使用au'和Decimal值解码字符串中的Python json

Question

我需要解码并加载到DB,这是一个以下列格式到达的字符串:

"[{u'date': 1508760000000, u'value': 0}, {u'date': 1509364800000, u'value': Decimal('5.989999771118164')}, {u'date': 1509969600000, u'value': Decimal('5.989999771118164')}, {u'date': 1510574400000, u'value': Decimal('9.579999923706055')}]"

目前,这是我用来将其转换为数据帧的代码:

import pandas as pd
import json

#json for example:
my_json="""[{u'date': 1508760000000, u'value': 0}, {u'date': 1509364800000, u'value': Decimal('5.989999771118164')}, {u'date': 1509969600000, u'value': Decimal('5.989999771118164')}, {u'date': 1510574400000, u'value': Decimal('9.579999923706055')}]"""
my_json=my_json[1:-1]
my_json=my_json.replace("u'","'")
my_json=my_json.replace("'",'"')
my_json=my_json.replace('Decimal("','')
my_json=my_json.replace('")','')
my_json=my_json.replace(', {','~ {')
my_json_list=my_json.split('~')
my_dict_list=[json.loads(row) for row in my_json_list]
df=pd.DataFrame(my_dict_list)

是否有更短/更优雅的方式来执行此操作？

Answer 1

使用evalie

from decimal import *
df = pd.DataFrame(eval(my_json))

           date              value
0  1508760000000                  0
1  1509364800000  5.989999771118164
2  1509969600000  5.989999771118164
3  1510574400000  9.579999923706055