On Fri, Apr 24, 2015 at 5:52 AM, Jarrad Hope <m...@jarradhope.com> wrote:
> apologies for double email,
>
> I was looking into inference and it looks like theres some context
> required for inference?
> specifically function argument types?
The context is also used for optimization, because it has a cache
of inferred objects. next(node.infer(context=InferenceContext()) should be
enough for start.
>
> I tried next(node.infer()) and iterating through the infer generator
> but all i can seem to muster is a "YES/_Yes" object
> I looked in source and unit tests but it's not clear what YES means
YES node represents something that wasn't inferrable at a given time.
To explain better through an example. Let's say we have a module,
called missing, which doesn't exist at all anywhere.
Trying to infer the x from this code will lead to an YES, meaning that
astroid knows something is there, but can't know what.
from missing import Missing
x = Missing()
>
> I see test_infer_arguments, which seems to test inference of function
> arguments based on their calls,
> it it possible to infer arguments based on their interaction with locals?
>
> for example
> def double(x):
> return(x * 2)
What you need here is a call context (see astroid.bases.CallContext).
All by itself, that x is nothing more than a YES node, but if you provide
a call context, than you can reach something more useful. Here's an example
of how the inference is actually getting to a result:
from astroid.builder import AstroidBuilder
b = AstroidBuilder()
node = b.string_build('''
def test(x):
return x*2
f = test(3)
''')
f = node['f']
result = next(f.infer())
print(result) # Const
print(result.value) # it finds out that's actually 6
>
> I'd like to be able to walk the double function arguments and infer x
> is an int based on it's interaction with Const(int)
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