On 23 Jun 2015 03:37, "Gregory P. Smith" <greg@krypto.org> wrote:
On Sun, Jun 21, 2015 at 4:56 AM Devin Jeanpierre <jeanpierreda@gmail.com>
On Sat, Jun 20, 2015 at 4:16 PM, Eric Snow <ericsnowcurrently@gmail.com>
wrote:
On Jun 20, 2015 4:55 PM, "Devin Jeanpierre" <jeanpierreda@gmail.com>
wrote:
It's worthwhile to consider fork as an alternative. IMO we'd get a lot out of making forking safer, easier, and more efficient. (e.g. respectively: adding an atfork registration mechanism; separating out the bits of multiprocessing that use pickle from those that d, I
still disagreeon't;
moving the refcount to a separate page, or allowing it to be frozen prior to a fork.)
So leverage a common base of code with the multiprocessing module?
What is this question in response to? I don't understand.
I would expect subinterpreters to use less memory. Furthermore creating them would be significantly faster. Passing objects between them would be much more efficient. And, yes, cross-platform.
Maybe I don't understand how subinterpreters work. AIUI, the whole point of independent subinterpreters is that they share no state. So if I have a web server, each independent serving thread has to do all of the initialization (import HTTP libraries, etc.), right? Compare with forking, where the initialization is all done and then you fork, and you are immediately ready to serve, using the data structures shared with all the other workers, which is only copied when it is written to.
Unfortunately CPython subinterpreters do share some state, though it is not visible to the running code in many cases. Thus the other mentions of "wouldn't it be nice if CPython didn't assume a single global state per
wrote: process" (100% agreed, but tangential to this discussion)...
https://docs.python.org/3/c-api/init.html#sub-interpreter-support
You are correct that some things that could make sense to share, such as
imported modules, would not be shared as they are in a forked environment.
This is an important oddity of subinterpreters: They have to re-import
everything other than extension modules. When you've got a big process with a ton of modules (like, say, 100s of protocol buffers...), that's going to be a non-starter (pun intended) for the use of threads+subinterpreters as a fast form of concurrency if they need to import most of those from each subinterpreter. startup latency and cpu usage += lots. (possibly uses more memory as well but given our existing refcount implementation forcing needless PyObject page writes during a read causing fork to copy-on-write... impossible to guess)
What this means for subinterpreters in this case is not much different
from starting up multiple worker processes: You need to start them up and wait for them to be ready to serve, then reuse them as long as feasible before recycling them to start up a new one. The startup cost is high. While I don't believe it's clear from the current text in the PEP (mostly because I only figured it out while hacking on the prototype implementation), PEP 432 should actually give us much better control over how subinterpreters are configured, as many more interpreter settings move out of global variables and into the interpreter state: https://www.python.org/dev/peps/pep-0432/ (the global variables will still exist, but primarily as an input to the initial configuration of the main interpreter) The current state of that work can be seen at https://bitbucket.org/ncoghlan/cpython_sandbox/compare/pep432_modular_bootst... While a lot of things are broken there, it's at least to the point where it can start running the regression test suite under the new 2-phase initialisation model. Cheers, Nick.