Let's have a simple script test.py:
def f():
	return x
x = 2
print(f())

Now if we try to run it via runpy.run_path, we get the following:
>>> import runpy
>>> g = runpy.run_path("test.py")
2
>>> g["f"]() is None
True
>>> g["x"] is 2
True
>>> g["f"].__globals__["x"] is None
True

Is the behaviour of f.__globals__ after return from run_path intended and why?

When modules are garbage collected the associated globals dict is purged -- see #18214.  This means that all values (except __builtins__) are replaced by None.

To work around this run_path() apparently returns a *copy* of the globals dict which was created before purging.

As Richard said, the __globals__ attributes of the functions are pointing at the real module dictionary, which may have been cleared when the temporary module was destroyed.

However, I just checked the docs and they don't actually mention the fact that run_path and run_module currently return a copy of the globals - they say they "return the resulting module globals dictionary."

Since I would prefer it if the functions actually worked as advertised, I suggest we document the namespace copying as a CPython implementation detail, rather than as a guaranteed feature. That way we can eliminate these copy operations once the module namespace purging has been eliminated.

Some related references:
   Don't purge module dicts before shutdown: issue 18214
   Don't purge module dicts at all: issue 812369
   More robust finalisation semantics: PEP 442
   
We should also tidy up the headings in the data model reference (
http://docs.python.org/3/reference/datamodel.html#the-standard-type-hierarchy) so we can link directly to the section that mentions the CPython module clearing implementation detail this behaviour is designed to work around.

Nick, is this issue still needed?