Is it really worth it?

Fact is, while it can shave off some lines of code,

I think it is interesting to know _which_ lines of code -

Usually when one writes a decorator, it is expected that they

will know what they are writing, and will want to be in control of

their code. Delegating this to a decorator-decorator that is to be

copied and pasted, and will definitely change call-order, and when

your decorator is called, is something that I, at least, would be wary

to use.

Meanwhile, when I want this pattern, it really takes me 2 LoC inside

the decorator to have the same functionality, and still be 100% in control

of when my function is called:

```

from functools import partial

def mydecorator(func=None, /, *, param1=None, **kwargs):

if func is None:

return partial(mydcorator, param1=None, **kwargs)

# decorator code goes here

...

```

So, yes, your proposal has some utility - but I consider it to be marginal -

it is the kind of stuff that I'd rather see on a 3rdy party package

with extra-stuff to help building decorators than on stdlib.

On Mon, 30 Nov 2020 at 17:04, Yurii Karabas <1998uriyyo@gmail.com> wrote:

The idea of `decorator_factory` is to eliminate boilerplate code that used to create a decorator with parameters.

A perfect example is how `dataclass` decorator can be simplified from this:
```
def dataclass(cls=None, /, *, init=True, repr=True, eq=True, order=False,
unsafe_hash=False, frozen=False):
def wrap(cls):
return _process_class(cls, init, repr, eq, order, unsafe_hash, frozen)

# See if we're being called as @dataclass or @dataclass().
if cls is None:
# We're called with parens.
return wrap

# We're called as @dataclass without parens.
return wrap(cls)
```
To this:
@functools.decorator_factory
def dataclass(cls, /, *, init=True, repr=True, eq=True, order=False,
unsafe_hash=False, frozen=False):
return _process_class(cls, init, repr, eq, order, unsafe_hash, frozen)
```
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