I am working in CoNaLa dataset contains high-quality natural language intent and source code snippet pairs in Python. The data are stored in JSON format, and you can see some examples below:
{
"example": 1,
"intent": "copying one file's contents to another in python",
"snippet": "shutil.copy(source_file, target_file)",
},
{
"example": 2
"intent": "How do I check if all elements in a list are the same?",
"snippet": "len(set(mylist)) == 1",
}
{
"example": 3
"intent": "Iterate through words of a file in Python",
"snippet": "words = open(my_file).read().split()"
}
I am looking for an approach to encapsulate each of the code snippets into a function. However to accomplish that I would have to infer which parameters this function should contain. In example 1, for instance, function declaration could be:
def function_name (source_file, target_file):
where function_name can be a generic name but the parameters should be source_file and target_file because they must be known in shutil.copy method.
For examples 2 and 3 the expected result would be respectively:
def function_name (myList):
and
def function_name (my_file):
