Python namedtuple命名元组详解 - 替代字典的轻量方案

from collections import namedtuple

# 创建命名元组类
ClassName = namedtuple('ClassName', ['field1', 'field2', ...])
ClassName = namedtuple('ClassName', 'field1 field2 ...')
ClassName = namedtuple('ClassName', 'field1,field2,...')

# 创建实例
obj = ClassName(value1, value2, ...)
obj = ClassName(field1=value1, field2=value2, ...)

from collections import namedtuple

# 创建命名元组类
Point = namedtuple('Point', ['x', 'y'])
Person = namedtuple('Person', 'name age email')

# 创建实例
p1 = Point(3, 4)
p2 = Point(x=1, y=2)

person = Person(name="张三", age=25, email="zhangsan@example.com")

# 通过字段名访问
print(f"点坐标: ({p1.x}, {p1.y})")
print(f"距离原点: {(p1.x**2 + p1.y**2)**0.5:.1f}")

# 通过索引访问（兼容普通元组）
print(f"\n索引访问: p1[0]={p1[0]}, p1[1]={p1[1]}")

# 解包
x, y = p2
print(f"解包: x={x}, y={y}")

# 字段信息
print(f"\n字段名: {Point._fields}")
print(f"类型: {type(p1).__name__}")
print(f"是元组: {isinstance(p1, tuple)}")

点坐标: (3, 4)
距离原点: 5.0

索引访问: p1[0]=3, p1[1]=4

解包: x=1, y=2

字段名: ('x', 'y')
类型: Point
是元组: True

from collections import namedtuple

Student = namedtuple('Student', ['name', 'score', 'grade'])

# 创建实例
s = Student(name="李四", score=85, grade="B")

# _asdict：转换为字典
s_dict = s._asdict()
print(f"字典: {dict(s_dict)}")

# _replace：替换字段（返回新实例，原实例不变）
s_updated = s._replace(score=92, grade="A")
print(f"\n原实例: {s}")
print(f"更新后: {s_updated}")

# _make：从可迭代对象创建
data = ["王五", 78, "C"]
s_new = Student._make(data)
print(f"\n从列表创建: {s_new}")

# 默认值（Python 3.7+）
Config = namedtuple('Config', ['host', 'port', 'timeout'],
                    defaults=['localhost', 8080, 30])
c1 = Config('example.com')  # port和timeout使用默认值
c2 = Config('example.com', 9090)  # timeout使用默认值
print(f"\n部分默认值: {c1}")
print(f"覆盖默认值: {c2}")

字典: {'name': '李四', 'score': 85, 'grade': 'B'}

原实例: Student(name='李四', score=85, grade='B')
更新后: Student(name='李四', score=92, grade='A')

从列表创建: Student(name='王五', score=78, grade='C')

部分默认值: Config(host='example.com', port=8080, timeout=30)
覆盖默认值: Config(host='example.com', port=9090, timeout=30)

from collections import namedtuple
import csv
from io import StringIO

# 定义数据记录
Employee = namedtuple('Employee', ['id', 'name', 'department', 'salary'])

# 模拟CSV数据
csv_data = """id,name,department,salary
1,张三,技术部,15000
2,李四,市场部,12000
3,王五,技术部,18000
4,赵六,人事部,10000
5,钱七,技术部,20000
"""

# 从CSV读取并创建命名元组
reader = csv.DictReader(StringIO(csv_data))
employees = [Employee(**row) for row in reader]

# 数据查询
print("员工列表:")
for emp in employees:
    print(f"  {emp.id}. {emp.name} - {emp.department} - ¥{emp.salary}")

# 按部门统计
departments = {}
for emp in employees:
    departments.setdefault(emp.department, []).append(emp)

print(f"\n部门人数:")
for dept, emps in departments.items():
    avg_salary = sum(int(e.salary) for e in emps) / len(emps)
    print(f"  {dept}: {len(emps)}人, 平均薪资¥{avg_salary:.0f}")

# 使用_replace更新数据
updated = employees[0]._replace(salary="16000")
print(f"\n调薪: {employees[0].name} ¥{employees[0].salary} -> ¥{updated.salary}")

员工列表:
  1. 张三 - 技术部 - ¥15000
  2. 李四 - 市场部 - ¥12000
  3. 王五 - 技术部 - ¥18000
  4. 赵六 - 人事部 - ¥10000
  5. 钱七 - 技术部 - ¥20000

部门人数:
  技术部: 3人, 平均薪资¥17667
  市场部: 1人, 平均薪资¥12000
  人事部: 1人, 平均薪资¥10000

调薪: 张三 ¥15000 -> ¥16000