10

At one point or another you might come over functions with a lot of arguments. Sometimes it makes sense to combine some of the arguments into super-arguments. I've often done this with dicts, but now I'm looking at better ways of doing it.

I'd like to turn ...

def do_something(ax, ay, az, bu, bv, c):
    # Do something

... into ...

def do_something(a, b, c):
    # Do something

... where a and b contain their subvariations.

One way to do this is to do:

A = namedtuple('A', 'x, y, z')
a = A(ax, ay, az)
B = namedtuple('B', 'u, v')
b = B(bu, bv)

However, this seems simpler:

a = SimpleNamespace(x=ax, y=ay, z=az)
b = SimpleNamespace(u=bu, v=bv)

What is the drawback? The fact that a and b aren't well typed? They aren't A and B objects?

(Btw, don't worry about the variable names. I don't normally use as short variable names.)

  • 1
    There is no drawbacks per se, they are just different things. For starter namedtuples are inmutable while namespaces are mutable. Is mutable better or worse than inmutable? It depends on what you need or want, in many cases it just doesn't matter. You function would probably work with any object with the required attributes, how to build it is up to the caller. – Goyo May 28 '17 at 14:10
  • @Goyo Thank you. The "drawback" thing was a clumsy way of saying it. I didn't mean to imply one is inherently better than the other. Just wanted the pros and cons. Thanks, again. – André Christoffer Andersen May 28 '17 at 16:07
  • 1
    shouldn't the 4th line look like "b = B(bu, bv)"? – Alen Siljak Dec 22 '17 at 19:19
  • @AlenSiljak Yes it should. I'll fix it now. – André Christoffer Andersen Nov 11 '18 at 8:27
18

SimpleNamespace is basically just a nice facade on top of a dictionary. It allows you to use properties instead of index keys. This is nice as it is super flexible and easy to manipulate.

The downside of that flexibility is that it doesn't provide any structure. There is nothing to stop someone from calling SimpleNamespace(x=ax, y=ay) (and del a.z at some point later). If this instance gets passed to your function, the exception occurs when you try to access the field.

In contrast, namedtuple lets you create a structured type. The type will have a name and it will know what fields it is supposed to have. You won't be able to make an instance without each of those field and they can't be removed later. Additionally, the instance is immutable, so you will know that the value in a.x will always be the same.

It's up to you to decide if you need the flexibility that SimpleNamespace gives you, or if you prefer to have the structure and guarantees provided by namedtuple.

1

I really like the answer about structured versus not, so I'm just providing a concrete example below.

SimpleNamespace will accept keys that begin with _. If you're looking for a quick and easy way to turn, say, JSON you don't control into objects with field names, this is very handy:

d = {"_id": 2342122, "text": "hi there!"} # Elasticsearch gives this id!
e = SimpleNamespace(**d) # works
Name = namedtuple("Name", sorted(d)) # ValueError so we can't do Name(**d)

Note above that you can see that namedtuple gives us a whole extra object that SimpleNamespace never will. Each SimpleNamespace is really a "unique snowflake", whereas namedtuple exists without ever being instantiated with any concrete values. Wherever you have need of abstractions that generalize on concrete values, you probably should prefer it.

1

Summary of SimpleNamespace

It allows to initialize attributes while constructing the object:

sn = SimpleNamespace(a=1, b=2)

It provides a readable

repr(): eval(repr(sn)) == sn

It overrides the default comparison. Instead of comparing by id(), it compares attribute values instead.

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