Thursday, December 22, 2011

Easily import a dynamically created module

Python modules are typically Python source files that are used like simple namespaces for variables. Take this simple module:

mod.py:

x = "Hi, I'm a module variable."

Provided mod.py is on the import path (which usually includes the current working directory), you can run Python and see:

>>> import mod
>>> print mod.x
"Hi, I'm a module variable."


Of course, this is Python and Python modules are objects of type 'module'. You can dynamically create an object of this type easily enough:

>>> from types import ModuleType
>>> mymodule = ModuleType('mymodule')
>>> mymodule.x = "Hi, I'm in a dynamically-created module."
>>> print mymodule.x
"Hi, I'm in a dynamically-created module."

Pretty much what you'd expect. ModuleType is the same thing you'd get back from import sys; type(sys). That's actually what the types module uses.

But, you can't import mymodule because it's not a real, source-based module on the import path. If you want other Pythonauts to be able to use standard import syntax to import your dynamic module, a little more trickery is involved.

dynmod.py:

import sys
from types import ModuleType

not_present = "Hi, I was masked by the dynamic module."

dm = ModuleType(__name__)
dm.x = 5

sys.modules[__name__] = dm


If you're doing this you probably already know, but __name__ is just a string containing the name of the current module, based on the filename ('dynmod'). Using __name__ just keeps things a bit more consistent.

Now, look what happens when you import dynmod:

>>> import dynmod
>>> dynmod.x
5
>>> dynmod.not_present
Traceback (most recent call last):
File "", line 1, in
AttributeError: 'module' object has no attribute 'not_present'
>>> dir(dynmod)
['__doc__', '__name__', 'x']


All the normal import syntax should work, including from dynmod import x, even though the module isn't strictly what's in the source file.

The dynamic behavior is only executed once, on initial import. When imported, Python modules create a name->module_object entry in the sys.modules dictionary. From then on, if the module name is found in sys.modules, the associated module object is used. That's how normal modules work, and that's how we want our dynamic module to work, too.

The key here is that the sys.modules entry seems to be created before the module code is run, allowing the module code to modify its own entry. Be careful with this, because Python's import system has some complex locking behavior that can make certain manipulations not work:

dynmod_broken.py:

# Breaks some import locks or something
import sys
from types import ModuleType

not_present = "masked"

sys.modules[__name__] = ModuleType(__name__)
sys.modules[__name__].x = 5

(In fact, according to my testing, this left every single variable in the namespace set to None. Pretty PDW, if you ask me.)

If that's not interesting enough for you, then stay tuned for the follow-up post on more advanced dynamic modules where we show you how to use modules' simple and familiar nature to do your darkest biddings.

(Note: if you're looking for the right way to simply mask certain variables, consider using __all__. Also, you could probably do more fancy things with Import Hooks, but this is tested to work on Python 2.7 and 3.1, so maybe keep it simple, if simple's all you need.)

13 comments:

  1. Cool you write, the information is very good and interesting, I'll give you a link to my site.
    Data Science Course in Bangalore

    ReplyDelete
  2. Easily, the article is actually the best topic on this registry related issue. I fit in with your conclusions and will eagerly look forward to your next updates. Just saying thanks will not just be sufficient, for the fantasti c lucidity in your writing. I will instantly grab your rss feed to stay informed of any updates.
    Data Science Training in Bangalore

    ReplyDelete
  3. It's good to visit your blog again, it's been months for me. Well, this article that I have been waiting for so long. I will need this post to complete my college homework, and it has the exact same topic with your article. Thanks, have a good game.
    Business Analytics Course

    ReplyDelete
  4. I read this post,very well explain about python.Keep sharing this information.

    Python Classes in Pune

    ReplyDelete
  5. I value the blog article. Thanks Again. Really Great.온라인경마

    ReplyDelete
  6. I'm always looking online for articles that can help me. I think you also made some good comments on the functions. Keep up the good work!

    Data Scientist Training and Placement Bangalore

    ReplyDelete
  7. Very efficiently written information. It will be beneficial to anybody who utilizes it, including me. Keep up the good work. For sure i will check out more posts. This site seems to get a good amount of visitors. Ielts

    ReplyDelete
  8. Thanks for getting the effort to write this amazing post. Visit Best Python training course in Delhi

    ReplyDelete
  9. My spouse and I stumbled over here by a different web address and thought I might check things out. I like what I see so i am just following you. Look forward to checking out your web page again. https://python.engineering/image-processing-without-opencv-python/

    ReplyDelete
  10. Great tips and very easy to understand. This will definitely be very useful for me when I get a chance to start my blog. data science course in mysore

    ReplyDelete
  11. This comment has been removed by the author.

    ReplyDelete
  12. Great post i must say and thanks for the information. Visit at https://www.uncodemy.com/course/python/

    ReplyDelete