simple_salesforce python中的父子关系查询，从有序dict中提取

Question

我试图使用python中的simple_salesforce包从salesforce查询信息

问题在于，它将作为父子关系一部分的字段嵌套到有序dict中的有序dict中

我想。。从Opportunity对象中查找id以及与该记录关联的accountid

SOQL查询可能看起来像

query = "select id, account.id from opportunity where closedate = last_n_days:5"

在SOQL（salesforce对象查询语言）中，点表示数据库中的父子关系。因此，我试图从opportunity对象获取id，然后从该记录上的account对象获取相关id

由于某些原因，Id很好，但account.Id嵌套在有序dict中的有序dict中：

q = sf.query_all(query)

这将收回一本有序字典

OrderedDict([('totalSize', 455),
             ('done', True),
             ('records',
              [OrderedDict([('attributes',
                             OrderedDict([('type', 'Opportunity'),
                                          ('url',

我将拉动ordereddict的records部分来创建一个df

df = pd.DataFrame(q['records'])

这给了我3列，一个有序dict称为'attributes'，Id，另一个有序dict称为'Account'。我正在寻找一种从嵌套有序dict'Account'中提取('BillingCountry', 'United States')片段的方法

[OrderedDict([('attributes',
               OrderedDict([('type', 'Opportunity'),
                            ('url',
                             '/services/data/v34.0/sobjects/Opportunity/0061B003451RhZgiHHF')])),
              ('Id', '0061B003451RhZgiHHF'),
              ('Account',
               OrderedDict([('attributes',
                             OrderedDict([('type', 'Account'),
                                          ('url',
                                           '/services/data/v34.0/sobjects/Account/001304300MviPPF3Z')])),
                            ('BillingCountry', 'United States')]))])

编辑：澄清我在寻找什么

我想以一个dataframe结束，每个查询字段都有一列

当我使用df = pd.DataFrame(sf.query_all(query)['records'])将'records'片段放入数据帧时，它给出了：

attributes  Id  Account
OrderedDict([('type', 'Opportunity'), ('url', '/services/data/v34.0/sobjects/Opportunity/0061B003451RhZgiHHF')])    0061B003451RhZgiHHF OrderedDict([('attributes', OrderedDict([('type', 'Account'), ('url', '/services/data/v34.0/sobjects/Account/0013000000MvkRQQAZ')])), ('BillingCountry', 'United States')])
OrderedDict([('type', 'Opportunity'), ('url', '/services/data/v34.0/sobjects/Opportunity/0061B00001Pa52QQAR')]) 0061B00001Pa52QQAR  OrderedDict([('attributes', OrderedDict([('type', 'Account'), ('url', '/services/data/v34.0/sobjects/Account/0011300001vQPxqAAG')])), ('BillingCountry', 'United States')])
OrderedDict([('type', 'Opportunity'), ('url', '/services/data/v34.0/sobjects/Opportunity/0061B00001TRu5mQAD')]) 0061B00001TRu5mQAD  OrderedDict([('attributes', OrderedDict([('type', 'Account'), ('url', '/services/data/v34.0/sobjects/Account/0011300001rfRTrAAE')])), ('BillingCountry', 'United States')])

删除'attributes'列后，我希望输出是

Id BillingCountry
0061B003451RhZgiHHF 'United States'
0061B00001Pa52QQAR 'United States'
0061B00001TRu5mQAD 'United States'

Answer 1

Pandas是表格数据的神奇工具。但是，尽管它可以包含Python对象，但这并不是它的最佳选择。我建议您先从查询中提取数据，然后再将其插入pandas.Dataframe：

提取记录：

将所需字段提取为字典列表非常简单，如下所示：

records = [dict(id=rec['Id'], country=rec['Account']['BillingCountry'])
           for rec in data['records']]

将记录插入数据框：

有了DICT列表，数据帧就像：

df = pd.DataFrame(records)

测试代码：

import pandas as pd
from collections import OrderedDict

data = OrderedDict([
    ('totalSize', 455),
    ('done', True),
    ('records', [
        OrderedDict([
            ('attributes', OrderedDict([('type', 'Opportunity'), ('url', '/services/data/v34.0/sobjects/Opportunity/0061B003451RhZgiHHF')])),
            ('Id', '0061B003451RhZgiHHF'),
            ('Account', OrderedDict([('attributes', OrderedDict([('type', 'Account'), ('url', '/services/data/v34.0/sobjects/Account/0013000000MvkRQQAZ')])),
                                     ('BillingCountry', 'United States')])),
        ]),
        OrderedDict([
            ('attributes', OrderedDict([('type', 'Opportunity'), ('url', '/services/data/v34.0/sobjects/Opportunity/0061B00001Pa52QQAR')])),
            ('Id', '0061B00001Pa52QQAR'),
            ('Account', OrderedDict([('attributes', OrderedDict([('type', 'Account'), ('url', '/services/data/v34.0/sobjects/Account/0011300001vQPxqAAG')])),
                                     ('BillingCountry', 'United States')])),
        ]),
        OrderedDict([
            ('attributes', OrderedDict([('type', 'Opportunity'), ('url', '/services/data/v34.0/sobjects/Opportunity/0061B00001TRu5mQAD')])),
            ('Id', '0061B00001TRu5mQAD'),
            ('Account', OrderedDict([('attributes', OrderedDict([('type', 'Account'), ('url', '/services/data/v34.0/sobjects/Account/0011300001rfRTrAAE')])),
                                     ('BillingCountry', 'United States')])),
        ]),
    ])
])

records = [dict(id=rec['Id'], country=rec['Account']['BillingCountry'])
           for rec in data['records']]
for r in records:
    print(r)

print(pd.DataFrame(records))

测试结果：

{'country': 'United States', 'id': '0061B003451RhZgiHHF'}
{'country': 'United States', 'id': '0061B00001Pa52QQAR'}
{'country': 'United States', 'id': '0061B00001TRu5mQAD'}

         country                   id
0  United States  0061B003451RhZgiHHF
1  United States   0061B00001Pa52QQAR
2  United States   0061B00001TRu5mQAD

Answer 2

熊猫可以阅读有序的口述

import pandas as pd
from simple_salesforce import Salesforce

sf = Salesforce(username='your_username',   
                password='your_password',
                security_token='your_token')

query = "select id, account.id from opportunity where closedate = last_n_days:5"
df = pd.DataFrame(sf.query_all(query)['records']).drop(columns='attributes')