[Python-Dev] PEP 567 v3 (original) (raw)

Yury Selivanov yselivanov.ml at gmail.com
Tue Jan 16 17:44:14 EST 2018


Hi,

This is a third version of PEP 567.

Changes from v2:

  1. PyThreadState now references Context objects directly (instead of referencing _ContextData). This fixes out of sync Context.get() and ContextVar.get().

  2. Added a new Context.copy() method.

  3. Renamed Token.old_val property to Token.old_value

  4. ContextVar.reset(token) now raises a ValueError if the token was created in a different Context.

  5. All areas of the PEP were updated to be more precise. Context is no longer defined as a read-only or an immutable mapping; ContextVar.get() behaviour is fully defined; the immutability is only mentioned in the Implementation section to avoid confusion; etc.

  6. Added a new Examples section.

The reference implementation has been updated to include all these changes.

The only open question I personally have is whether ContextVar.reset() should be idempotent or not. Maybe we should be strict and raise an error if a user tries to reset a variable more than once with the same token object?

Other than that, I'm pretty happy with this version. Big thanks to everybody helping with the PEP!

PEP: 567 Title: Context Variables Version: RevisionRevisionRevision Last-Modified: DateDateDate Author: Yury Selivanov <yury at magic.io> Status: Draft Type: Standards Track Content-Type: text/x-rst Created: 12-Dec-2017 Python-Version: 3.7 Post-History: 12-Dec-2017, 28-Dec-2017, 16-Jan-2018

Abstract

This PEP proposes a new contextvars module and a set of new CPython C APIs to support context variables. This concept is similar to thread-local storage (TLS), but, unlike TLS, it also allows correctly keeping track of values per asynchronous task, e.g. asyncio.Task.

This proposal is a simplified version of :pep:550. The key difference is that this PEP is concerned only with solving the case for asynchronous tasks, not for generators. There are no proposed modifications to any built-in types or to the interpreter.

This proposal is not strictly related to Python Context Managers. Although it does provide a mechanism that can be used by Context Managers to store their state.

Rationale

Thread-local variables are insufficient for asynchronous tasks that execute concurrently in the same OS thread. Any context manager that saves and restores a context value using threading.local() will have its context values bleed to other code unexpectedly when used in async/await code.

A few examples where having a working context local storage for asynchronous code is desirable:

Introduction

The PEP proposes a new mechanism for managing context variables. The key classes involved in this mechanism are contextvars.Context and contextvars.ContextVar. The PEP also proposes some policies for using the mechanism around asynchronous tasks.

The proposed mechanism for accessing context variables uses the ContextVar class. A module (such as decimal) that wishes to use the new mechanism should:

The notion of "current value" deserves special consideration: different asynchronous tasks that exist and execute concurrently may have different values for the same key. This idea is well-known from thread-local storage but in this case the locality of the value is not necessarily bound to a thread. Instead, there is the notion of the "current Context" which is stored in thread-local storage. Manipulation of the current context is the responsibility of the task framework, e.g. asyncio.

A Context is a mapping of ContextVar objects to their values. The Context itself exposes the abc.Mapping interface (not abc.MutableMapping!), so it cannot be modified directly. To set a new value for a context variable in a Context object, the user needs to:

The ContextVar.get() method looks for the variable in the current Context object using self as a key.

It is not possible to get a direct reference to the current Context object, but it is possible to obtain a shallow copy of it using the contextvars.copy_context() function. This ensures that the caller of Context.run() is the sole owner of its Context object.

Specification

A new standard library module contextvars is added with the following APIs:

  1. copy_context() -> Context function is used to get a copy of the current Context object for the current OS thread.

  2. ContextVar class to declare and access context variables.

  3. Context class encapsulates context state. Every OS thread stores a reference to its current Context instance. It is not possible to control that reference directly. Instead, the Context.run(callable, *args, **kwargs) method is used to run Python code in another context.

contextvars.ContextVar

The ContextVar class has the following constructor signature: ContextVar(name, *, default=_NO_DEFAULT). The name parameter is used for introspection and debug purposes, and is exposed as a read-only ContextVar.name attribute. The default parameter is optional. Example::

# Declare a context variable 'var' with the default value 42.
var = ContextVar('var', default=42)

(The _NO_DEFAULT is an internal sentinel object used to detect if the default value was provided.)

ContextVar.get(default=_NO_DEFAULT) returns a value for the context variable for the current Context::

# Get the value of `var`.
var.get()

If there is no value for the variable in the current context, ContextVar.get() will:

ContextVar.set(value) -> Token is used to set a new value for the context variable in the current Context::

# Set the variable 'var' to 1 in the current context.
var.set(1)

ContextVar.reset(token) is used to reset the variable in the current context to the value it had before the set() operation that created the token (or to remove the variable if it was not set)::

assert var.get(None) is None

token = var.set(1)
try:
    ...
finally:
    var.reset(token)

assert var.get(None) is None

ContextVar.reset() method is idempotent and can be called multiple times on the same Token object: second and later calls will be no-ops. The method raises a ValueError if:

contextvars.Token

contextvars.Token is an opaque object that should be used to restore the ContextVar to its previous value, or to remove it from the context if the variable was not set before. It can be created only by calling ContextVar.set().

For debug and introspection purposes it has:

contextvars.Context

Context object is a mapping of context variables to values.

Context() creates an empty context. To get a copy of the current Context for the current OS thread, use the contextvars.copy_context() method::

ctx = contextvars.copy_context()

To run Python code in some Context, use Context.run() method::

ctx.run(function)

Any changes to any context variables that function causes will be contained in the ctx context::

var = ContextVar('var')
var.set('spam')

def function():
    assert var.get() == 'spam'
    assert ctx[var] == 'spam'

    var.set('ham')
    assert var.get() == 'ham'
    assert ctx[var] == 'ham'

ctx = copy_context()

# Any changes that 'function' makes to 'var' will stay
# isolated in the 'ctx'.
ctx.run(function)

assert var.get() == 'spam'
assert ctx[var] == 'ham'

Context.run() raises a RuntimeError when called on the same context object from more than one OS thread, or when called recursively.

Context.copy() returns a shallow copy of the context object.

Context objects implement the collections.abc.Mapping ABC. This can be used to introspect contexts::

ctx = contextvars.copy_context()

# Print all context variables and their values in 'ctx':
print(ctx.items())

# Print the value of 'some_variable' in context 'ctx':
print(ctx[some_variable])

Note that all Mapping methods, including Context.__getitem__ and Context.get, ignore default values for context variables (i.e. ContextVar.default). This means that for a variable var that was created with a default value and was not set in the context:

asyncio

asyncio uses Loop.call_soon(), Loop.call_later(), and Loop.call_at() to schedule the asynchronous execution of a function. asyncio.Task uses call_soon() to run the wrapped coroutine.

We modify Loop.call_{at,later,soon} and Future.add_done_callback() to accept the new optional context keyword-only argument, which defaults to the current context::

def call_soon(self, callback, *args, context=None):
    if context is None:
        context = contextvars.copy_context()

    # ... some time later
    context.run(callback, *args)

Tasks in asyncio need to maintain their own context that they inherit from the point they were created at. asyncio.Task is modified as follows::

class Task:
    def __init__(self, coro):
        ...
        # Get the current context snapshot.
        self._context = contextvars.copy_context()
        self._loop.call_soon(self._step, context=self._context)

    def _step(self, exc=None):
        ...
        # Every advance of the wrapped coroutine is done in
        # the task's context.
        self._loop.call_soon(self._step, context=self._context)
        ...

Implementation

This section explains high-level implementation details in pseudo-code. Some optimizations are omitted to keep this section short and clear.

The Context mapping is implemented using an immutable dictionary. This allows for a O(1) implementation of the copy_context() function. The reference implementation implements the immutable dictionary using Hash Array Mapped Tries (HAMT); see :pep:550 for analysis of HAMT performance [1]_.

For the purposes of this section, we implement an immutable dictionary using a copy-on-write approach and built-in dict type::

class _ContextData:

    def __init__(self):
        self._mapping = dict()

    def get(self, key):
        return self._mapping[key]

    def set(self, key, value):
        copy = _ContextData()
        copy._mapping = self._mapping.copy()
        copy._mapping[key] = value
        return copy

    def delete(self, key):
        copy = _ContextData()
        copy._mapping = self._mapping.copy()
        del copy._mapping[key]
        return copy

Every OS thread has a reference to the current Context object::

class PyThreadState:
    context: Context

contextvars.Context is a wrapper around _ContextData::

class Context(collections.abc.Mapping):

    _data: _ContextData
    _prev_context: Optional[Context]

    def __init__(self):
        self._data = _ContextData()
        self._prev_context = None

    def run(self, callable, *args, **kwargs):
        if self._prev_context is not None:
            raise RuntimeError(
                f'cannot enter context: {self} is already entered')

        ts: PyThreadState = PyThreadState_Get()
        if ts.context is None:
            ts.context = Context()

        self._prev_context = ts.context
        try:
            ts.context = self
            return callable(*args, **kwargs)
        finally:
            ts.context = self._prev_context
            self._prev_context = None

    def copy(self):
        new = Context()
        new._data = self._data
        return new

    # Mapping API methods are implemented by delegating
    # `get()` and other Mapping methods to `self._data`.

contextvars.copy_context() is implemented as follows::

def copy_context():
    ts: PyThreadState = PyThreadState_Get()

    if ts.context is None:
        ts.context = Context()

    return ts.context.copy()

contextvars.ContextVar interacts with PyThreadState.context directly::

class ContextVar:

    def __init__(self, name, *, default=_NO_DEFAULT):
        self._name = name
        self._default = default

    @property
    def name(self):
        return self._name

    def get(self, default=_NO_DEFAULT):
        ts: PyThreadState = PyThreadState_Get()
        if ts.context is not None:
            try:
                return ts.context[self]
            except KeyError:
                pass

        if default is not _NO_DEFAULT:
            return default

        if self._default is not _NO_DEFAULT:
            return self._default

        raise LookupError

    def set(self, value):
        ts: PyThreadState = PyThreadState_Get()
        if ts.context is None:
            ts.context = Context()

        data: _ContextData = ts.context._data
        try:
            old_value = data.get(self)
        except KeyError:
            old_value = Token.MISSING

        updated_data = data.set(self, value)
        ts.context._data = updated_data
        return Token(ts.context, self, old_value)

    def reset(self, token):
        if token._var is not self:
            raise ValueError(
                "Token was created by a different ContextVar")

        ts: PyThreadState = PyThreadState_Get()
        if token._ctx is not ts.context:
            raise ValueError(
                "Token was created in a different Context")

        if token._used:
            return

        if token._old_value is Token.MISSING:
            ts.context._data = data.delete(token._var)
        else:
            ts.context._data = data.set(token._var,
                                        token._old_value)

        token._used = True

Note that the in the reference implementation, ContextVar.get() has an internal cache for the most recent value, which allows to bypass a hash lookup. This is similar to the optimization the decimal module implements to retrieve its context from PyThreadState_GetDict(). See :pep:550 which explains the implementation of the cache in great detail.

The Token class is implemented as follows::

class Token:

    MISSING = object()

    def __init__(self, ctx, var, old_value):
        self._ctx = ctx
        self._var = var
        self._old_value = old_value
        self._used = False

    @property
    def var(self):
        return self._var

    @property
    def old_value(self):
        return self._old_value

Summary of the New APIs

Python API

  1. A new contextvars module with ContextVar, Context, and Token classes, and a copy_context() function.

  2. asyncio.Loop.call_at(), asyncio.Loop.call_later(), asyncio.Loop.call_soon(), and asyncio.Future.add_done_callback() run callback functions in the context they were called in. A new context keyword-only parameter can be used to specify a custom context.

  3. asyncio.Task is modified internally to maintain its own context.

C API

  1. PyContextVar * PyContextVar_New(char *name, PyObject *default): create a ContextVar object. The default argument can be NULL, which means that the variable has no default value.

  2. int PyContextVar_Get(PyContextVar *, PyObject *default_value, PyObject **value): return -1 if an error occurs during the lookup, 0 otherwise. If a value for the context variable is found, it will be set to the value pointer. Otherwise, value will be set to default_value when it is not NULL. If default_value is NULL, value will be set to the default value of the variable, which can be NULL too. value is always a new reference.

  3. PyContextToken * PyContextVar_Set(PyContextVar *, PyObject *): set the value of the variable in the current context.

  4. PyContextVar_Reset(PyContextVar *, PyContextToken *): reset the value of the context variable.

  5. PyContext * PyContext_New(): create a new empty context.

  6. PyContext * PyContext_Copy(): get a copy of the current context.

  7. int PyContext_Enter(PyContext *) and int PyContext_Exit(PyContext *) allow to set and restore the context for the current OS thread. It is required to always restore the previous context::

    PyContext *old_ctx = PyContext_Copy(); if (old_ctx == NULL) goto error;

    if (PyContext_Enter(new_ctx)) goto error;

    // run some code

    if (PyContext_Exit(old_ctx)) goto error;

Design Considerations

Why contextvars.Token and not ContextVar.unset()?

The Token API allows to get around having a ContextVar.unset() method, which is incompatible with chained contexts design of :pep:550. Future compatibility with :pep:550 is desired (at least for Python 3.7) in case there is demand to support context variables in generators and asynchronous generators.

The Token API also offers better usability: the user does not have to special-case absence of a value. Compare::

token = cv.get()
try:
    cv.set(blah)
    # code
finally:
    cv.reset(token)

with::

_deleted = object()
old = cv.get(default=_deleted)
try:
    cv.set(blah)
    # code
finally:
    if old is _deleted:
        cv.unset()
    else:
        cv.set(old)

Rejected Ideas

Replication of threading.local() interface

Please refer to :pep:550 where this topic is covered in detail: [2]_.

Backwards Compatibility

This proposal preserves 100% backwards compatibility.

Libraries that use threading.local() to store context-related values, currently work correctly only for synchronous code. Switching them to use the proposed API will keep their behavior for synchronous code unmodified, but will automatically enable support for asynchronous code.

Examples

Converting code that uses threading.local()

A typical code that uses threading.local() usually looks like the following snippet::

class mylocal(threading.local):
    # Subclass threading.local to specify a default value.
    value = 'spam'

mylocal = mylocal()

# To set a new value:
mylocal.value = 'new value'

# To read the current value:
mylocal.value

Such code can be converted to use the contextvars module::

mylocal = contextvars.ContextVar('mylocal', 'spam')

# To set a new value:
mylocal.set('new value')

# To read the current value:
mylocal.get()

Offloading execution to other threads

It is possible to run code in a separate OS thread using a copy of the current thread context::

executor = ThreadPoolExecutor()
current_context = contextvars.copy_context()

executor.submit(
    lambda: current_context.run(some_function))

Reference Implementation

The reference implementation can be found here: [3]_.

References

.. [1] https://www.python.org/dev/peps/pep-0550/#appendix-hamt-performance-analysis

.. [2] https://www.python.org/dev/peps/pep-0550/#replication-of-threading-local-interface

.. [3] https://github.com/python/cpython/pull/5027

Copyright

This document has been placed in the public domain.

.. Local Variables: mode: indented-text indent-tabs-mode: nil sentence-end-double-space: t fill-column: 70 coding: utf-8 End:



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