我使用以下代码使用beatbox python API从Salesforce中提取数据。
import beatbox
sf_username = "xyz@salesforce.com"
sf_password = "123"
sf_api_token = "ABC"
def extract():
sf_client = beatbox.PythonClient()
password = str("%s%s" % (sf_password, sf_api_token))
sf_client.login(sf_username, password)
lead_qry = "SELECT CountryIsoCode__c,LastModifiedDate FROM Country limit 10"
records = sf_client.query(lead_qry)
output = open('output','w')
for record in records:
output.write('\t'.join(record.values())
output.close()
if _name_ == '__main__':
extract()
但这是我在输出中得到的。如何获取原始数据,只是我在工作台中看到的值。我不想解析每个数据类型并获取原始值。
实际输出:
[{'LastModifiedDate':datetime.datetime(2012,11,2,9,32,4), 'CountryIsoCode_ c':'AU','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,8,18,14,0,21), 'CountryIsoCode_ c':'LX','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,12,15,20,11), 'CountryIsoCode_ c':'AE','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,12,15,20,29), 'CountryIsoCode_ c':'AR','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,2,9,32,4), 'CountryIsoCode_ c':'AT','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,2,9,32,4), 'CountryIsoCode_ c':'BE','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,12,15,21,28), 'CountryIsoCode_ c':'BR','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,12,15,21,42), 'CountryIsoCode_ c':'CA','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,12,15,36,18), 'CountryIsoCode_ c':'CH','type':'Country _c','Id':''}, {'LastModifiedDate':datetime.datetime(2012,11,12,15,35,8), 'CountryIsoCode_ c':'CL','type':'Country _c','Id':''}]
预期产出:
AU 2012-11-02T09:32:04Z
LX 2012-08-18T14:00:21Z
答案 0 :(得分:4)
如果使用表数据,则应使用Pandas库
以下是一个例子:
import pandas as pd
from datetime import datetime
import beatbox
service = beatbox.PythonClient()
service.login('login_here', 'creds_here')
query_result = service.query("SELECT Name, Country, CreatedDate FROM Lead limit 5") # CreatedDate is a datetime object
records = query_result['records'] # records is a list of dictionaries
记录是您之前提到的字典列表
df = pd.DataFrame(records)
print (df)
Country CreatedDate Id Name type
0 United States 2011-05-26 23:39:58 qwe qwe Lead
1 France 2011-09-01 08:45:26 qwe qwe Lead
2 France 2011-09-01 08:37:36 qwe qwe Lead
3 France 2011-09-01 08:46:38 qwe qwe Lead
4 France 2011-09-01 08:46:57 qwe qwe Lead
现在你有了表格式的Dataframe对象。您可以索引多个列和行:
df['CreatedDate']
0 2011-05-26 23:39:58
1 2011-09-01 08:45:26
2 2011-09-01 08:37:36
3 2011-09-01 08:46:38
4 2011-09-01 08:46:57
以下是有关熊猫时间功能的更多信息http://pandas.pydata.org/pandas-docs/stable/timeseries.html
这是关于大熊猫http://pandas.pydata.org/pandas-docs/stable/install.html