[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Question About When Objects Are Destroyed (continued)

On Sun, Aug 6, 2017 at 7:32 AM, Tim Daneliuk <info at tundraware.com> wrote:
> On 08/05/2017 03:21 PM, Chris Angelico wrote:
>> After a 'with' block,
>> the object *still exists*, but it has been "exited" in some way
>> (usually by closing/releasing an underlying resource).
> The containing object exists, but the things that the closing
> logic explicitly released do not.  In some sense, a context
> acts like a deconstructor, just not on the object it's associated
> with.
>> If there's a resource you need to clean up, you clean that up
>> explicitly,
> Such "resources" *are* objects themselves notionally.  You are exactly
> killing those objects to free the underlying resources they consume.

Utterly irrelevant. The original post was about the string in memory.
An "open file" is no more an object than the part of a floating point
number after the decimal is.

>> so the object's lifetime shouldn't matter to you.
> I disagree with this most strongly.  That's only true when the machine
> resources being consumed by your Python object are small in size.  But
> when you're dynamically cranking out millions of objects of relatively
> short lifetime, you can easily bump into the real world limits of
> practical machinery.  "Wait until the reference count sweep gets rid of
> it" only works when you have plenty of room to squander.
> Also, waiting for the reference count/gc to do its thing is
> nondeterministic in time.  It's going to happen sooner or later, but not
> at the same or a predictable interval.  If you want to write large,
> performant code, you don't want this kind of variability.  While I
> realize that we're not typically writing embedded realtime drivers in
> Python, the principle remains - where possible make things as
> predictable and repeatable as you can.
> For reasons I am not free discuss here, I can say with some assurance
> that there are real world applications where managing Python object
> lifetimes is very much indicated.

Very VERY few. How often do you actually care about the lifetime of a
specific Python object, and not (say) about the return of a block of
memory to the OS? Memory in CPython is allocated in pages, and those
pages are then suballocated into objects (or other uses). Sometimes
you care about that block going back to the OS; other times, all you
care about is that a subsequent allocation won't require more memory
(which can be handled with free lists). But most of the time, you
don't need to think about either, because the language *does the right
thing*. The nondeterminism of the GC is irrelevant to most Python
programs; in CPython, that GC sweep applies only to reference *cycles*
(and to weak references, I think??), so unless you frequently create
those, you shouldn't have to care.

I've written plenty of large programs in high level languages. Some of
them in Python, some in Pike (which has the same refcount semantics),
and some in REXX (which has very different technical semantics but
comes to the same thing). I've had those programs running for months
on end; in more than one instance, I've had a program running for over
a year (over two years, even) without restarting the process or
anything. Aside from taking care not to create cyclic references, I
have not needed to care about when the garbage collector runs, with
the sole exception of an instance where I built my own system on top
of the base GC (using weak references and an autoloader to emulate a
lookup table larger than memory). So yes, I maintain that most of the
time, object lifetimes *should not matter* to a Python programmer.
Python is not C, and you shouldn't treat it as C.