# 写入
with open("data.txt", "w", encoding="utf-8") as f:
    f.write("第一行\n")
    f.write("第二行\n")

# 读取整个文件
with open("data.txt", "r", encoding="utf-8") as f:
    content = f.read()

# 按行读取
with open("data.txt", "r", encoding="utf-8") as f:
    for line in f:
        print(line.strip())

# 读取为列表
with open("data.txt", "r", encoding="utf-8") as f:
    lines = f.readlines()  # ['第一行\n', '第二行\n']

# 追加模式
with open("data.txt", "a", encoding="utf-8") as f:
    f.write("第三行\n")

# 读取二进制文件
with open("image.jpg", "rb") as f:
    data = f.read()
    print(len(data))  # 字节数

# 写入二进制文件
with open("copy.jpg", "wb") as f:
    f.write(data)

from pathlib import Path

# 创建路径
p = Path("/home/user/documents")
p = Path("documents") / "file.txt"  # 推荐用 / 拼接

# 常用属性
print(p.name)       # file.txt
print(p.stem)       # file
print(p.suffix)     # .txt
print(p.parent)     # documents
print(p.resolve())  # 绝对路径

# 判断
p.exists()
p.is_file()
p.is_dir()
p.is_absolute()

from pathlib import Path

p = Path("data.txt")

# 写入
p.write_text("Hello, World!", encoding="utf-8")
p.write_bytes(b"\x00\x01\x02")

# 读取
content = p.read_text(encoding="utf-8")
data = p.read_bytes()

from pathlib import Path

# 创建目录
Path("new_dir").mkdir(parents=True, exist_ok=True)

# 遍历当前目录
for p in Path(".").iterdir():
    print(p)

# glob 匹配
for p in Path(".").glob("*.py"):
    print(p)

# 递归匹配
for p in Path(".").rglob("*.py"):
    print(p)

# 删除文件
Path("data.txt").unlink(missing_ok=True)

# 删除空目录
Path("empty_dir").rmdir()

import csv

# 写入 CSV
with open("users.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.writer(f)
    writer.writerow(["姓名", "年龄", "城市"])
    writer.writerow(["Alice", 30, "北京"])
    writer.writerow(["Bob", 25, "上海"])

# 读取 CSV
with open("users.csv", "r", encoding="utf-8") as f:
    reader = csv.reader(f)
    header = next(reader)
    for row in reader:
        print(row)  # ['Alice', '30', '北京']

import csv

# 写入字典格式
with open("users.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": "北京"})

# 读取字典格式
with open("users.csv", "r", encoding="utf-8") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(f"{row['name']}, {row['age']}岁")  # Alice, 30岁

import json

# Python 对象 → JSON 字符串
data = {"name": "Alice", "age": 30, "scores": [90, 85, 92]}
json_str = json.dumps(data, ensure_ascii=False, indent=2)

# JSON 字符串 → Python 对象
parsed = json.loads(json_str)

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

# 从文件读取
with open("data.json", "r", encoding="utf-8") as f:
    loaded = json.load(f)

import json
from datetime import datetime

class DateTimeEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

data = {"created": datetime.now()}
print(json.dumps(data, cls=DateTimeEncoder, ensure_ascii=False))

# pip install pyyaml
import yaml

# 读取
with open("config.yaml", "r", encoding="utf-8") as f:
    config = yaml.safe_load(f)

# 写入
data = {"database": {"host": "localhost", "port": 5432}}
with open("config.yaml", "w", encoding="utf-8") as f:
    yaml.dump(data, f, default_flow_style=False, allow_unicode=True)

import xml.etree.ElementTree as ET

# 解析 XML
tree = ET.parse("data.xml")
root = tree.getroot()

# 遍历
for child in root:
    print(child.tag, child.attrib)

# 查找
for elem in root.iter("item"):
    print(elem.text)

# 创建 XML
root = ET.Element("data")
item = ET.SubElement(root, "item")
item.text = "Hello"
item.set("id", "1")
tree = ET.ElementTree(root)
tree.write("output.xml", xml_declaration=True, encoding="utf-8")

import json
import csv
from pathlib import Path
from dataclasses import dataclass, asdict

@dataclass
class Employee:
    name: str
    department: str
    salary: float

def export_to_formats(employees: list[Employee], base_path: Path):
    """导出员工数据为多种格式。"""
    base_path.mkdir(parents=True, exist_ok=True)
    data = [asdict(e) for e in employees]
    
    # JSON
    (base_path / "employees.json").write_text(
        json.dumps(data, ensure_ascii=False, indent=2),
        encoding="utf-8",
    )
    
    # CSV
    with open(base_path / "employees.csv", "w", newline="", encoding="utf-8") as f:
        writer = csv.DictWriter(f, fieldnames=["name", "department", "salary"])
        writer.writeheader()
        writer.writerows(data)
    
    print(f"已导出到 {base_path}")

employees = [
    Employee("Alice", "工程", 20000),
    Employee("Bob", "设计", 18000),
]

export_to_formats(employees, Path("output"))