从BigQuery到Python数据框架的实时数据

我正在探索将BigQuery数据引入Python的方法,以下是我迄今为止的代码:

from google.cloud import bigquery
from pandas.io import gbq

client = bigquery.Client.from_service_account_json("path_to_my.json")

project_id = "my_project_name"

query_job = client.query("""
    #standardSQL
    SELECT date,
    SUM(totals.visits) AS visits
    FROM `projectname.dataset.ga_sessions_20*` AS t
    WHERE parse_date('%y%m%d', _table_suffix) between 
    DATE_sub(current_date(), interval 3 day) and
    DATE_sub(current_date(), interval 1 day)
    GROUP BY date
    """)

results = query_job.result()  # Waits for job to complete.

#for row in results:
#  print("{}: {}".format(row.date, row.visits))

results_df = gbq.read_gbq(query_job,project_id=project_id)

注释掉的行: #for row in results: print("{}: {}".format(row.date, row.visits)) 从我的查询中返回正确的结果,但它们在此表单中不可用,下一步我想将它们放入数据帧中,但此代码返回错误 TypeError: Object of type 'QueryJob' is not JSON serializable .

有人能告诉我生成这个错误的代码有什么问题吗,或者有人能建议一种更好的方法将BigQuery数据引入到数据帧中吗?