Python dynamic function creation with custom names
Apologies if this question has already been raised and answered. What I need to do is very simple in concept, but unfortunately I have not been able to find an answer for it online.
I need to create dynamic functions in Python (Python2.7) with custom names at runtime. The body of each function also needs to be constructed at runtime but it is (almost) the same for all functions.
I start off with a list of names.
func_names = ["func1", "func2", "func3"]
Note that the func_name list can hold a list of arbitrary names, so the names will NOT simply be func1, func2, func3, ....
I want the outcome to be :
def func1(*args):
...
def func2(*args):
...
def func3(*args):
...
The reason I need to do this is that each function name corresponds to a test case which is then called from the outside world.
update: There is no user input. I'm tying two ends of a much bigger module. One end determines what the test cases are and among other things, populates a list of the test cases' names. The other end is the functions themselves, which must have 1:1 mapping with the name of the test case. So I have the name of the test cases, I know what I want to do with each test case, I just need to create the functions that have the name of the test cases. Since the name of the test cases are determined at runtime, the function creation based on those test cases must be at runtime as well.
update: I can also wrap this custom named functions in a class if that would make things easier.
I can hard-code the content of the functions (since they are almost the same) in a string, or I can base it off of a base class previously defined. Just need to know how to populate the functions with this content.
For example:
func_content = """
for arg in args:
print arg
"""
Thanks in advance,
Mahdi
For what you describe, I don't think you need to descend into eval or macros — creating function instances by closure should work just fine. Example:
def bindFunction1(name):
def func1(*args):
for arg in args:
print arg
return 42 # ...
func1.__name__ = name
return func1
def bindFunction2(name):
def func2(*args):
for arg in args:
print arg
return 2142 # ...
func2.__name__ = name
return func2
However, you will likely want to add those functions by name to some scope so that you can access them by name.
>>> print bindFunction1('neat')
<function neat at 0x00000000629099E8>
>>> print bindFunction2('keen')
<function keen at 0x0000000072C93DD8>
Extending on Shane's answer since I just found this question when looking for a solution to a similar problem. Take care with the scope of the variables. You can avoid scope problems by using a generator function to define the scope. Here is an example that defines methods on a class:
class A(object):
pass
def make_method(name):
def _method(self):
print("method {0} in {1}".format(name, self))
return _method
for name in ('one', 'two', 'three'):
_method = make_method(name)
setattr(A, name, _method)
In use:
In [4]: o = A()
In [5]: o.one()
method one in <__main__.A object at 0x1c0ac90>
In [6]: o1 = A()
In [7]: o1.one()
method one in <__main__.A object at 0x1c0ad10>
In [8]: o.two()
method two in <__main__.A object at 0x1c0ac90>
In [9]: o1.two()
method two in <__main__.A object at 0x1c0ad10>
There probably is a sort of introspection to do this kind of thing, but I don't think it would be the pythonic approach to the problem.
I think you should take advantage of the nature of functions in python as first level citizens. Use closures as Shane Holloway pointed, to customize the function contents as you like. Then for the dynamic name binding, use a dictionary whose keys are the names defined dynamically, and the values will be the functions itself.
def function_builder(args):
def function(more_args):
#do stuff based on the values of args
return function
my_dynamic_functions = {}
my_dynamic_functions[dynamic_name] = function_builder(some_dynamic_args)
#then use it somewhere else
my_dynamic_functions[dynamic_name](the_args)
Hope it makes sense to your use case.
You may want to use eval; you'll build the string containing the Python definition of each function (i.e. a multiline string starting with def func1
....) and you'll then eval
it.
But I would generate a unique name for each such function (e.g. genfun345
). Don't use some unchecked user input for such names. Because if the name is the same as some known name in Python, you are going into a difficult to debug disaster.
Do you trust the inputs from which these functions are made? Do you care about malware or abuse?
Read about hygenic macros on wikipedia.
To truly create functions dynamically, you can use makefun, I have developed it just for that. It supports three ways to define the signature to generate:
- a string representation, for example
'foo(a, b=1)'
- a
Signature
object, either handcrafted or derived by usinginspect.signature
on another function - a reference function. In that case the exposed signature will be identical to this function's signature.
Moreover you can tell it to inject the created function's reference as the first argument in your implementation, so as to have minor behavior modifications depending on where the call comes from (which facade). For example:
# generic core implementation
def generic_impl(f, *args, **kwargs):
print("This is generic impl called by %s" % f.__name__)
# here you could use f.__name__ in a if statement to determine what to do
if f.__name__ == "func1":
print("called from func1 !")
return args, kwargs
my_module = getmodule(generic_impl)
# generate 3 facade functions with various signatures
for f_name, f_params in [("func1", "b, *, a"),
("func2", "*args, **kwargs"),
("func3", "c, *, a, d=None")]:
# the signature to generate
f_sig = "%s(%s)" % (f_name, f_params)
# create the function dynamically
f = create_function(f_sig, generic_impl, inject_as_first_arg=True)
# assign the symbol somewhere (local context, module...)
setattr(my_module, f_name, f)
# grab each function and use it
func1 = getattr(my_module, 'func1')
assert func1(25, a=12) == ((), dict(b=25, a=12))
func2 = getattr(my_module, 'func2')
assert func2(25, a=12) == ((25,), dict(a=12))
func3 = getattr(my_module, 'func3')
assert func3(25, a=12) == ((), dict(c=25, a=12, d=None))
As you can see in the documentation, arguments are always redirected to the kwargs
except when it is absolutely not possible (var-positional signatures such as in func2
).