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Gevent be or not to be
- 1. Gevent: be or not to be? Александр Мокров
- 2. About ● asynchrony ● gevent ● asyncio ● пример построения асинхронного приложения
- 3. Web APP Task queue Task queue Task queue WorkerWorkerWorker DB Push tasks into queue Workers pull task from queue Report progress Pull DP for report status
- 4. Tasks workflow get flour bake pie get meat seal pie create dough order pie get milk get aggs
- 5. Applications as services Service 1 Worker Worker Service 3 Worker Worker Service 2 Worker Service 2 Worker Worker Worker Worker
- 8. entry task service task 1 DB callback task 1 service task n callback task n Callbacks
- 9. entry task service task 1 DB callback task 1 service task n callback task n Callbacks
- 10. entry task service task 1 DB callback task 1 service task n callback task n Callbacks
- 11. What we want entry task service task 1 service task 2 service task n
- 12. What we want entry task service task 1 service task 2 service task n
- 17. Gevent gevent is a concurrency library based around libev. It provides a clean API for a variety of concurrency and network related tasks.
- 18. Greenlet The primary pattern used in gevent is the Greenlet, a lightweight coroutine provided to Python as a C extension module. Greenlets all run inside of the OS process for the main program but are scheduled cooperatively. Only one greenlet is ever running at any given time. Spin-off of Stackless, a version of CPython that supports micro-threads called “tasklets”. Tasklets run pseudo-concurrently (typically in a single or a few OS-level threads) and are synchronized with data exchanges on “channels”. Its coroutine
- 19. The way to gevent ● Stackless ● Greenlet ● Eventlet ● Gevent
- 20. Event loop
- 21. def foo(): print('Running in foo') gevent.sleep(0) print('Explicit context switch to foo') def bar(): print('Explicit context to bar') gevent.sleep() print('Implicit context switch to bar') gevent.joinall([ gevent.spawn(foo), gevent.spawn(bar), ]) Synchronous & Asynchronous Execution. Context Switching Running in foo Explicit context to bar Explicit context switch to foo Implicit context switch to bar
- 22. def task(pid): gevent.sleep(random.randint(0,2)*0.001) print('Task %s done' % pid) def synchronous(): for i in range(1, 8): task(i) Synchronous & Asynchronous Execution Task 1 done Task 2 done Task 3 done Task 4 done Task 5 done Task 6 done Task 7 done
- 23. def task(pid): gevent.sleep(random.randint(0,2)*0.001) print('Task %s done' % pid) def asynchronous(): threads = [gevent.spawn(task, i) for i in range(1, 8)] gevent.joinall(threads) Task 1 done Task 5 done Task 6 done Task 2 done Task 4 done Task 7 done Task 3 done Synchronous & Asynchronous Execution
- 25. def callback_hell(param): def _cb1(result): def _cb2(result): def _cb3(result): def _cb4(result): def _cb5(result): def _cb6(result): def _cb7(result): def _cb8(result): return func9(param).add_callback(_cb2) return func8(param).add_callback(_cb2) return func7(param).add_callback(_cb2) return func6(param).add_callback(_cb2) return func5(param).add_callback(_cb2) return func4(param).add_callback(_cb2) return func3(param).add_callback(_cb2) return func2(param).add_callback(_cb2) return func1(param).add_callback(_cb1) Callback hell
- 26. def echo(i): time.sleep(0.001) return i # Non Deterministic Process Pool from multiprocessing.pool import Pool p = Pool(10) run1 = [a for a in p.imap_unordered(echo, range(10))] run2 = [a for a in p.imap_unordered(echo, range(10))] run3 = [a for a in p.imap_unordered(echo, range(10))] run4 = [a for a in p.imap_unordered(echo, range(10))] print(run1 == run2 == run3 == run4) False Determinism
- 27. # Deterministic Gevent Pool from gevent.pool import Pool p = Pool(10) run1 = [a for a in p.imap_unordered(echo, range(10))] run2 = [a for a in p.imap_unordered(echo, range(10))] run3 = [a for a in p.imap_unordered(echo, range(10))] run4 = [a for a in p.imap_unordered(echo, range(10))] print(run1 == run2 == run3 == run4) True Determinism
- 28. Spawning Greenlets from gevent import Greenlet thread1 = Greenlet.spawn(foo, "message", 1) thread2 = gevent.spawn(foo, "message", 2) thread3 = gevent.spawn(lambda x: (x+1), 2) threads = [thread1, thread2, thread3] # Block until all threads complete. gevent.joinall(threads)
- 29. class MyGreenlet(Greenlet): def __init__(self, message, n): Greenlet.__init__(self) self.message = message self.n = n def _run(self): print(self.message) gevent.sleep(self.n) g = MyGreenlet("Hi there!", 3) g.start() g.join() Spawning Greenlets
- 30. Greenlet State started -- Boolean, indicates whether the Greenlet has been started ready() -- Boolean, indicates whether the Greenlet has halted successful() -- Boolean, indicates whether the Greenlet has halted and not thrown an exception value -- arbitrary, the value returned by the Greenlet exception -- exception, uncaught exception instance thrown inside the greenlet
- 32. from gevent import Timeout timeout = Timeout(seconds=10) timeout.start() def wait(): gevent.sleep(10) print('Completed') try: gevent.spawn(wait).join() except Timeout: print('Could not complete') Timeouts
- 33. time_to_wait = 5 # seconds class TooLong(Exception): pass with Timeout(time_to_wait, TooLong): gevent.sleep(10) Timeouts
- 34. class Queue(maxsize=None, items=None) empty() full() get(block=True, timeout=None) get_nowait() next() peek(block=True, timeout=None) peek_nowait() put(item, block=True, timeout=None) put_nowait(item) qsize() Queues
- 36. greenlet greenlet greenlet service results dispatcher service service service reply_to services queues subscribe gevent.queues Asynchronous RPC
- 42. import socket print(socket.socket) from gevent import monkey monkey.patch_socket() print("After monkey patch") print(socket.socket) import select print(select.select) monkey.patch_select() print("After monkey patch") print(select.select) <class 'socket.socket'> After monkey patch <class 'gevent._socket3.socket'> <built-in function select> After monkey patch <function select at 0x7ff7e111c378> Monkey patching
- 43. Stack layout for a greenlet | ^^^ | | older data | | | stack_stop . |_______________| . | | . | greenlet data | . | in stack | . * |_______________| . . _____________ stack_copy + stack_saved . | | | | . | data | |greenlet data| . | unrelated | | saved | . | to | | in heap | stack_start . | this | . . |_____________| stack_copy | greenlet | | | | newer data | | vvv |
- 44. What instead?
- 45. PEP 255 -- Simple Generators Authors: Neil Schemenauer <nas at arctrix.com>, Tim Peters <tim.peters at gmail.com>, Magnus Lie Hetland <magnus at hetland.org> Created: 18-May-2001 Python 2.2
- 46. PEP 342 Coroutine via Enhanced Generators Authors: Guido van Rossum, Phillip J. Eby Created: 10-May-2005 Python 2.5 PEP 288, Generators Attributes and Exceptions (Raymond Hettinger) PEP 325, Resource-Release Support for Generators (Samuele Pedroni)
- 47. What’s new? 1. (yield) statement: value = (yield) 2. send() 3. throw() 4. close() 5. Ensure that close() is called when a generator iterator is garbage-collected. 6. Allow yield to be used in try/finally blocks
- 49. Produce, Filter, and Consume producer consumerfilterfilter ... send sendsend (yield) (yield)(yield)
- 50. RESULT = yield from EXPR PEP 380 Syntax for Delegating to aSubgenerator Authors: Gregory Ewing Created: 13-Feb-2009 Python 3.3 - September 29, 2012
- 51. PEP 0492 -- Coroutines with async and await syntax Authors: Yury Selivanov Created: 09-Apr-2015 Python 3.5
- 52. asynciotulip
- 53. Event loop async def coroutine(): print('Running in coro') event_loop = asyncio.get_event_loop() try: print('init coroutine') coro = coroutine() print('waiting for ...') event_loop.run_until_complete(coro) finally: print('closing event loop') event_loop.close() init coroutine waiting for ... Running in coro closing event loop
- 54. Coroutines, futures and tasks ● Coroutines ○ async def ○ @asyncio.coroutine ● Futures ○ promise of a result or an error ● Tasks ○ future which runs a coroutine
- 55. Chaining coroutines async def chain(): result1 = await step1() result2 = await step2(result1) result3 = await step3(result2) return result2, result3
- 56. async def task(pid): asyncio.sleep(random.randint(0, 2)*0.001) print(f'Task {pid} done') loop = asyncio.get_event_loop() futures = asyncio.gather( *[task(i) for i in range(7)]) loop.run_until_complete(futures) loop.close() Task 3 done Task 2 done Task 4 done Task 5 done Task 1 done Task 6 done Task 0 done Asynchronous Execution
- 57. Queues ● Queue ● PriorityQueue ● LifoQueue
- 58. Transport and protocols (callback based API) Streams (coroutine based API)
- 59. greenlet greenlet coro service results dispatcher service service service reply_to services queues subscribe asyncio.queues Asynchronous RPC
- 62. Combining Coroutines with Threads and Processes executor = concurrent.futures.ProcessPoolExecutor( max_workers=3, ) event_loop = asyncio.get_event_loop() try: event_loop.run_until_complete( run_blocking_tasks(executor) ) finally: event_loop.close()
- 63. Summary ● В мире python много библиотек хороших и разных ● Некоторые библиотеки, когда-то популярные, уступают свое место новым, более продуманным ● Чтобы крепче спать, не ковыряйтесь в потрохах ● Не всё то, чем кажется
- 65. Thank you!