使用Python进行文件读写操作的基本方法

# 打开文件
with open('example.txt', 'r') as file:
    # 读取文件的全部内容
    content = file.read()
    print(content)

    # 将文件指针重置到文件开头
    file.seek(0)
    # 逐行读取文件内容
    lines = file.readlines()
    for line in lines:
        print(line.strip())  # 去除行末的换行符

    # 将文件指针重置到文件开头
    file.seek(0)
    # 逐行读取文件内容的另一种方式
    for line in file:
        print(line.strip())

# 打开文件进行写入
with open('output.txt', 'w') as file:
    # 写入内容
    file.write("Hello, World!\n")
    file.write("This is a new line.")

# 打开文件进行追加
with open('output.txt', 'a') as file:
    # 追加内容
    file.write("\nThis is an appended line.")

# 以二进制模式读取文件
with open('example.bin', 'rb') as file:
    binary_data = file.read()
    print(binary_data)

# 以二进制模式写入文件
with open('output.bin', 'wb') as file:
    binary_data = b'\x48\x65\x6c\x6c\x6f\x20\x57\x6f\x72\x6c\x64'  # 二进制数据
    file.write(binary_data)

import json

# 写入 JSON 数据
data = {'name': 'John', 'age': 30, 'city': 'New York'}
with open('data.json', 'w') as file:
    json.dump(data, file)

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

import csv

# 写入 CSV 数据
data = [['Name', 'Age', 'City'], ['John', 30, 'New York'], ['Jane', 25, 'Chicago']]
with open('data.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerows(data)

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

import pandas as pd

# 写入数据到 CSV 文件
data = {'Name': ['John', 'Jane'], 'Age': [30, 25], 'City': ['New York', 'Chicago']}
df = pd.DataFrame(data)
df.to_csv('data_pandas.csv', index=False)

# 读取 CSV 文件
df_read = pd.read_csv('data_pandas.csv')
print(df_read)

import pickle

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

# 反序列化对象
with open('data.pkl', 'rb') as file:
    loaded_data = pickle.load(file)
    print(loaded_data)