将文本文件转换为特定格式的json（python）

Question

我有一些文本格式的库存数据，我想把它转换成特定格式的JSON。 文本文件中的数据点用逗号（，）分隔，每行包含间隔为1分钟的数据。 另外，在某些行中，末尾有多余的不必要数据，因此我要确保在转换之后只存在六个数据点（不包括第一个数据点和第七个数据点之后的任何数据）

输入数据：

BANKNIFTY_F1,20150228,15:27,19904.65,19924.00,19900.40,19920.20,31225
BANKNIFTY_F1,20150228,15:28,19921.05,19941.30,19921.05,19937.00,31525
BANKNIFTY_F1,20150228,15:29,19932.45,19945.00,19930.10,19945.00,38275
BANKNIFTY_F1,20150228,15:30,19947.00,19949.40,19930.00,19943.80,43400
BANKNIFTY_F1,20150302,09:16,20150.15,20150.15,20021.50,20070.00,91775,2026525
BANKNIFTY_F1,20150302,09:17,20071.50,20085.00,20063.50,20063.50,45700,2026525

预期输出数据：

[{"date":"20150228","time":"15:27","open":"19904.65","high":"19924.00","low":"19900.40","close":"19920.20","volume":"31225"},{"date": "20150228", "time":"15:28", "open":"19921.05","high":"19941.30" ,"low":"19921.05","close":"19937.00", "volume":"31525"}, {"date":"20150228","time" :"15:29" ,"open": "19932.45" ,"high" :"19945.00 ","low":"19930.10","close" :"19945.00","volume":"38275"},{"date": "20150228","time ":" 15:30","open ":"19947.00","high" :"19949.40","low":"19930.00" ,"close":"19943.80", "volume":"43400"} , {"date": "20150302","time" :"09:16","open":"20150.15","high ":"20150.15", "low":"20021.50", "close":"20070.00 ","volume":"91775"}, {"date":"20150302", "time": "09:17","open": "20071.50", "high":"20085.00" , "low":"20063.50", "close":"20063.50", "volume": "45700"}

请注意，在预期输出中，最后两个输入行中显示的最后一个不必要的数据点被忽略。你知道吗

Answer 1

假设文本文件中的所有行都是以相同的方式构建的，您可以逐行迭代文本文件，并以严格的方式断开它，如：

my_tokens = []
for line in f.read():
    tokens = line.split(',')
    my_dict = {}
    try:
        my_dict['date'] = tokens[1]
        my_dict['time'] = tokens[2]
        my_dict['open'] = tokens[3]
        my_dict['high'] = tokens[4]
        my_dict['low'] = tokens[5]
        my_dict['close'] = tokens[6]
        my_dict['volume'] = tokens[7]
    except Exception as:
        continue
    my_tokens.append(my_dict)

这不是最漂亮的答案，但它适用于您的数据类型（：

Answer 2

您希望将csv文件转换为JSON。在python中使用CSV文件时，请始终考虑数据帧。所以首先安装Pandas（pip install Pandas）。你知道吗

将csv文件作为Pandas数据帧读取，将列标题设置为键，然后使用Pandas内置功能to_dict转换为json。只有几行代码。你知道吗

首先需要清除文件中不需要的行。如果只需要前X列，还可以使用pd.read_csv中的参数来选择特定的列。然后执行以下操作：

import pandas as pd

dataframe = pd.read_csv("stockdata.txt", header = None, names = ["date","time","open","high","low","close","volume"])

// this is a python dictionary
json_dictionary = dataframe.to_dict('records')

print(json_dictionary)

// optionally convert to a json string
json_string = json_dictionary.dumps()

可以使用pd.read_csv为列设置特定的数据类型

Answer 3

您可以使用python中的文件处理简单地做到这一点。你知道吗

import json
stocks = []

with open('stocks.txt', 'r') as data:
    for line in data:
        line = line.strip()
        ldata = line.split(',')
        temp_stock = {
            'date':ldata[1],
            'time':ldata[2],
            'open':ldata[3],
            'high':ldata[4],
            'low':ldata[5],
            'close':ldata[6],
            'volume':ldata[7]
        }
        stocks.append(temp_stock)
with open('stocks.json', 'w') as fp:
    json.dump(stocks, fp, indent=4)
from pprint import pprint
pprint(stocks)

不然呢

with open('stocks.txt', 'r') as data:
    res = [ {
            'date':line.strip().split(',')[1],
            'time':line.strip().split(',')[2],
            'open':line.strip().split(',')[3],
            'high':line.strip().split(',')[4],
            'low':line.strip().split(',')[5],
            'close':line.strip().split(',')[6],
            'volume':line.strip().split(',')[7]
        } for line in data ]

输出：

  'date': '20150228',
  'high': '19924.00',
  'low': '19900.40',
  'open': '19904.65',
  'time': '15:27',
  'volume': '31225'},
 {'close': '19937.00',
  'date': '20150228',
  'high': '19941.30',
  'low': '19921.05',
  'open': '19921.05',
  'time': '15:28',
  'volume': '31525'},
 {'close': '19945.00',
  'date': '20150228',
  'high': '19945.00',
  'low': '19930.10',
  'open': '19932.45',
  'time': '15:29',
  'volume': '38275'},
 {'close': '19943.80',
  'date': '20150228',
  'high': '19949.40',
  'low': '19930.00',
  'open': '19947.00',
  'time': '15:30',
  'volume': '43400'},
 {'close': '20070.00',
  'date': '20150302',
  'high': '20150.15',
  'low': '20021.50',
  'open': '20150.15',
  'time': '09:16',
  'volume': '91775'},
 {'close': '20063.50',
  'date': '20150302',
  'high': '20085.00',
  'low': '20063.50',
  'open': '20071.50',
  'time': '09:17',
  'volume': '45700'}]