Goes similar to previous answer, but why so complicated?
def do_call(what, args=[], kwargs = {}):
return what(*args, **kwargs)
(Which is more elegant than my previously posted definition:)
def do_call(which, args=None, kwargs = None):
if args is None and kwargs is not None:
return which(**kwargs)
elif args is not None and kwargs is None:
return which(*args)
else:
return which(*args, **kwargs)
Python's sum
is different than R's sum
(1 argument a list expected vs.
arbitraily many arguments expected in R). So we define our own sum (mysum
)
which behaves similarly to R's sum
. In a similar way we define mymean
.
def mysum(*args):
return sum(args)
def mymean(*args):
return sum(args)/len(args)
Now we can recreate your example in Python - as a reasonable 1:1 translation of the R function call.
do_call(what = mymean, args=[1, 2, 3])
## 2.0
do_call(what = mysum, args=[1, 2, 3])
## 6
For functions with argument names, we use a dict for kwargs, where the parameter
names are keys of the dictionary (as strings) and their values the values.
def myfunc(a, b, c):
return a + b + c
do_call(what = myfunc, kwargs={"a": 1, "b": 2, "c": 3})
## 6
# we can even mix named and unnamed parts
do_call(what = myfunc, args = [1, 2], kwargs={"c": 3})
## 6