python-peps/pep-0554.rst

PEP: 554
Title: Multiple Interpreters in the Stdlib
Author: Eric Snow <ericsnowcurrently@gmail.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 2017-09-05
Python-Version: 3.7
Post-History:


Abstract
========

This proposal introduces the stdlib ``interpreters`` module.  It exposes
the basic functionality of subinterpreters that already exists in the
C-API.  Each subinterpreter runs with its own state (see
``Interpreter Isolation`` below).  The module will be "provisional", as
described by PEP 411.


Rationale
=========

Running code in multiple interpreters provides a useful level of
isolation within the same process.  This can be leveraged in number
of ways.  Furthermore, subinterpreters provide a well-defined framework
in which such isolation may extended.

CPython has supported subinterpreters, with increasing levels of
support, since version 1.5.  While the feature has the potential
to be a powerful tool, subinterpreters have suffered from neglect
because they are not available directly from Python.  Exposing the
existing functionality in the stdlib will help reverse the situation.

This proposal is focused on enabling the fundamental capability of
multiple isolated interpreters in the same Python process.  This is a
new area for Python so there is relative uncertainly about the best
tools to provide as companions to subinterpreters.  Thus we minimize
the functionality we add in the proposal as much as possible.

Concerns
--------

* "subinterpreters are not worth the trouble"

Some have argued that subinterpreters do not add sufficient benefit
to justify making them an official part of Python.  Adding features
to the language (or stdlib) has a cost in increasing the size of
the language.  So it must pay for itself.  In this case, subinterpreters
provide a novel concurrency model focused on isolated threads of
execution.  Furthermore, they present an opportunity for changes in
CPython that will allow simulateous use of multiple CPU cores (currently
prevented by the GIL).

Alternatives to subinterpreters include threading, async, and
multiprocessing.  Threading is limited by the GIL and async isn't
the right solution for every problem (nor for every person).
Multiprocessing is likewise valuable in some but not all situations.
Direct IPC (rather than via the multiprocessing module) provides
similar benefits but with the same caveat.

Notably, subinterpreters are not intended as a replacement for any of
the above.  Certainly they overlap in some areas, but the benefits of
subinterpreters include isolation and (potentially) performance.  In
particular, subinterpreters provide a direct route to an alternate
concurrency model (e.g. CSP) which has found success elsewhere and
will appeal to some Python users.  That is the core value that the
``interpreters`` module will provide.

* "stdlib support for subinterpreters adds extra burden
  on C extension authors"

In the ``Interpreter Isolation`` section below we identify ways in
which isolation in CPython's subinterpreters is incomplete.  Most
notable is extension modules that use C globals to store internal
state.  PEP 3121 and PEP 489 provide a solution for most of the
problem, but one still remains. [petr-c-ext]_  Until that is resolved,
C extension authors will face extra difficulty to support
subinterpreters.

Consequently, projects that publish extension modules may face an
increased maintenance burden as their users start using subinterpreters,
where their modules may break.  This situation is limited to modules
that use C globals (or use libraries that use C globals) to store
internal state.

Ultimately this comes down to a question of how often it will be a
problem in practice: how many projects would be affected, how often
their users will be affected, what the additional maintenance burden
will be for projects, and what the overall benefit of subinterpreters
is to offset those costs.  The position of this PEP is that the actual
extra maintenance burden will be small and well below the threshold at
which subinterpreters are worth it.


Proposal
========

The ``interpreters`` module will be added to the stdlib.  It will
provide a high-level interface to subinterpreters and wrap the low-level
``_interpreters`` module.  The proposed API is inspired by the
``threading`` module.

The module provides the following functions:

``list()``::

   Return a list of all existing interpreters.

``get_current()``::

   Return the currently running interpreter.

``get_main()``::

   Return the main interpreter.

``create()``::

   Initialize a new Python interpreter and return it.  The
   interpreter will be created in the current thread and will remain
   idle until something is run in it.

The module also provides the following classes:

``Interpreter(id)``::

   id:

      The interpreter's ID (read-only).

   is_running():

      Return whether or not the interpreter is currently executing code.

   destroy():

      Finalize and destroy the interpreter.  If called on a running
      interpreter then raise RuntimeError in the interpreter that
      called ``destroy()``.

   run(code):

      Run the provided Python code in the interpreter, in the current
      OS thread.  If the interpreter is already running then raise
      RuntimeError in the interpreter that called ``run()``.

      The current interpreter (which called ``run()``) will block until
      the subinterpreter finishes running the requested code.  Any
      uncaught exception in that code will bubble up to the current
      interpreter.

      Supported code: source text.

   get_fifo(name):

      Return the FIFO object with the given name that is associated
      with this interpreter.  If no such FIFO exists then raise
      KeyError.  The FIFO will be either a "FIFOReader" or a
      "FIFOWriter", depending on which "add_*_fifo()" was called.

   list_fifos():

      Return a list of all fifos associated with the interpreter.

   add_recv_fifo(name=None):

      Create a new FIFO, associate the two ends with the involved
      interpreters, and return the side associated with the interpreter
      in which "add_recv_fifo()" was called.  A FIFOReader gets tied to
      this interpreter.  A FIFOWriter gets tied to the interpreter that
      called "add_recv_fifo()".

      The FIFO's name is set to the provided value.  If no name is
      provided then a dynamically generated one is used.  If a FIFO
      with the given name is already associated with this interpreter
      (or with the one in which "add_recv_fifo()" was called) then raise
      KeyError.

   add_send_fifo(name=None):

      Create a new FIFO, associate the two ends with the involved
      interpreters, and return the side associated with the interpreter
      in which "add_recv_fifo()" was called.  A FIFOWriter gets tied to
      this interpreter.  A FIFOReader gets tied to the interpreter that
      called "add_recv_fifo()".

      The FIFO's name is set to the provided value.  If no name is
      provided then a dynamically generated one is used.  If a FIFO
      with the given name is already associated with this interpreter
      (or with the one in which "add_send_fifo()" was called) then raise
      KeyError.

   remove_fifo(name):

      Drop the association between the named FIFO and this interpreter.
      If the named FIFO is not found then raise KeyError.


``FIFOReader(name)``::

   The receiving end of a FIFO.  An interpreter may use this to receive
   objects from another interpreter.  At first only bytes and None will
   be supported.

   name:

      The FIFO's name.

   __next__():

      Return the next bytes object from the pipe.  If none have been
      pushed on then block.

   pop(*, block=True):

      Return the next bytes object from the pipe.  If none have been
      pushed on and "block" is True (the default) then block.
      Otherwise return None.


``FIFOWriter(name)``::

   The sending end of a FIFO.  An interpreter may use this to send
   objects to another interpreter.  At first only bytes and None will
   be supported.

   name:

      The FIFO's name.

   push(object, *, block=True):

       Add the object to the FIFO.  If "block" is true then block
       until the object is popped off.  If the FIFO does not support
       the object's type then TypeError is raised.

About FIFOs
-----------

Subinterpreters are inherently isolated (with caveats explained below),
in contrast to threads.  This enables a different concurrency model than
currently exists in Python.  CSP (Communicating Sequential Processes),
upon which Go's concurrency is based, is one example of this model.

A key component of this approach to concurrency is message passing.  So
providing a message/object passing mechanism alongside ``Interpreter``
is a fundamental requirement.  This proposal includes a basic mechanism
upon which more complex machinery may be built.  That basic mechanism
draws inspiration from pipes, queues, and CSP's channels.

The key challenge here is that sharing objects between interpreters
faces complexity due in part to CPython's current memory model.
Furthermore, in this class of concurrency, the ideal is that objects
only exist in one interpreter at a time.  However, this is not practical
for Python so we initially constrain supported objects to ``bytes`` and
``None``.  There are a number of strategies we may pursue in the future
to expand supported objects and object sharing strategies.

Note that the complexity of object sharing increases as subinterpreters
become more isolated, e.g. after GIL removal.  So the mechanism for
message passing needs to be carefully considered.  Keeping the API
minimal and initially restricting the supported types helps us avoid
further exposing any underlying complexity to Python users.


Deferred Functionality
======================

In the interest of keeping this proposal minimal, the following
functionality has been left out for future consideration.  Note that
this is not a judgement against any of said capability, but rather a
deferment.  That said, each is arguably valid.

Interpreter.call()
------------------

It would be convenient to run existing functions in subinterpreters
directly.  ``Interpreter.run()`` could be adjusted to support this or
a ``call()`` method could be added::

   Interpreter.call(f, *args, **kwargs)

This suffers from the same problem as sharing objects between
interpreters via queues.  The minimal solution (running a source string)
is sufficient for us to get the feature out where it can be explored.

timeout arg to pop() and push()
-------------------------------

Typically functions that have a ``block`` argument also have a
``timeout`` argument.  We can add it later if needed.


Interpreter Isolation
=====================

CPython's interpreters are intended to be strictly isolated from each
other.  Each interpreter has its own copy of all modules, classes,
functions, and variables.  The same applies to state in C, including in
extension modules.  The CPython C-API docs explain more. [c-api]_

However, there are ways in which interpreters share some state.  First
of all, some process-global state remains shared, like file descriptors.
There are no plans to change this.

Second, some isolation is faulty due to bugs or implementations that did
not take subinterpreters into account.  This includes things like
at-exit handlers and extension modules that rely on C globals.  In these
cases bugs should be opened (some are already).

Finally, some potential isolation is missing due to the current design
of CPython.  This includes the GIL and memory management.  Improvements
are currently going on to address gaps in this area.


Provisional Status
==================

The new ``interpreters`` module will be added with "provisional" status
(see PEP 411).  This allows Python users to experiment with the feature
and provide feedback while still allowing us to adjust to that feedback.
The module will be provisional in Python 3.7 and we will make a decision
before the 3.8 release whether to keep it provisional, graduate it, or
remove it.


References
==========

.. [c-api]
   https://docs.python.org/3/c-api/init.html#bugs-and-caveats

.. [petr-c-ext]
   https://mail.python.org/pipermail/import-sig/2016-June/001062.html
   https://mail.python.org/pipermail/python-ideas/2016-April/039748.html


Copyright
=========

This document has been placed in the public domain.



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