python - 使用 python 以所需格式从 CSV 中检索 JSON

Question

非常感谢，我一直热衷于收集一些关于从相应输入中获取以下输出的见解。希望通过使用 python 脚本将表格转换为所需的格式，因为我必须在稍后阶段使用巨大的 CSV。任何输入都受到高度赞赏。

输入 CSV：

参考	微控制器	价值	货币
10000	5300	134.09	美元
10001	5651	128.95	美元
10002	5912	104.71	美元

使用的python代码：

from csv import DictReader
from itertools import groupby
from pprint import pprint
import json

with open('Test_bulk_transactions_data.csv') as csvfile:
    r = DictReader(csvfile, skipinitialspace=True)
    data = [dict(d) for d in r]

    group = []
    uniquekeys = []

    for k, g in groupby(data, lambda r: (r['reference'], r['mcc'])):
        group.append({
            "reference": k[0],
            "mcc": k[1],
            "amount": [{k:v for k, v in d.items() if k not in ['reference','mcc']} for d in list(g)]})
        uniquekeys.append(k)

print(json.dumps(group, indent = 3) + '}')

电流输出：

  {
   "reference": "10000",
   "mcc": "5300",
   "amount": [
    {
     "value": "134.09",
     "currency": "USD"
    }
   ]
  },
  {
   "reference": "10001",
   "mcc": "5651",
   "amount": [
    {
     "value": "128.95",
     "currency": "USD"
    }
   ]
  },
  {
   "reference": "10002",
   "mcc": "5912",
   "amount": [ 
    {
     "value": "104.71",
     "currency": "USD"
    }
   ]
  }

所需的输出 JSON：

  {
   "reference": "10000",
   "mcc": "5300",
   "amount": {
     "value": 134.09,
     "currency": "USD"
    }
  },
  {
   "reference": "10001",
   "mcc": "5651",
   "amount": {
     "value": 128.95,
     "currency": "USD"
    }
  },
  {
   "reference": "10002",
   "mcc": "5912",
   "amount": {
     "value": 104.71,
     "currency": "USD"
    }
  }

• 重要说明：金额不应落入 [] 并且该值应作为数字输出而不是字符串。

Answer 1

import csv

csv_filepath =  "/home/mhs/test.csv"
 
output = []


with open(csv_filepath) as cd:
    csvReader = csv.DictReader(cd)
    for r in csvReader:
        r["amount"] = {"value": float(r.pop("value")), "currency": r.pop("currency")}
        output.append(r)

Answer 2

不依赖导入的模块，您可以这样做：

J = []

with open('input.csv') as csv:
    cols = next(csv).split()
    assert len(cols) == 4
    for row in csv:
        t = row.split()
        if len(t) == 4:
            J.append({cols[0]: t[0], cols[1]: t[1], "amount": {cols[2]: float(t[2]), cols[3]: t[3]}})


print(J)