Answer: d) is a bad idea because the default [] will accumulate data and the default [] will change with subsequent calls.
Return Type: Returns an empty list if no parameters are passed. If a parameter is passed then it returns a list of elements in the iterable.
In this solution, we use the len() to check if a list is empty, this function returns the length of the argument passed. And given the length of an empty list is 0 it can be used to check if a list is empty in Python.
You can define Python function optional arguments by specifying the name of an argument followed by a default value when you declare a function. You can also use the **kwargs method to accept a variable number of arguments in a function. To learn more about coding in Python, read our How to Learn Python guide.
def my_func(working_list=None):
if working_list is None:
working_list = []
# alternative:
# working_list = [] if working_list is None else working_list
working_list.append("a")
print(working_list)
The docs say you should use None
as the default and explicitly test for it in the body of the function.
Other answers have already already provided the direct solutions as asked for, however, since this is a very common pitfall for new Python programmers, it's worth adding the explanation of why Python behaves this way, which is nicely summarized in The Hitchhikers Guide to Python under Mutable Default Arguments:
Python's default arguments are evaluated once when the function is defined, not each time the function is called (like it is in say, Ruby). This means that if you use a mutable default argument and mutate it, you will and have mutated that object for all future calls to the function as well.
Not that it matters in this case, but you can use object identity to test for None:
if working_list is None: working_list = []
You could also take advantage of how the boolean operator or is defined in python:
working_list = working_list or []
Though this will behave unexpectedly if the caller gives you an empty list (which counts as false) as working_list and expects your function to modify the list he gave it.
If the intent of the function is to modify the parameter passed as working_list
, see HenryR's answer (=None, check for None inside).
But if you didn't intend to mutate the argument, just use it as starting point for a list, you can simply copy it:
def myFunc(starting_list = []):
starting_list = list(starting_list)
starting_list.append("a")
print starting_list
(or in this simple case just print starting_list + ["a"]
but I guess that was just a toy example)
In general, mutating your arguments is bad style in Python. The only functions that are fully expected to mutate an object are methods of the object. It's even rarer to mutate an optional argument — is a side effect that happens only in some calls really the best interface?
If you do it from the C habit of "output arguments", that's completely unnecessary - you can always return multiple values as a tuple.
If you do this to efficiently build a long list of results without building intermediate lists, consider writing it as a generator and using result_list.extend(myFunc())
when you are calling it. This way your calling conventions remains very clean.
One pattern where mutating an optional arg is frequently done is a hidden "memo" arg in recursive functions:
def depth_first_walk_graph(graph, node, _visited=None):
if _visited is None:
_visited = set() # create memo once in top-level call
if node in _visited:
return
_visited.add(node)
for neighbour in graph[node]:
depth_first_walk_graph(graph, neighbour, _visited)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With