The other answers evince a mild confusion as to how import
really works.
This statement:
import foo
is roughly equivalent to this statement:
foo = __import__('foo', globals(), locals(), [], -1)
That is, it creates a variable in the current scope with the same name as the requested module, and assigns it the result of calling __import__()
with that module name and a boatload of default arguments.
The __import__()
function handles conceptually converts a string ('foo'
) into a module object. Modules are cached in sys.modules
, and that's the first place __import__()
looks--if sys.modules has an entry for 'foo'
, that's what __import__('foo')
will return, whatever it is. It really doesn't care about the type. You can see this in action yourself; try running the following code:
import sys
sys.modules['boop'] = (1, 2, 3)
import boop
print boop
Leaving aside stylistic concerns for the moment, having an import statement inside a function works how you'd want. If the module has never been imported before, it gets imported and cached in sys.modules. It then assigns the module to the local variable with that name. It does not not not modify any module-level state. It does possibly modify some global state (adding a new entry to sys.modules).
That said, I almost never use import
inside a function. If importing the module creates a noticeable slowdown in your program—like it performs a long computation in its static initialization, or it's simply a massive module—and your program rarely actually needs the module for anything, it's perfectly fine to have the import only inside the functions in which it's used. (If this was distasteful, Guido would jump in his time machine and change Python to prevent us from doing it.) But as a rule, I and the general Python community put all our import statements at the top of the module in module scope.
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