15% to LY)
4C83B542E9C9566AA8D6A5279839115E7C0C454A1,Purchase,2020-06-15T09:55:01Z,150,DEPOSITS, NAN,PA,Active,Declined (-15% to LY)
361604C2B8FC67,Purchase,2020-06-15T15:41:18Z,50,DEPOSITS, NAN,OtherNew (Less than 3 Months),Did Not Shop LY
09133B0CDFA527BA9013CA8F1A0382D76F9,Purchase,2020-06-15T08:44:47Z,1,DEPOSITS, NAN,PX,Active,Growth (+15% to LY)
50cff131E2B3042C6E533ss225146C37994E2C2,Purchase,2020-06-15T07:35:50Z,300,DEPOSITS, NAN,Other,ActiveGrowth (+10% to LY)
ECD35DBB79FF37B0FC95E131,Purchase,2020-06-15T16:13:28Z,50,DEPOSITS, NAN,PX,Active,Decline (-12% to LY)

代码：

def upload_offline_conversion(**args):
    from facebook_business.adobjects.offlineconversiondataset import OfflineConversionDataSet
    from facebook_business.api import FacebookAdsApi
    import pandas as pd
    #import gcsfs
    import json
    access_token = access_token
    FacebookAdsApi.init(app_id=app_id,access_token=access_token)
    offline_dataset = OfflineConversionDataSet(dataset_id)
    df = pd.read_csv('UPLOADS.csv',sep =',')
    df['event_time'] = (pd.to_datetime(df['event_time']).astype(int) / 10 ** 9).astype(int).astype(str)
    df['match_keys'] = df.apply(lambda row: json.dumps({k: [row[k]] if k in ['email'] else row[k] for k in ['email'] if pd.notnull(row[k])}), axis=1)
    del df['email']  # deleting match_keys single columns since they are now useless
    df["currency"]='CAD'
    data = (df.groupby(['event_name','event_time','match_keys','value','currency'], as_index=False)
         .apply(lambda x: x[['dept','brand','tx_type','cust_type','cust_trend']].to_dict('r'))
         .reset_index()
         .rename(columns={0:'custom_data'}).to_json(orient='records'))
          
    print(data)
    batch_limit = 2000 # Maximum number of events permitted in a single call
    for i in range(0, len(data), batch_limit):
        params = {
                'upload_tag': 'upload_test',
                'data': data[i:i+batch_limit],
                }
       # print(params)
       #offline_dataset.create_event(params=params)

预计o/p

data=[ 
    { 
      match_keys: {"email": ['79FBB38FC843911533020FD8DE5B29CBA9958F']}, 
      currency: "CAD", 
      value: 100.25,
      event_name: "Purchase",
      event_time: 1592206967,
      custom_data: {
        dept: "RENTAL",
        brand:"NAN",
        tx_type:"PA",
        cust_type:"ACTIVE",
        cust_trend:"Growth (+15% to LY)"
      },
    }, 
    { 
      match_keys: {"email": ["8EF89542E99BF7D8C0D4AA9F218"]}, 
      currency: "CAD", 
      value: 50,
      event_name: "Purchase",
      event_time: 1592243173,
      custom_data: {
        dept: "RENTAL",
        brand:"NAN",
        tx_type:"PA",
        cust_type:"ACTIVE",
        cust_trend:"Growth (+15% to LY)"
      },
    }, 
    #and so on...................
  ]

我的示例输出：

{'upload_tag': 'sales_upload_test_final', 
'data': '[
          {"event_name":"Purchase",
           "event_time":"1592243173",
           "match_keys":"{"\email\": [\"8EF89542E99BF7D8C0D4AA9F218"\]}",
           "value":"50",
           "currency":"CAD",
           "custom_data":[{"dept":"DEPOSITS","brand":" NAN","tx_type":"Other","cust_type":"Active","cust_trend":"Declined (-15% to LY)"}]}]}

Answer 1

需要指定截至 2020 年 7 月 1 日的 LDU。

    Code:
    def upload_offline_conversion(**args):
        from facebook_business.adobjects.offlineconversiondataset import OfflineConversionDataSet
        from facebook_business.api import FacebookAdsApi
        import pandas as pd
        #import gcsfs
        import json
        access_token = access_token
        FacebookAdsApi.init(app_id=app_id,access_token=access_token)
        offline_dataset = OfflineConversionDataSet(dataset_id)
        df = pd.read_csv('UPLOADS.csv',sep =',')
        df['event_time'] = (pd.to_datetime(df['event_time']).astype(int) / 10 ** 9).astype(int).astype(str)
        df['match_keys'] = df.apply(lambda row: json.dumps({k: [row[k]] if k in ['email'] else row[k] for k in ['email'] if pd.notnull(row[k])}), axis=1)
        del df['email']  # deleting match_keys single columns since they are now useless
        df["currency"]='CAD'
        data = (df.groupby(['event_name','event_time','match_keys','value','currency'], as_index=False)
             .apply(lambda x: x[['dept','brand','tx_type','cust_type','cust_trend']].to_dict('r'))
             .reset_index()
             .rename(columns={0:'custom_data'}).to_dict(orient='records'))
        df = pd.DataFrame(data)
        df["data_processing_options"]=  [[]] * df.shape[0]  #(Value either [] or ["LDU"]  ) 
        data  = df.to_dict(orient="records")  
        batch_limit = 2000 # Maximum number of events permitted in a single call
        for i in range(0, len(data), batch_limit):
            params = {
                    'upload_tag': 'upload_test',
                    'data': data[i:i+batch_limit],
                    }
           # print(params)
           #offline_dataset.create_event(

params=params)

Facebook API 线下转化事件参数数据必须是数组错误

Facebook API offline conversion event param data must be an array error

python

json

facebook-graph-api

pandas