Can anyone amend namedtuple or provide an alternative class so that it works for mutable objects?
Primarily for readability, I would like something similar to namedtuple that does this:
from Camelot import namedgroup
Point = namedgroup('Point', ['x', 'y'])
p = Point(0, 0)
p.x = 10
>>> p
Point(x=10, y=0)
>>> p.x *= 10
Point(x=100, y=0)
It must be possible to pickle the resulting object. And per the characteristics of named tuple, the ordering of the output when represented must match the order of the parameter list when constructing the object.
There is a mutable alternative to collections.namedtuple
– recordclass.
It can be installed from PyPI:
pip3 install recordclass
It has the same API and memory footprint as namedtuple
and it supports assignments (It should be faster as well). For example:
from recordclass import recordclass
Point = recordclass('Point', 'x y')
>>> p = Point(1, 2)
>>> p
Point(x=1, y=2)
>>> print(p.x, p.y)
1 2
>>> p.x += 2; p.y += 3; print(p)
Point(x=3, y=5)
recordclass
(since 0.5) support typehints:
from recordclass import recordclass, RecordClass
class Point(RecordClass):
x: int
y: int
>>> Point.__annotations__
{'x':int, 'y':int}
>>> p = Point(1, 2)
>>> p
Point(x=1, y=2)
>>> print(p.x, p.y)
1 2
>>> p.x += 2; p.y += 3; print(p)
Point(x=3, y=5)
There is a more complete example (it also includes performance comparisons).
Recordclass
library now provides another variant -- recordclass.make_dataclass
factory function. It support dataclasses-like API (there are module level functions update
, make
, replace
instead of self._update
, self._replace
, self._asdict
, cls._make
methods).
from recordclass import dataobject, make_dataclass
Point = make_dataclass('Point', [('x', int), ('y',int)])
Point = make_dataclass('Point', {'x':int, 'y':int})
class Point(dataobject):
x: int
y: int
>>> p = Point(1, 2)
>>> p
Point(x=1, y=2)
>>> p.x = 10; p.y += 3; print(p)
Point(x=10, y=5)
recordclass
and make_dataclass
can produce classes, whose instances occupy less memory than __slots__
-based instances. This can be important for the instances with attribute values, which has not intended to have reference cycles. It may help reduce memory usage if you need to create millions of instances. Here is an illustrative example.