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* Init commit for async plasma client * Create an eventloop model for ray/plasma * Implement a poll-like selector base on `ray.wait`. Huge improvements. * Allow choosing workers & selectors * remove original design * initial implementation of epoll-like selector for plasma * Add a param for `worker` used in `PlasmaSelectorEventLoop` * Allow accepting a `Future` which returns object_id * Do not need `io.py` anymore * Create a basic testing model * fix: `ray.wait` returns tuple of lists * fix a few bugs * improving performance & bug fixing * add test * several improvements & fixing * fix relative import * [async] change code format, remove old files * [async] Create context wrapper for the eventloop * [async] fix: context should return a value * [async] Implement futures grouping * [async] Fix bugs & replace old functions * [async] Fix bugs found in tests * [async] Implement `PlasmaEpoll` * [async] Make test faster, add tests for epoll * [async] Fix code format * [async] Add comments for main code. * [async] Fix import path. * [async] Fix test. * [async] Compatibility. * [async] less verbose to not annoy the CI. * [async] Add test for new API * [async] Allow showing debug info in some of the test. * [async] Fix test. * [async] Proper shutdown. * [async] Lint~ * [async] Move files to experimental and create API * [async] Use async/await syntax * [async] Fix names & styles * [async] comments * [async] bug fixing & use pytest * [async] bug fixing & change tests * [async] use logger * [async] add tests * [async] lint * [async] type checking * [async] add more tests * [async] fix bugs on waiting a future while timeout. Add more docs. * [async] Formal docs. * [async] Add typing info since these codes are compatible with py3.5+. * [async] Documents. * [async] Lint. * [async] Fix deprecated call. * [async] Fix deprecated call. * [async] Implement a more reasonable way for dealing with pending inputs. * [async] Fix docs * [async] Lint * [async] Fix bug: Type for time * [async] Set our eventloop as the default eventloop so that we can get it through `asyncio.get_event_loop()`. * [async] Update test & docs. * [async] Lint. * [async] Temporarily print more debug info. * [async] Use `Poll` as a default option. * [async] Limit resources. * new async implementation for Ray * implement linked list * bug fix * update * support seamless async operations * update * update API * fix tests * lint * bug fix * refactor names * improve doc * properly shutdown async_api * doc * Change the table on the index page. * Adjust table size. * Only keeps `as_future`. * change how we init connection * init connection in `ray.worker.connect` * doc * fix * Move initialization code into the module. * Fix docs & code * Update pyarrow version. * lint * Restore index.rst * Add known issues. * Apply suggestions from code review Co-Authored-By: suquark <suquark@gmail.com> * rename * Update async_api.rst * Update async_api.py * Update async_api.rst * Update async_api.py * Update worker.py * Update async_api.rst * fix tests * lint * lint * replace the magic number
87 lines
4.8 KiB
ReStructuredText
87 lines
4.8 KiB
ReStructuredText
Async API (Experimental)
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========================
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Since Python 3.5, it is possible to write concurrent code using the ``async/await`` `syntax <https://docs.python.org/3/library/asyncio.html>`__.
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This document describes Ray's support for asyncio, which enables integration with popular async frameworks (e.g., aiohttp, aioredis, etc.) for high performance web and prediction serving.
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Starting Ray
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------------
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You must initialize Ray first.
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Please refer to `Starting Ray`_ for instructions.
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.. _`Starting Ray`: http://ray.readthedocs.io/en/latest/tutorial.html#starting-ray
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Converting Ray objects into asyncio futures
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-------------------------------------------
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Ray object IDs can be converted into asyncio futures with ``ray.experimental.async_api``.
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.. code-block:: python
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import asyncio
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import time
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import ray
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from ray.experimental import async_api
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@ray.remote
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def f():
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time.sleep(1)
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return {'key1': ['value']}
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ray.init()
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future = async_api.as_future(f.remote())
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asyncio.get_event_loop().run_until_complete(future) # {'key1': ['value']}
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.. autofunction:: ray.experimental.async_api.as_future
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Example Usage
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-------------
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+----------------------------------------+-----------------------------------------------------+
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| **Basic Python** | **Distributed with Ray** |
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+----------------------------------------+-----------------------------------------------------+
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| .. code-block:: python | .. code-block:: python |
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| # Execute f serially. | # Execute f in parallel. |
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| def f(): | @ray.remote |
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| time.sleep(1) | def f(): |
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| return 1 | time.sleep(1) |
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| | return 1 |
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| | |
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| | ray.init() |
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| results = [f() for i in range(4)] | results = ray.get([f.remote() for i in range(4)]) |
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+----------------------------------------+-----------------------------------------------------+
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| **Async Python** | **Async Ray** |
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+----------------------------------------+-----------------------------------------------------+
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| .. code-block:: python | .. code-block:: python |
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| # Execute f asynchronously. | # Execute f asynchronously with Ray/asyncio. |
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| | from ray.experimental import async_api |
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| | @ray.remote |
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| async def f(): | def f(): |
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| await asyncio.sleep(1) | time.sleep(1) |
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| return 1 | return 1 |
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| | ray.init() |
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| loop = asyncio.get_event_loop() | loop = asyncio.get_event_loop() |
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| tasks = [f() for i in range(4)] | tasks = [async_api.as_future(f.remote()) |
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| | for i in range(4)] |
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| results = loop.run_until_complete( | results = loop.run_until_complete( |
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| asyncio.gather(tasks)) | asyncio.gather(tasks)) |
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+----------------------------------------+-----------------------------------------------------+
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Known Issues
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------------
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Async API support is experimental, and we are working to improve its performance. Please `let us know <https://github.com/ray-project/ray/issues>`__ any issues you encounter.
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