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The Lazy Python Reloader

Project description

This is one way to control what happens when you reload. Modules are reloaded in the same order they would be if they were being loaded for the first time, and for the same reasons, thus eliminating some of the unpredictability associated with circular module references.

Usage

from lazy_reload import lazy_reload
import foo.bar.baz
lazy_reload(foo)
from foo.bar import baz # <= foo, bar, and baz reloaded here

Motivation

The problems with reloading modules in Python are legion and well-known. During the course of ordinary execution, references to objects in the modules and to the modules themselves end up distributed around the object graph in ways that can be hard to manage and hard to predict. As a result, it’s very common to have old code hanging around long after the reload, possibly referencing things you expect to have reloaded. This is not necessarily Python’s fault: it’s just a hard problem to solve well.

As a result, most applications that need to update their code dynamically find a way to start up a new python process for that purpose. I strongly recommend you do that if it’s an option for you; you’ll save yourself lots of debugging headaches in the long run. For the rest of us, there’s lazy_reload.

What Python’s __builtin__.reload Does

The reload() function supplied by Python is very simple-minded: it causes the module’s source file to be interpreted in the context of the existing module object. Any attributes of the module that aren’t overwritten by that interpretation remain in place. So for example, a module can detect that it’s being reloaded as follows:

if 'already_loaded' in globals():
    print 'I am being reloaded'
already_loaded = True

Also, Python makes no attempt to update references to that module elsewhere in your program. Because the identity of the module object doesn’t change, direct module references will still work. However, any existing references to functions or classes defined within that module will still point to the old definitions. Objects created before the reload still refer to outdated classes via their __class__ attribute, and any local names that have been imported into other modules still reference their old definitions.

What lazy_reload Does

lazy_reload(foo) (or lazy_reload('foo')) removes foo and all of its submodules from sys.modules, and arranges that the next time any of them are imported, they will be reloaded.

What lazy_reload Doesn’t Do

  • It doesn’t eliminate references to the reloaded module from other modules. In particular, having loaded this:

    # bar.py
    import foo
    def f():
        return foo.x

    the reference to foo is already present in bar, so after lazy_unload(foo), a call to bar.f() will not cause foo to be reloaded even though it is used there. Thus, you are safest using lazy_unload on top-level modules that are not known to other parts of your program by name.

  • It doesn’t immediately cause anything to be reloaded. Remember that the reload operation is lazy, and only happens when the module is being imported.

  • It also doesn’t cause anything to be “unloaded,” nor does it do anything explicit to reclaim memory. If the program is holding references to functions and classes, don’t expect them to be garbage-collected. (Watch out for backtraces; information from the last exception raised can keep things alive longer than you’d like).

  • It doesn’t fold your laundry or wash your cats. If you don’t enjoy these activities yourself, consider the many affordable alternatives to pets and clothes.

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