Python's namedtuple can be really useful as a lightweight, immutable data class. I like using them for bookkeeping parameters rather than dictionaries. When some more functionality is desired, such as a simple docstring or default values, you can easily refactor the namedtuple to a class. However, I've seen classes that inherit from namedtuple. What functionality are they gaining, and what performance are they losing? For example, I would implement this as
from collections import namedtuple class Pokemon(namedtuple('Pokemon', 'name type level')): """ Attributes ---------- name : str What do you call your Pokemon? type : str grass, rock, electric, etc. level : int Experience level [0, 100] """ __slots__ = ()
For the sole purpose of being able to document the attrs cleanly, and __slots__
is used to prevent the creation of a __dict__
(keeping the lightweight nature of namedtuples).
Is there a better recommendation of a lightweight data class for documenting parameters? Note I'm using Python 2.7.
The NamedTuple is another class, under the collections module. Like the dictionary type objects, it contains keys and that are mapped to some values. In this case we can access the elements using keys and indexes. To use it at first we need to import it the collections standard library module. import collections.
Python's namedtuple() is a factory function available in collections . It allows you to create tuple subclasses with named fields. You can access the values in a given named tuple using the dot notation and the field names, like in obj.
NamedTuple . The class created from typing.
Since a named tuple is a tuple, and tuples are immutable, it is impossible to change the value of a field.
NEW UPDATE:
In python 3.6+, you can use the new typed syntax and create a typing.NamedTuple
. The new syntax supports all the usual python class creation features (docstrings, multiple inheritance, default arguments, methods, etc etc are available as of 3.6.1):
import typing class Pokemon(MyMixin, typing.NamedTuple): """ Attributes ---------- name : str What do you call your Pokemon? type : str grass, rock, electric, etc. level : int Experience level [0, 100] """ name: str type: str level: int = 0 # 3.6.1 required for default args def method(self): # method work
The class objects created by this version are mostly equivalent to the original collections.namedtuple
, except for a few details.
You can also use the same syntax as the old named tuple:
Pokemon = typing.NamedTuple('Pokemon', [('name', str), ('type', str), ('level', int)])
Original Answer
Short answer: no, unless you are using Python < 3.5
The P3 docs seem to imply pretty clearly that unless you need to add calculated fields (i.e., descriptors), subclassing namedtuple
is not considered the canonical approach. This is because you can update the docstrings directly (they are now writable as of 3.5!).
Subclassing is not useful for adding new, stored fields. Instead, simply create a new named tuple type from the
_fields
attribute...Docstrings can be customized by making direct assignments to the
__doc__
fields...
UPDATE:
There are now a couple other compelling possibilities for lightweight data classes in the latest versions of Python.
One is types.SimpleNamespace
(Python 3.3 and later). It is not structured like namedtuple
, but structure isn't always necessary.
One thing to note about SimpleNamespace
: by default it is required to explicitly designate the field names when instantiating the class. This can be got around fairly easily, though, with a call to super().__init__
:
from types import SimpleNamespace class Pokemon(SimpleNamespace): """ Attributes ---------- name : str What do you call your Pokemon? type : str grass, rock, electric, etc. level : int Experience level [0, 100] """ __slots__ = ("name", "type", "level") # note that use of __init__ is optional def __init__(self, name, type, level): super().__init__(name=name, type=type, level=level)
Another intriguing option- which is available as of Python 3.7 - is dataclasses.dataclass
(see also PEP 557):
from dataclasses import dataclass @dataclass class Pokemon: __slots__ = ("name", "type", "level") name: str # What do you call your Pokemon? type: str # grass, rock, electric, etc. level: int = 0 # Experience level [0, 100]
Note that both of these suggestions are mutable by default, and that __slots__
is not required for either one.
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