人工智能之编程进阶 Python高级：第六章 文件类模块

import csv

# 写入列表数据
with open('data.csv', 'w', newline='', encoding='utf-8') as f:
    writer = csv.writer(f)
    writer.writerow(['Name', 'Age', 'City'])        # 表头
    writer.writerow(['Alice', 30, 'New York'])
    writer.writerows([['Bob', 25, 'London'], ['Charlie', 35, 'Tokyo']])

# 写入字典数据（推荐）
with open('data_dict.csv', 'w', newline='', encoding='utf-8') as f:
    fieldnames = ['Name', 'Age', 'City']
    writer = csv.DictWriter(f, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerow({'Name': 'Alice', 'Age': 30, 'City': 'New York'})

# 读取为列表
with open('data.csv', 'r', encoding='utf-8') as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)  # ['Alice', '30', 'New York']

# 读取为字典（推荐）
with open('data_dict.csv', 'r', encoding='utf-8') as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row['Name'], row['Age'])  # Alice 30

import json

data = {
    "name": "Alice",
    "age": 30,
    "hobbies": ["reading", "coding"],
    "active": True,
    "balance": None
}

# 序列化：Python → JSON 字符串
json_str = json.dumps(data, ensure_ascii=False, indent=2)
print(json_str)

# 反序列化：JSON 字符串 → Python
parsed = json.loads(json_str)
print(parsed['name'])  # Alice

# 写入 JSON 文件
with open('config.json', 'w', encoding='utf-8') as f:
    json.dump(data, f, ensure_ascii=False, indent=2)

# 读取 JSON 文件
with open('config.json', 'r', encoding='utf-8') as f:
    config = json.load(f)

import xml.etree.ElementTree as ET

xml_data = '''
<bookstore>
    <book id="1">
        <title>Python指南</title>
        <author>张三</author>
        <price>59.9</price>
    </book>
    <book id="2">
        <title>数据科学实战</title>
        <author>李四</author>
        <price>79.9</price>
    </book>
</bookstore>
'''

# 从字符串解析
root = ET.fromstring(xml_data)

# 或从文件解析
# tree = ET.parse('books.xml')
# root = tree.getroot()

# 遍历
for book in root.findall('book'):
    title = book.find('title').text
    author = book.find('author').text
    price = float(book.find('price').text)
    book_id = book.get('id')  # 获取属性
    print(f"ID:{book_id} | {title} by {author} - ¥{price}")

# 创建根元素
root = ET.Element("students")

# 添加子元素
student = ET.SubElement(root, "student", id="101")
ET.SubElement(student, "name").text = "王五"
ET.SubElement(student, "grade").text = "A"

# 写入文件
tree = ET.ElementTree(root)
tree.write("students.xml", encoding="utf-8", xml_declaration=True)

from io import StringIO

# 写入内存
f = StringIO()
f.write("Hello, ")
f.write("World!")
content = f.getvalue()  # "Hello, World!"
f.close()

# 读取内存
f = StringIO("Line 1\nLine 2\nLine 3")
for line in f:
    print(line.strip())
f.close()

# with 语句自动关闭
with StringIO() as f:
    f.write("Test")
    print(f.getvalue())  # Test

from io import BytesIO

# 模拟二进制文件（如图片、PDF）
buffer = BytesIO()
buffer.write(b'\x89PNG\r\n\x1a\n')  # PNG 文件头
png_data = buffer.getvalue()
buffer.close()

import pickle

data = {'users': ['Alice', 'Bob'], 'count': 42, 'flag': True}

# 序列化到文件
with open('data.pkl', 'wb') as f:  # 注意：二进制模式 'wb'
    pickle.dump(data, f)

# 从文件反序列化
with open('data.pkl', 'rb') as f:  # 'rb'
    loaded = pickle.load(f)
    print(loaded)  # {'users': ['Alice', 'Bob'], ...}

# 转为 bytes
serialized = pickle.dumps(data)
# 从 bytes 恢复
restored = pickle.loads(serialized)

# 自动关闭文件，无需 f.close()
with open('file.txt', 'r') as f:
    content = f.read()
# 文件在此处已关闭

with open('input.txt', 'r') as fin, open('output.txt', 'w') as fout:
    fout.write(fin.read().upper())

class Timer:
    def __enter__(self):
        self.start = time.time()
        return self
    def __exit__(self, exc_type, exc_val, exc_tb):
        print(f"耗时: {time.time() - self.start:.2f}秒")

with Timer():
    time.sleep(1)  # 耗时: 1.00秒