Question

Background:
Migrating from R to Python with numpy/scipy. Trying to make a little module of useful functions. In particular, I’m trying to create a recursive element-type checker.

Question:
Is it possible to get a list of the current valid types in the Python environment a function is being called in?

For example, isinstance(1,int) will return True, isinstance(1,str) will return False, but isinstance(1,asdf) will throw a NameError: name 'asdf' is not defined i.e. int and str are defined, but asdf is not. How can I get the list of types that are defined, or names present in the current Python environment, and filter them by types?

Answer 1

In Python, types are themselves ordinary objects. That is, for example,

type('hello') == str
type(5) == int
type(int) == type
type(type) == type

are all True.

So to do this, look for all variables in scope that point to objects of type type.

To get all objects in scope, look at both dir() (which excludes built-in names like int) and dir(__builtins__) (the built-in names) locals() (variables defined in the current function), globals() (variables defined outside of functions in the current module), and vars(__builtins__) (the built-in names). These are all dictionaries from name => object, so combine them all and get the objects:

objs = dict(vars(__builtins__), **dict(globals(), **locals())).values()

and filter only types:

types_in_scope = [o for o in objs if isinstance(o, type)]

Note that these are just the variables in scope that point to types. It’s quite possible to have a reference to an object whose type is not assigned to any variable in scope. For example:

def foo():
    class Foo:
        pass
    return Foo()
x = foo()