一，python解析文件：

1）读取文件存入内存

2）然后根据字符串进行处理

3）最后将数据转换成数组

4）最后利用dataframe解析数据

# _*_ coding: utf-8 _*_

import pandas as pd

# 获取文件的内容

def get_contends(path):

with open(path) as file_object:

contends = file_object.read()

return contends

# 将一行内容变成数组

def get_contends_arr(contends):

contends_arr_new = []

contends_arr = str(contends).split(']')

for i in range(len(contends_arr)):

if (contends_arr[i].__contains__('[')):

index = contends_arr[i].rfind('[')

temp_str = contends_arr[i][index + 1:]

if temp_str.__contains__('"'):

contends_arr_new.append(temp_str.replace('"', ''))

# print(index)

# print(contends_arr[i])

return contends_arr_new

if __name__ == '__main__':

path = 'event.txt'

contends = get_contends(path)

contends_arr = get_contends_arr(contends)

contents = []

for content in contends_arr:

contents.append(content.split(','))

df = pd.DataFrame(contents, columns=['shelf_code', 'robotid', 'event', 'time'])

print(df)

二，用json读取数组数据：

# _*_ coding: utf-8 _*_

import pandas as pd

import json

file = open("event.txt")

context = file.readline()

data = json.loads(context)

data = data['data']

pd.DataFrame(data, columns=['shelfCode', 'robotId', 'action', 'time'])

第二种方法比较简洁，更适合于生产环境