Python文件操作JSON CSV TSV Excel和Pickle文件序列化

import json
# 读取JSON文件
with open('data.json', 'r') as file:
    data = json.load(file)
# 使用数据
print(data)

import json

data = {'name': 'John', 'age': 30, 'city': 'New York'}

# 写入JSON文件
with open('data.json', 'w') as file:
    json.dump(data, file)

import csv
# 读取CSV文件
with open('data.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

import csv
data = [['Name', 'Age'], ['Alice', 25], ['Bob', 30], ['Charlie', 35]]
# 写入CSV文件
with open('data.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerows(data)

import openpyxl
# 读取Excel文件
workbook = openpyxl.load_workbook('data.xlsx')
sheet = workbook.active
for row in sheet.iter_rows():
    for cell in row:
        print(cell.value)

import openpyxl
data = [['Name', 'Age'], ['Alice', 25], ['Bob', 30], ['Charlie', 35]]
# 写入Excel文件
workbook = openpyxl.Workbook()
sheet = workbook.active
for row in data:
    sheet.append(row)
workbook.save('data.xlsx')

import pickle
data = {'name': 'John', 'age': 30, 'city': 'New York'}
# 序列化对象并保存到文件
with open('data.pkl', 'wb') as file:
    pickle.dump(data, file)

import pickle
# 从文件加载对象
with open('data.pkl', 'rb') as file:
    loaded_data = pickle.load(file)
# 使用加载的数据
print(loaded_data)