python collections 模块 之namedtuple
namedtuple
collections.namedtuple(typename, filed_name, *, rename=False, module=None)
创建一个以 typename 命名的 tuple 子类,这个子类用于创建类元组对象,这些对象可以像元组一样被索引和迭代。
field_name: 指定 namedtuple 的字段名,可以是列表,可以是用空格或逗号隔开的字符串。
rename: field_name 中无效的标识符(字符,数字,下划线,并且不以下划线或数字开头,不与内置变量名冲突)将被自动替换为下划线加索引(例:_1),
module: 设置__module__的值,默认为 '__main__'
from collections import namedtuple
Point = namedtuple('Point', ['x', 'y'])
a = Point(1, 2)
输出:
>>> a[0]
1
>>> a[1]
2
>>> a.x
1
>>> a.y
2
>>> c,d = a
>>> c, d
(1, 2)
namedtuple 除了继承 tuples 的方法外,还有3个额外的方法和2个额外的属性:
classmethod somenamedtuple._make(iterable)
用已存在的列表或可迭代对象创建 namedtuple 实例:
>>> t = [1, 2]
>>> Point._make(t)
Point(x=1, y=2)
somenamedtuple._asdict()
将 namedtuple 转变为 OrderDict
>>> p = Point(x=11, y=22)
>>> p._asdict()
OrderedDict([('x', 11), ('y', 22)])
somenamedtuple._replace()
替换属性值,返还一个新的对象
>>> p = Point(x=11, y=22)
>>> p._replace(x=33)
Point(x=33, y=22)
_replace() 还有一个很有用的特性,就是当你的命名元组拥有可选字段或者缺失字段的时候,它能够方便的添加数据。
from collections import namedtuple
Stock = namedtuple('Stock', ['name', 'shares', 'price', 'date', 'time'])
# Create a prototype instance
stock_prototype = Stock('', 0, 0.0, None, None)
# Function to convert a dictionary to a Stock
def dict_to_stock(s):
return stock_prototype._replace(**s)
>>> a = {'name': 'ACME', 'shares': 100, 'price': 123.45}
>>> dict_to_stock(a)
Stock(name='ACME', shares=100, price=123.45, date=None, time=None)
>>> b = {'name': 'ACME', 'shares': 100, 'price': 123.45, 'date': '12/17/2012'}
>>> dict_to_stock(b)
Stock(name='ACME', shares=100, price=123.45, date='12/17/2012', time=None)
>>>
somenamedtuple._source()
somenamedtuple._fields
返回一个元祖,包含所有的属性
>>> p._fields # view the field names
('x', 'y')
>>> Color = namedtuple('Color', 'red green blue')
>>> Pixel = namedtuple('Pixel', Point._fields + Color._fields)
>>> Pixel(11, 22, 128, 255, 0)
Pixel(x=11, y=22, red=128, green=255, blue=0)
将字典转变为 namedtuple:
>>> d = {'x': 11, 'y': 22}
>>> Point(**d)
Point(x=11, y=22)
默认值可以通过 _replace() 来重新定义,例:
>>> Account = namedtuple('Account', 'owner balance transaction_count')
>>> default_account = Account('<owner name>', 0.0, 0)
>>> johns_account = default_account._replace(owner='John')
>>> janes_account = default_account._replace(owner='Jane')
# _replace()返回一个新的实例
源码分析
def namedtuple(typename, field_names, *, rename=False, defaults=None, module=None):
"""Returns a new subclass of tuple with named fields. >>> Point = namedtuple('Point', ['x', 'y'])
>>> Point.__doc__ # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22) # instantiate with positional args or keywords
>>> p[0] + p[1] # indexable like a plain tuple
33
>>> x, y = p # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y # fields also accessible by name
33
>>> d = p._asdict() # convert to a dictionary
>>> d['x']
11
>>> Point(**d) # convert from a dictionary
Point(x=11, y=22)
>>> p._replace(x=100) # _replace() is like str.replace() but targets named fields
Point(x=100, y=22) """ # Validate the field names. At the user's option, either generate an error
# message or automatically replace the field name with a valid name.
if isinstance(field_names, str):
field_names = field_names.replace(',', ' ').split()
field_names = list(map(str, field_names))
typename = _sys.intern(str(typename)) # 使用字符串驻留机制
if rename:
seen = set()
for index, name in enumerate(field_names):
# enumerate 将一个可遍历的数据对象组合成一个索引序列, 返回一个enumerate对象,可以用for遍历,返回索引和值
# isidentifier 判断变量名知否合法, _iskeyword() 判断是否为内置关键字
if (not name.isidentifier()
or _iskeyword(name)
or name.startswith('_')
or name in seen):
field_names[index] = f'_{index}' # f'' ==> 字符串格式化
seen.add(name) for name in [typename] + field_names:
if type(name) is not str:
raise TypeError('Type names and field names must be strings')
if not name.isidentifier():
raise ValueError('Type names and field names must be valid '
f'identifiers: {name!r}') # !r 反映对象本体
if _iskeyword(name):
raise ValueError('Type names and field names cannot be a '
f'keyword: {name!r}') seen = set()
for name in field_names:
if name.startswith('_') and not rename:
raise ValueError('Field names cannot start with an underscore: '
f'{name!r}')
if name in seen:
raise ValueError(f'Encountered duplicate field name: {name!r}')
seen.add(name)
# 为字段设置默认值,靠右
field_defaults = {}
if defaults is not None:
defaults = tuple(defaults)
if len(defaults) > len(field_names):
raise TypeError('Got more default values than field names')
field_defaults = dict(reversed(list(zip(reversed(field_names),
reversed(defaults))))) # Variables used in the methods and docstrings
field_names = tuple(map(_sys.intern, field_names))
num_fields = len(field_names)
arg_list = repr(field_names).replace("'", "")[1:-1]
repr_fmt = '(' + ', '.join(f'{name}=%r' for name in field_names) + ')'
tuple_new = tuple.__new__
_len = len # Create all the named tuple methods to be added to the class namespace s = f'def __new__(_cls, {arg_list}): return _tuple_new(_cls, ({arg_list}))'
namespace = {'_tuple_new': tuple_new, '__name__': f'namedtuple_{typename}'}
# Note: exec() has the side-effect of interning the field names
exec(s, namespace) # 执行 s 中的python 语句,namespace为参数,将__new__添加至 namespace
__new__ = namespace['__new__']
__new__.__doc__ = f'Create new instance of {typename}({arg_list})'
if defaults is not None:
__new__.__defaults__ = defaults @classmethod
def _make(cls, iterable):
result = tuple_new(cls, iterable) # 实例化
if _len(result) != num_fields:
raise TypeError(f'Expected {num_fields} arguments, got {len(result)}')
return result _make.__func__.__doc__ = (f'Make a new {typename} object from a sequence '
'or iterable') def _replace(_self, **kwds):
result = _self._make(map(kwds.pop, field_names, _self))
if kwds:
raise ValueError(f'Got unexpected field names: {list(kwds)!r}')
return result _replace.__doc__ = (f'Return a new {typename} object replacing specified '
'fields with new values') def __repr__(self):
'Return a nicely formatted representation string'
return self.__class__.__name__ + repr_fmt % self def _asdict(self):
'Return a new OrderedDict which maps field names to their values.'
return OrderedDict(zip(self._fields, self)) def __getnewargs__(self):
'Return self as a plain tuple. Used by copy and pickle.'
return tuple(self) # Modify function metadata to help with introspection and debugging for method in (__new__, _make.__func__, _replace,
__repr__, _asdict, __getnewargs__):
method.__qualname__ = f'{typename}.{metho .__name__}' # Build-up the class namespace dictionary
# and use type() to build the result class
# 类的各个属性和方法
class_namespace = {
'__doc__': f'{typename}({arg_list})',
'__slots__': (),
'_fields': field_names,
'_fields_defaults': field_defaults,
'__new__': __new__,
'_make': _make,
'_replace': _replace,
'__repr__': __repr__,
'_asdict': _asdict,
'__getnewargs__': __getnewargs__,
}
cache = _nt_itemgetters
# 将属性与属性值对应起来
for index, name in enumerate(field_names):
try:
itemgetter_object, doc = cache[index]
except KeyError:
itemgetter_object = _itemgetter(index)
doc = f'Alias for field number {index}'
cache[index] = itemgetter_object, doc
class_namespace[name] = property(itemgetter_object, doc=doc) result = type(typename, (tuple,), class_namespace) # 动态创建类 # For pickling to work, the __module__ variable needs to be set to the frame
# where the named tuple is created. Bypass this step in environments where
# sys._getframe is not defined (Jython for example) or sys._getframe is not
# defined for arguments greater than 0 (IronPython), or where the user has
# specified a particular module.
if module is None:
try:
module = _sys._getframe(1).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
if module is not None:
result.__module__ = module return result
python collections 模块 之namedtuple的更多相关文章
- Python的collections模块中namedtuple结构使用示例
namedtuple顾名思义,就是名字+元组的数据结构,下面就来看一下Python的collections模块中namedtuple结构使用示例 namedtuple 就是命名的 tuple,比较 ...
- Python collections模块总结
Python collections模块总结 除了我们使用的那些基础的数据结构,还有包括其它的一些模块提供的数据结构,有时甚至比基础的数据结构还要好用. collections ChainMap 这是 ...
- (转)python collections模块详解
python collections模块详解 原文:http://www.cnblogs.com/dahu-daqing/p/7040490.html 1.模块简介 collections包含了一些特 ...
- python collections模块
collections模块基本介绍 collections在通用的容器dict,list,set和tuple之上提供了几个可选的数据类型 namedtuple() factory function f ...
- collections 模块(namedtuple, deque, Counter )
基本介绍 我们都知道,Python拥有一些内置的数据类型,比如str, int, list, tuple, dict等, collections模块在这些内置数据类型的基础上,提供了几个额外的数据类型 ...
- Python collections 模块用法举例
Python作为一个“内置电池”的编程语言,标准库里面拥有非常多好用的模块.比如今天想给大家 介绍的 collections 就是一个非常好的例子. 1.collections模块基本介绍 我们都知道 ...
- Python——collections模块、time模块、random模块、os模块、sys模块
1. collections模块 (1)namedtuple # (1)点的坐标 from collections import namedtuple Point = namedtuple('poin ...
- python collections模块详解
参考老顽童博客,他写的很详细,例子也很容易操作和理解. 1.模块简介 collections包含了一些特殊的容器,针对Python内置的容器,例如list.dict.set和tuple,提供了另一种选 ...
- Python——collections模块
collections模块 collections模块在内置数据类型(dict.list.set.tuple)的基础上,还提供了几个额外的数据类型:ChainMap.Counter.deque.def ...
随机推荐
- <每日一题>题目5:生成器表达式面试题
题目: def demo(): for i in range(4): yield i g = demo() g1 = (i for i in g ) g2 = (i for i in g1) prin ...
- wpf 定时器应用,在界面动态刷新时间
DispatcherTimer = new DispatcherTimer(); Timer.Tick += Timer_Tick; Timer.Interval = TimeSpan.FromSec ...
- matlab-使用技巧
sel(1:100); 1 2 3 4 5 ...100 X(sel, :); 1.......2.......3.......4.......5..........100...... nn_para ...
- opencv-图像遍历
#include "stdafx.h" #include<opencv2/opencv.hpp> #include<iostream> #include&l ...
- art-template官方文档
http://aui.github.io/art-template/zh-cn/docs/
- 0809NOIP模拟测试赛后总结
终于有点脸单独建一个随笔写一下考试总结了…… T1一眼组合数学,推了一会儿式子发现恐怕是容斥.突然害怕,于是开始大力dp. 然后骗了70分走人hhh. T2挂了……又读错题了……以为必须相邻,然后就原 ...
- 二分图——poj2446匈牙利算法
/* 怎么建图: 首先分集合:不能相连的点必然在一个集合里,即对角点 再确定怎么连边: 一个点可以向上下左右连边,如果遇到了洞则不行 dfs(i),让匹配到的点接受i作为match结果 寻找增广路时, ...
- TSP+期望——lightoj1287记忆化搜索,好题!
感觉是很经典的题 记忆化时因为不好直接通过E判断某个状态是否已经求过,所以再加一个vis打标记即可 /*E[S][u]表示从u出发当前状态是S的期望*/ #include<bits/stdc++ ...
- js摇一摇事件
今早同事过来说.要做个小游戏.里面有个摇一摇动作. 平时都是做的手机营销h5比较少. 发现很有意思. 一时间没有反应过来. 怎么实现的摇一摇. 现在吧代码叠出来给2货的我. //运动事件监听if ...
- 容器安全与EDR的异同
以Docker为代表的容器技术,直接运行于宿主机操作系统内核,因此对于容器安全,很多人会有着这样的疑问:EDR(Endpoint Detection and Response)等主机安全方案,能否直接 ...