[FEATURE] allow for all kwargs when using @log_step

Hi,

When using @log_step in debugging a Pandas Pipeline, the current function must accept a single argument of df:pd.Dataframe.

However if the user sends all the parameters as kwargs there is an error .

It would be useful if the @log_step will check the first kwargs and if it is a pd.Dataframe then it will convert it into an arg - possible implementation before running the def wrapper() as follows

    _kwargs = {**kwargs}
    first_arg= next(iter(_kwargs))
    if isinstance(_kwargs[first_arg],pd.DataFrame) and len(args)==0:
        args=args+(_kwargs.pop[first_arg],)

[MBrouns]

I’m not sure if changing args directly is a great way to solve this because we use it later in result = func(*args, **kwargs)

Maybe something like this?

if shape_delta:
    if len(args) > 0:
        old_shape = args[0].shape
    else: 
        for v in kwargs.values:
              if isinstance(v, pd.DataFrame):
                  old_shape = v.shape
                  break
         else:
               raise ValueError("shape_delta was set to true, but no DataFrame instance was found as either the first non-keyword argument or in the keyword arguments")

[sephib]

If you think this is a good direction I’ll be happy to submit a PR