Python 3.7: Utility of Dataclasses and SimpleNameSpace

Python 3.7 provides new dataclasses which have predefined special functions.

dataclasses

From an overview point, dataclasses and SimpleNameSpace both provide nice data encapsulating facility.

dataclasses

SimpleNameSpace

@dataclass
class MyData:
name:str
age: int

data_1 = MyData(name = 'JohnDoe' , age = 23)

data_2 = SimpleNameSpace(name = 'JohnDoe' , age = 23)


A lot of times I use SimpleNameSpace just to wrap data and move it around.

SimpleNameSpace

I even subclass it to add special functions:

from types import SimpleNameSpace

class NewSimpleNameSpace(SimpleNameSpace):
def __hash__(self):
return some_hashing_func(self.__dict__)


For my question:

SimpleNameSpace

dataclasses

SimpleNameSpace

dataclasses

SimpleNamespace only adds the attributes and a __repr__. dataclass adds much more, e.g. __eq__, __hash__, ..
– L3viathan
Jun 28 at 12:05

__repr__

__eq__

__hash__

2 Answers
2

The short answer is that this is all covered by PEP 557. Taking your questions slightly out of order...

The PEP is quite clear that they are not a replacement and expect the other solutions to have their own place.

Like any other design decision, you'll therefore need to decide exactly what features you care about. If that includes the following, you definitely don't want dataclasses.

Where is it not appropriate to use Data Classes?

API compatibility with tuples or dicts is required.
Type validation beyond that provided by PEPs 484 and 526 is required, or value validation or conversion is required.

That said, the same is true for SimpleNameSpace, so what else can we look at to decide? Let's take a closer look at the extra features provided by dataclasses...

The existing definition of SimpleNameSpace is as follows:

A simple object subclass that provides attribute access to its namespace, as well as a meaningful repr.

The python docs then go on to say that it provides a simple __init__, __repr__ and __eq__ implementation. Comparing this to PEP 557, dataclasses also give you options for:

__init__

__repr__

__eq__

Clearly, then, you should use dataclasses if you care about ordering or immutability (or need the niche hashing control).

None that I can see, though you could argue that the initial "why?" covers other use cases.

I would point out that it also depends on how structured your data is. If there is a clear type/object model, dataclasses are more explicit as to what should be in the object. Also, class features like __slots__ makes more sense with dataclasses than SimpleNamespace
– Edward Minnix
Jun 29 at 12:02

__slots__

@EdwardMinnix Can you write that as an answer? It is a usecase worth discussing.
– xssChauhan
Jun 29 at 13:46

Dataclasses is much more like namedtuple and the popular attrs package than SimpleNamespace (which isn't even mentioned in the PEP). They serve two different intended purposes.

namedtuple

SimpleNamespace

Dataclasses

__init__

__hash__

__eq__

__slots__

SimpleNamespace

__slots__

From the SimpleNamespace documentation:

SimpleNamespace

SimpleNamespace may be useful as a replacement for class NS: pass. However, for a structured record type use namedtuple() instead.

class NS: pass

namedtuple()

Since @dataclass is supposed to replace a lot of the use cases of namedtuple, named records/structs should be done with @dataclass, not SimpleNamespace.

@dataclass

namedtuple

@dataclass

SimpleNamespace

You may also want to look at this PyCon talk by Raymond Hettinger, where he goes into the backstory of @dataclass and it's use.

@dataclass

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