mirror of
https://github.com/ARM-software/devlib.git
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fefdf29ed8
Add a memoize_method decorator that works for async methods. It will not leak memory since the memoization cache is held in the instance __dict__, and it does not rely on hacks to hash unhashable data.
438 lines
13 KiB
Python
438 lines
13 KiB
Python
# Copyright 2013-2018 ARM Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Async-related utilities
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"""
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import abc
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import asyncio
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import functools
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import itertools
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import contextlib
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import pathlib
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import os.path
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import inspect
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# Allow nesting asyncio loops, which is necessary for:
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# * Being able to call the blocking variant of a function from an async
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# function for backward compat
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# * Critically, run the blocking variant of a function in a Jupyter notebook
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# environment, since it also uses asyncio.
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#
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# Maybe there is still hope for future versions of Python though:
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# https://bugs.python.org/issue22239
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import nest_asyncio
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nest_asyncio.apply()
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def create_task(awaitable, name=None):
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if isinstance(awaitable, asyncio.Task):
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task = awaitable
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else:
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task = asyncio.create_task(awaitable)
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if name is None:
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name = getattr(awaitable, '__qualname__', None)
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task.name = name
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return task
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class AsyncManager:
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def __init__(self):
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self.task_tree = dict()
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self.resources = dict()
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def track_access(self, access):
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"""
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Register the given ``access`` to have been handled by the current
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async task.
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:param access: Access that were done.
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:type access: ConcurrentAccessBase
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This allows :func:`concurrently` to check that concurrent tasks did not
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step on each other's toes.
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"""
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try:
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task = asyncio.current_task()
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except RuntimeError:
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pass
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else:
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self.resources.setdefault(task, set()).add(access)
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async def concurrently(self, awaitables):
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"""
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Await concurrently for the given awaitables, and cancel them as soon as
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one raises an exception.
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"""
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awaitables = list(awaitables)
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# Avoid creating asyncio.Tasks when it's not necessary, as it will
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# disable a the blocking path optimization of Target._execute_async()
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# that uses blocking calls as long as there is only one asyncio.Task
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# running on the event loop.
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if len(awaitables) == 1:
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return [await awaitables[0]]
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tasks = list(map(create_task, awaitables))
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current_task = asyncio.current_task()
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task_tree = self.task_tree
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try:
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node = task_tree[current_task]
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except KeyError:
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is_root_task = True
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node = set()
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else:
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is_root_task = False
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task_tree[current_task] = node
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task_tree.update({
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child: set()
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for child in tasks
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})
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node.update(tasks)
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try:
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return await asyncio.gather(*tasks)
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except BaseException:
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for task in tasks:
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task.cancel()
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raise
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finally:
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def get_children(task):
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immediate_children = task_tree[task]
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return frozenset(
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itertools.chain(
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[task],
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immediate_children,
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itertools.chain.from_iterable(
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map(get_children, immediate_children)
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)
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)
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)
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# Get the resources created during the execution of each subtask
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# (directly or indirectly)
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resources = {
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task: frozenset(
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itertools.chain.from_iterable(
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self.resources.get(child, [])
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for child in get_children(task)
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)
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)
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for task in tasks
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}
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for (task1, resources1), (task2, resources2) in itertools.combinations(resources.items(), 2):
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for res1, res2 in itertools.product(resources1, resources2):
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if issubclass(res2.__class__, res1.__class__) and res1.overlap_with(res2):
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raise RuntimeError(
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'Overlapping resources manipulated in concurrent async tasks: {} (task {}) and {} (task {})'.format(res1, task1.name, res2, task2.name)
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)
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if is_root_task:
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self.resources.clear()
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task_tree.clear()
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async def map_concurrently(self, f, keys):
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"""
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Similar to :meth:`concurrently`,
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but maps the given function ``f`` on the given ``keys``.
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:return: A dictionary with ``keys`` as keys, and function result as
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values.
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"""
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keys = list(keys)
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return dict(zip(
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keys,
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await self.concurrently(map(f, keys))
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))
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def compose(*coros):
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"""
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Compose coroutines, feeding the output of each as the input of the next
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one.
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``await compose(f, g)(x)`` is equivalent to ``await f(await g(x))``
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.. note:: In Haskell, ``compose f g h`` would be equivalent to ``f <=< g <=< h``
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"""
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async def f(*args, **kwargs):
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empty_dict = {}
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for coro in reversed(coros):
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x = coro(*args, **kwargs)
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# Allow mixing corountines and regular functions
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if asyncio.isfuture(x):
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x = await x
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args = [x]
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kwargs = empty_dict
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return x
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return f
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class _AsyncPolymorphicFunction:
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"""
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A callable that allows exposing both a synchronous and asynchronous API.
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When called, the blocking synchronous operation is called. The ```asyn``
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attribute gives access to the asynchronous version of the function, and all
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the other attribute access will be redirected to the async function.
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"""
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def __init__(self, asyn, blocking):
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self.asyn = asyn
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self.blocking = blocking
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def __get__(self, *args, **kwargs):
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return self.__class__(
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asyn=self.asyn.__get__(*args, **kwargs),
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blocking=self.blocking.__get__(*args, **kwargs),
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)
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def __call__(self, *args, **kwargs):
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return self.blocking(*args, **kwargs)
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def __getattr__(self, attr):
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return getattr(self.asyn, attr)
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class memoized_method:
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"""
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Decorator to memmoize a method.
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It works for:
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* async methods (coroutine functions)
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* non-async methods
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* method already decorated with :func:`devlib.asyn.asyncf`.
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.. note:: This decorator does not rely on hacks to hash unhashable data. If
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such input is required, it will either have to be coerced to a hashable
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first (e.g. converting a list to a tuple), or the code of
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:func:`devlib.asyn.memoized_method` will have to be updated to do so.
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"""
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def __init__(self, f):
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memo = self
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sig = inspect.signature(f)
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def bind(self, *args, **kwargs):
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bound = sig.bind(self, *args, **kwargs)
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bound.apply_defaults()
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key = (bound.args[1:], tuple(sorted(bound.kwargs.items())))
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return (key, bound.args, bound.kwargs)
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def get_cache(self):
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try:
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cache = self.__dict__[memo.name]
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except KeyError:
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cache = {}
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self.__dict__[memo.name] = cache
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return cache
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if inspect.iscoroutinefunction(f):
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@functools.wraps(f)
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async def wrapper(self, *args, **kwargs):
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cache = get_cache(self)
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key, args, kwargs = bind(self, *args, **kwargs)
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try:
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return cache[key]
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except KeyError:
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x = await f(*args, **kwargs)
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cache[key] = x
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return x
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else:
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@functools.wraps(f)
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def wrapper(self, *args, **kwargs):
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cache = get_cache(self)
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key, args, kwargs = bind(self, *args, **kwargs)
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try:
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return cache[key]
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except KeyError:
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x = f(*args, **kwargs)
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cache[key] = x
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return x
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self.f = wrapper
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self._name = f.__name__
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@property
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def name(self):
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return '__memoization_cache_of_' + self._name
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def __call__(self, *args, **kwargs):
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return self.f(*args, **kwargs)
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def __get__(self, obj, owner=None):
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return self.f.__get__(obj, owner)
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def __set__(self, obj, value):
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raise RuntimeError("Cannot monkey-patch a memoized function")
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def __set_name__(self, owner, name):
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self.name = name
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def asyncf(f):
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"""
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Decorator used to turn a coroutine into a blocking function, with an
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optional asynchronous API.
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**Example**::
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@asyncf
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async def foo(x):
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await do_some_async_things(x)
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return x
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# Blocking call, just as if the function was synchronous, except it may
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# use asynchronous code inside, e.g. to do concurrent operations.
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foo(42)
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# Asynchronous API, foo.asyn being a corountine
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await foo.asyn(42)
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This allows the same implementation to be both used as blocking for ease of
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use and backward compatibility, or exposed as a corountine for callers that
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can deal with awaitables.
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"""
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@functools.wraps(f)
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def blocking(*args, **kwargs):
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# Since run() needs a corountine, make sure we provide one
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async def wrapper():
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x = f(*args, **kwargs)
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# Async generators have to be consumed and accumulated in a list
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# before crossing a blocking boundary.
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if inspect.isasyncgen(x):
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def genf():
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asyncgen = x.__aiter__()
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while True:
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try:
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yield asyncio.run(asyncgen.__anext__())
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except StopAsyncIteration:
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return
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return genf()
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else:
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return await x
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return asyncio.run(wrapper())
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return _AsyncPolymorphicFunction(
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asyn=f,
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blocking=blocking,
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)
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class _AsyncPolymorphicCM:
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"""
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Wrap an async context manager such that it exposes a synchronous API as
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well for backward compatibility.
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"""
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def __init__(self, async_cm):
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self.cm = async_cm
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def __aenter__(self, *args, **kwargs):
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return self.cm.__aenter__(*args, **kwargs)
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def __aexit__(self, *args, **kwargs):
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return self.cm.__aexit__(*args, **kwargs)
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def __enter__(self, *args, **kwargs):
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return asyncio.run(self.cm.__aenter__(*args, **kwargs))
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def __exit__(self, *args, **kwargs):
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return asyncio.run(self.cm.__aexit__(*args, **kwargs))
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def asynccontextmanager(f):
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"""
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Same as :func:`contextlib.asynccontextmanager` except that it can also be
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used with a regular ``with`` statement for backward compatibility.
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"""
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f = contextlib.asynccontextmanager(f)
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@functools.wraps(f)
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def wrapper(*args, **kwargs):
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cm = f(*args, **kwargs)
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return _AsyncPolymorphicCM(cm)
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return wrapper
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class ConcurrentAccessBase(abc.ABC):
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"""
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Abstract Base Class for resources tracked by :func:`concurrently`.
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"""
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@abc.abstractmethod
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def overlap_with(self, other):
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"""
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Return ``True`` if the resource overlaps with the given one.
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:param other: Resources that should not overlap with ``self``.
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:type other: devlib.utils.asym.ConcurrentAccessBase
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.. note:: It is guaranteed that ``other`` will be a subclass of our
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class.
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"""
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class PathAccess(ConcurrentAccessBase):
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"""
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Concurrent resource representing a file access.
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:param namespace: Identifier of the namespace of the path. One of "target" or "host".
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:type namespace: str
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:param path: Normalized path to the file.
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:type path: str
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:param mode: Opening mode of the file. Can be ``"r"`` for read and ``"w"``
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for writing.
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:type mode: str
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"""
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def __init__(self, namespace, path, mode):
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assert namespace in ('host', 'target')
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self.namespace = namespace
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assert mode in ('r', 'w')
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self.mode = mode
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self.path = os.path.abspath(path) if namespace == 'host' else os.path.normpath(path)
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def overlap_with(self, other):
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path1 = pathlib.Path(self.path).resolve()
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path2 = pathlib.Path(other.path).resolve()
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return (
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self.namespace == other.namespace and
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'w' in (self.mode, other.mode) and
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(
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path1 == path2 or
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path1 in path2.parents or
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path2 in path1.parents
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)
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)
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def __str__(self):
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mode = {
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'r': 'read',
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'w': 'write',
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}[self.mode]
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return '{} ({})'.format(self.path, mode)
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