How to go about. On read/write locks

Diez B. Roggisch deets at
Mon Apr 6 23:27:13 CEST 2009

> Python's approach with the GIL is both reasonable and disappointing.
> Reasonable because I understand how it can make things easier for its
> internals. Disappointing because it means that standard python cannot
> take advantage of the parallelism that can more and more often be
> afforded by today's computers. I.e. I found only recently, almost by
> chance, that my wife's laptop has not one but two processors, even
> though it isn't a particularly high-end computer. I now understand
> that OS-level threading does use them both, but I understand that the
> GIL effectively prevents parallel operations. (Am I understanding
> correctly?)

Not entirely. Yes, if your application is CPU-bound. No if it's 
IO-bound. And a lot of people think that threads are actually the wrong 
approach for concurrency anyway, so with python2.6 there comes the 
multiprocessing-module that lets you use the full capacity of your CPUs.

> I do not completely understand your statement in the context of my
> original example though, the shared dictionary. As the GIL is released
> every X bytecode operations surely it can happen that as the
> dictionary is iterated through, i.e. in a for/in loop, a different
> thread might change it, with potentially catastrophic consequences.
> The GIL wouldn't be able to prevent this, wouldn't it?

You didn't give a concrete usage scenario for your shared dict - but I 
assumed that by reading and writing you meant

mydict[key] = value

value = mydict[key]

which are both atomic through the GIL.

More complex operations - such as iteration - might need more coarse 
grained locking.


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