有没有人尝试过用Beatbox将SalesForce报告解析成Pandas DataFrame?在SO上有几个例子,但没有一个提供全面的解决方案,或者至少我认为它没有。
#!/usr/bin/env python3
import beatbox
import pandas as pd
sf = beatbox._tPartnerNS
service = beatbox.Client()
service.serverUrl = 'https://login.salesforce.com/services/Soap/u/38.0'
service.login('my-username', 'my-password')
report_id = '00myreport4G3V'
query = "SELECT Name FROM Report where id = '{}'".format(report_id)
query_result = service.query(query)这只是选择名称,但理想情况下,我希望将报告内容加载到DataFrame中。有什么需要帮忙的吗?
发布于 2018-12-26 18:09:10
我对BeatBox并不熟悉,但是使用simple-salesforce拉取csv然后将其转换为DataFrame是非常容易的。
#-*-coding:utf-8-*-
import pandas as pd
import numpy as np
from simple_salesforce import Salesforce
import requests
###login to SF
sf = Salesforce(username='xxxxx',
password='xxxx',
security_token='',
organizationId='xxxxxx')
def readReport(reportid):
with requests.session() as s:
d = s.get("https://ap1.salesforce.com/{}?export=1&enc=UTF-8&xf=csv".format(reportid),
headers=sf.headers,
cookies={'sid': sf.session_id})
import sys
if sys.version_info[0] < 3:
from StringIO import StringIO
else:
from io import StringIO
return pd.read_csv(StringIO(d.text), sep=",")
df = readReport('your report id')发布于 2017-08-12 07:41:27
可以通过Salesforce Reports and Dashboards REST API检索报告数据。这适用于Salesforce‘15(版本34.0)以来的版本。
由于REST API,我用Simple-salesforce包写了一个例子。(不过,可以在不使用simple-salesforce的情况下重写它,并使用Beatbox的api会话,编写至少10行额外的代码,并且只安装requests包。)
通用代码
from collections import OrderedDict
from simple_salesforce import Salesforce
import pandas as pd
import json
class SfReportsApi(Salesforce):
def __init__(self, *args, **kwargs):
super(SfReportsApi, self).__init__(*args, **kwargs)
def describe_report(self, report_id):
return self._call_report(report_id, command='/describe')
def to_pandas_dataframe(self, report_id, metadata=None):
"""SF report details exported to DataFrame, can be modified by metadata"""
resp = self._call_report(report_id, metadata=metadata)
if not resp['allData']:
print("Detailed data have been truncated to the usual report limit (2000).")
columns = []
converters = []
get_label = lambda x: x['label']
sf_pandas_map = {
'boolean': lambda x: x['value'],
'currency': lambda x: x['value']['amount'],
'date': lambda x: pd.Timestamp(x['value']),
'datetime': lambda x: pd.Timestamp(x['value']),
'double': lambda x: x['value'],
'picklist': get_label,
'string': get_label,
'textarea': get_label,
}
for col in resp['reportExtendedMetadata']['detailColumnInfo'].values():
columns.append(col['label'])
converters.append(sf_pandas_map.get(col['dataType'], get_label))
data = [[conv(cell) for conv, cell in zip(converters, row['dataCells'])]
for sect_key, section in resp['factMap'].items()
if sect_key != 'T!T'
for row in section['rows']
]
df = pd.DataFrame(data, columns=columns)
return df
def _call_report(self, report_id, metadata=None, command=None):
url = '{}analytics/reports/{}{}'.format(self.base_url, report_id, command or '')
data = json.dumps({'reportMetadata': metadata}) if metadata else None
resp = self._call_salesforce('POST' if metadata else 'GET', url, data=data)
return resp.json(object_pairs_hook=OrderedDict)用法示例
report_id = '00O24000004qtI4EAI'
# set Salesforce session_id some way (by login or reused from other app)
sf = SfReportsApi(username='me@example.com', password='password', security_token='token')
# sf = SfReportsApi(instance_url='https://na1.salesforce.com', session_id='')
# get report metadata if useful
metadata = sf.describe_report(report_id)['reportMetadata']
# modify them or write only the modified keys, e.g. change filters or remove subtotals etc.
metadata = {
'orderBy': ['ACCOUNT.NAME'],
'reportFilters': [{'value': 'W', 'column': 'ACCOUNT.NAME', 'operator': greaterOrEqual'}]
}
df = sf.to_pandas_dataframe(report_id, metadata)可以动态添加列、过滤器、排序等(有关report Execute synchronous的文档)。方法to_pandas_dataframe适用于包含详细信息的普通表格报表,并且可以选择使用一个总计,但不能超过一个级别的小计。可以从更复杂的报告中检索数据(请参阅关于Decode the Fact Map或cheatsheet的文档),但它没有实现,因为在运行之前通过元数据参数动态删除它们更容易。
只能报告2000个详细数据行。可以使用几个带有过滤器的请求来查看所有数据。
https://stackoverflow.com/questions/41004155
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