3 回答
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TA贡献1820条经验 获得超2个赞
现在,根据您的评论,我更好地理解您的问题,这是一个完全不同的答案。请注意,它不使用json模块,只是“手动”进行所需的处理。虽然它可能可以使用该模块来完成,但与下面使用的相对简单的逻辑相比,让它以不同的方式格式化默认情况下识别的 Python 数据类型可能相当复杂——我从经验中知道——。
花药注释:与您的代码一样,这会将 csv 文件的每一行转换为有效的 JSON 对象,并将每一行写入文件中的单独行。然而,结果文件的内容在技术上不会是有效的 JSON,因为所有这些单独的对象都需要用逗号分隔并括在[ ]括号中(即,从而成为有效的 JSON“数组”对象)。
import csv
with open('output2.csv', 'r', newline='') as csvfile, \
open('output2.json', 'w') as jsonfile:
for row in csv.DictReader(csvfile):
newfmt = []
for field, value in row.items():
field = '"{}"'.format(field)
try:
float(value)
except ValueError:
value = 'null' if value == '' else '"{}"'.format(value)
else:
# Avoid changing integer values to float.
try:
int(value)
except ValueError:
pass
else:
value = '"{}"'.format(value)
newfmt.append((field, value))
json_repr = '{' + ','.join(':'.join(pair) for pair in newfmt) + '}'
jsonfile.write(json_repr + '\n')
这是写入文件的 JSON:
{"ACCOUNTNAMEDENORM":"John Smith","DELINQUENCYSTATUS":2.0000000000,"RETIRED":0.0000000000,"INVOICEDAYOFWEEK":5.0000000000,"ID":1234567.0000000000,"BEANVERSION":69.0000000000,"ACCOUNTTYPE":1.0000000000,"ORGANIZATIONTYPEDENORM":null,"HIDDENTACCOUNTCONTAINERID":4321987.0000000000,"NEWPOLICYPAYMENTDISTRIBUTABLE":"1","ACCOUNTNUMBER":"000-000-000-00","PAYMENTMETHOD":12345.0000000000,"INVOICEDELIVERYTYPE":98765.0000000000,"DISTRIBUTIONLIMITTYPE":3.0000000000,"CLOSEDATE":null,"FIRSTTWICEPERMTHINVOICEDOM":1.0000000000,"HELDFORINVOICESENDING":"0","FEINDENORM":null,"COLLECTING":"0","ACCOUNTNUMBERDENORM":"000-000-000-00","CHARGEHELD":"0","PUBLICID":"bc:1234346"}
下面再次显示添加了空格:
{"ACCOUNTNAMEDENORM": "John Smith",
"DELINQUENCYSTATUS": 2.0000000000,
"RETIRED": 0.0000000000,
"INVOICEDAYOFWEEK": 5.0000000000,
"ID": 1234567.0000000000,
"BEANVERSION": 69.0000000000,
"ACCOUNTTYPE": 1.0000000000,
"ORGANIZATIONTYPEDENORM": null,
"HIDDENTACCOUNTCONTAINERID": 4321987.0000000000,
"NEWPOLICYPAYMENTDISTRIBUTABLE": "1",
"ACCOUNTNUMBER": "000-000-000-00",
"PAYMENTMETHOD": 12345.0000000000,
"INVOICEDELIVERYTYPE": 98765.0000000000,
"DISTRIBUTIONLIMITTYPE": 3.0000000000,
"CLOSEDATE": null,
"FIRSTTWICEPERMTHINVOICEDOM": 1.0000000000,
"HELDFORINVOICESENDING": "0",
"FEINDENORM": null,
"COLLECTING": "0",
"ACCOUNTNUMBERDENORM": "000-000-000-00",
"CHARGEHELD": "0",
"PUBLICID": "bc:1234346"}
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TA贡献1851条经验 获得超3个赞
哈,真的很有趣,我想和你找到相反的答案,结果是带引号的。
其实很容易自动删除它,只需删除参数“separators=(',',':')”。
对我来说,只需添加这个参数就可以了。
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TA贡献1900条经验 获得超5个赞
一种解决方案是使用正则表达式查看字符串值是否看起来像浮点数,如果是,则将其转换为浮点数。
import re
null = None
j = {"ACCOUNTNAMEDENORM":"John Smith","DELINQUENCYSTATUS":"2.0000000000",
"RETIRED":"0.0000000000","INVOICEDAYOFWEEK":"5.0000000000",
"ID":"1234567.0000000000","BEANVERSION":"69.0000000000",
"ACCOUNTTYPE":"1.0000000000","ORGANIZATIONTYPEDENORM":null,
"HIDDENTACCOUNTCONTAINERID":"4321987.0000000000",
"NEWPOLICYPAYMENTDISTRIBUTABLE":"1","ACCOUNTNUMBER":"000-000-000-00",
"PAYMENTMETHOD":"12345.0000000000","INVOICEDELIVERYTYPE":"98765.0000000000",
"DISTRIBUTIONLIMITTYPE":"3.0000000000","CLOSEDATE":null,
"FIRSTTWICEPERMTHINVOICEDOM":"1.0000000000","HELDFORINVOICESENDING":"0",
"FEINDENORM":null,"COLLECTING":"0","ACCOUNTNUMBERDENORM":"000-000-000-00",
"CHARGEHELD":"0","PUBLICID":"xx:1234346"}
for key in j:
if j[key] is not None:
if re.match("^\d+?\.\d+?$", j[key]):
j[key] = float(j[key])
我null = None在这里用来处理出现在 JSON 中的“null”。但是您可以在此处用您正在阅读的每个 CSV 行替换 'j',然后使用它来更新该行,然后用浮点数替换字符串将其写回。
如果您可以将任何数字字符串转换为浮点数,那么您可以跳过正则表达式(re.match()命令)并将其替换为j[key].isnumeric(),如果它适用于您的 Python 版本。
编辑:我不认为 Python 中的浮点数以您可能认为的方式处理“精度”。它可能看起来像是2.0000000000被“截断”为2.0,但我认为这更多是格式和显示问题,而不是丢失信息。考虑以下示例:
>>> float(2.0000000000)
2.0
>>> float(2.00000000001)
2.00000000001
>>> float(1.00) == float(1.000000000)
True
>>> float(3.141) == float(3.140999999)
False
>>> float(3.141) == float(3.1409999999999999)
True
>>> print('%.10f' % 3.14)
3.1400000000
虽然有可能让 JSON 包含这些零,但在这种情况下,它归结为将数字视为字符串,即格式化的字符串。
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