详解Python中namedtuple的使用

 from collections import namedtuple # 基本例子 Point = namedtuple('Point',['x','y']) # 类名为Point,属性有'x'和'y' p = Point(11, y=22) # 用位置或关键字参数实例化，因为'x'在'y'前，所以x=11,和函数参数赋值一样的 print(p[0]+p[1]) # 我们也可以使用下标来访问 # 33 x, y = p # 也可以像一个元组那样解析 print(x,y) # (11, 22) print(p.x+p.y) # 也可以通过属性名来访问 # 33 print(p) # 通过内置的__repr__函数，显示该对象的信息 # Point(x=11, y=22)

 t = [11, 22] # 列表 list p = Point._make(t) # 从列表中直接赋值，返回对象 print(Point(x=11, y=22)) # Point(x=11, y=22)

 p = Point(x=11, y=22) # 新建一个对象 d = p._asdict() # 解析并返回一个字典对象 print(d) # {'x': 11, 'y': 22}

 p = Point(x=11, y=22) # x=11,y=22 print(p) # Point(x=11, y=22) d = p._replace(x=33) # x=33,y=22 新的对象 print(p) # Point(x=11, y=22) print(d) # Point(x=33, y=22)

 print(p._fields) # 查看属性名 # ('x', 'y') Color = namedtuple('Color', 'red green blue') Pixel = namedtuple('Pixel', Point._fields + Color._fields) # 新建一个子类，使用多个属性名 q = Pixel(11, 22, 128, 255, 0) print(q) 

 Account = namedtuple('Account', ['type', 'balance'], defaults=[0]) print(Account._field_defaults) #{'balance': 0} print(Account('premium')) #Account(type='premium', balance=0)

 print(getattr(p, 'x')) # 11

 d = {'x': 11, 'y': 22} # 字典 p = Point(**d) # 双星号是重点 print(p) # Point(x=11, y=22)

 EmployeeRecord = namedtuple('EmployeeRecord', 'name, age, title, department, paygrade') import csv for emp in map(EmployeeRecord._make, csv.reader(open("employees.csv", "r"))): # 这里每行返回一个对象 注意！ print(emp.name, emp.title) import sqlite3 conn = sqlite3.connect('/companydata') # 连接数据库 cursor = conn.cursor() cursor.execute('SELECT name, age, title, department, paygrade FROM employees') for emp in map(EmployeeRecord._make, curs<i style="color:transparent">来源gaodai$ma#com搞$$代**码)网</i>or.fetchall()): # 每行返回一个对象 注意！ print(emp.name, emp.title)

 NODES = "nodes" EDGES = "edges" RECEIVERS = "receivers" SENDERS = "senders" GLOBALS = "globals" N_NODE = "n_node" N_EDGE = "n_edge" GRAPH_DATA_FIELDS = (NODES, EDGES, RECEIVERS, SENDERS, GLOBALS) GRAPH_NUMBER_FIELDS = (N_NODE, N_EDGE) class GraphsTuple( # 定义元组子类名 以及字典形式的键名（属性名） collections.namedtuple("GraphsTuple", GRAPH_DATA_FIELDS + GRAPH_NUMBER_FIELDS)): # 这个函数用来判断依赖是否满足，和我们的namedtuple关系不大 def _validate_none_fields(self): """Asserts that the set of `None` fields in the instance is valid.""" if self.n_node is None: raise ValueError("Field `n_node` cannot be None") if self.n_edge is None: raise ValueError("Field `n_edge` cannot be None") if self.receivers is None and self.senders is not None: raise ValueError( "Field `senders` must be None as field `receivers` is None") if self.senders is None and self.receivers is not None: raise ValueError( "Field `receivers` must be None as field `senders` is None") if self.receivers is None and self.edges is not None: raise ValueError( "Field `edges` must be None as field `receivers` and `senders` are " "None") # 用来初始化一些参数 不是重点 def __init__(self, *args, **kwargs): del args, kwargs # The fields of a `namedtuple` are filled in the `__new__` method. # `__init__` does not accept parameters. super(GraphsTuple, self).__init__() self._validate_none_fields() # 这就用到了_replace()函数,注意只要修改了属性值 # 那么就返回一个新的对象 def replace(self, **kwargs): output = self._replace(**kwargs) # 返回一个新的实例 output._validate_none_fields() # pylint: disable=protected-access 验证返回的新实例是否满足要求 return output # 这是为了针对tensorflow1版本的函数 # 返回一个拥有相同属性的对象，但是它的属性值是输入的大小和类型 def map(self, field_fn, fields=GRAPH_FEATURE_FIELDS): # 对每个键应用函数 """Applies `field_fn` to the fields `fields` of the instance. `field_fn` is applied exactly once per field in `fields`. The result must satisfy the `GraphsTuple` requirement w.r.t. `None` fields, i.e. the `SENDERS` cannot be `None` if the `EDGES` or `RECEIVERS` are not `None`, etc. Args: field_fn: A callable that take a single argument. fields: (iterable of `str`). An iterable of the fields to apply `field_fn` to. Returns: A copy of the instance, with the fields in `fields` replaced by the result of applying `field_fn` to them. """ return self.replace(**{k: field_fn(getattr(self, k)) for k in fields}) # getattr(self, k) 获取的是键值对中的值, k表示键