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【已解决】Flask的gunicorn中多进程多worker如何共享数据或单实例

Flask crifan 2164浏览 0评论

折腾:

【部分解决】Python中实现多线程或多进程中的单例singleton

期间,需要去在用gunicorn去部署Flask的情况下,对于基于threads的gunicorn,多个worker:

<code>[2018-08-29 17:14:57 +0800] [19328] [INFO] Starting gunicorn 19.9.0
[2018-08-29 17:14:57 +0800] [19328] [INFO] Listening at: http://0.0.0.0:32851 (19328)
[2018-08-29 17:14:57 +0800] [19328] [INFO] Using worker: threads
[2018-08-29 17:14:57 +0800] [19342] [INFO] Booting worker with pid: 19342
[2018-08-29 17:14:58 +0800] [19344] [INFO] Booting worker with pid: 19344
[2018-08-29 17:14:58 +0800] [19347] [INFO] Booting worker with pid: 19347
[2018-08-29 17:14:58 +0800] [19349] [INFO] Booting worker with pid: 19349
[2018-08-29 17:14:58 +0800] [19353] [INFO] Booting worker with pid: 19353
[2018-08-29 17:14:58 +0800] [19356] [INFO] Booting worker with pid: 19356
[2018-08-29 17:14:58 +0800] [19357] [INFO] Booting worker with pid: 19357
[2018-08-29 17:14:58 +0800] [19360] [INFO] Booting worker with pid: 19360
[2018-08-29 17:14:58 +0800] [19362] [INFO] Booting worker with pid: 19362
[2018-08-29 17:55:09 +0800] [25949] [INFO] Starting gunicorn 19.9.0
[2018-08-29 17:55:09 +0800] [25949] [INFO] Listening at: http://0.0.0.0:32851 (25949)
</code>

中,如何共享数据,或者如何实现多线程/进程的单实例:

python gunicorn threads

Gunicorn’s settings – workers vs threads · Issue #1045 · benoitc/gunicorn

Gunicorn Workers and Threads – Stack Overflow

python – How to run Flask with Gunicorn in multithreaded mode – Stack Overflow

淺談 Gunicorn 各個 worker type 適合的情境 – Genchi Lu – Medium

python gunicorn multiple worker singleton

python 3.x – Falcon/gunicorn code initialization (run once) with multiple workers (singleton?) – Stack Overflow

说是gunicorn有个preload_app:可以实现app运行之前,只初始化一次

Python class/singleton interaction with Django and gunicorn – Stack Overflow

说是:每个process进程有自己独立的内存,所以会有自己的实例

-》建议换用数据库或换成等方式去实现:多进程共享

python – Access app singleton instance in wsgi application – Stack Overflow

Django – gunicorn – App level variable (shared across workers) – Stack Overflow

Singletons and their Problems in Python | Armin Ronacher’s Thoughts and Writings

Shared data with multiple gevent workers · Issue #1026 · benoitc/gunicorn

“If you want to do this use case, I recommend you to use Redis or something like that between workers.”

还是建议多个worker之间共享数据用:redis

python multiple process singleton

python singleton into multiprocessing – Stack Overflow

说是:

最好是单独制定一个线程去处理数据,然后别人线程去从改线程去获取即可实现共享。

其中包括用IPC去通信获取数据。

另外方案:多个线程 share 数据

17.2. multiprocessing — Process-based parallelism — Python 3.7.0 documentation

python – Shared-memory objects in multiprocessing – Stack Overflow

flask gunicorn multiprocessing share data

python – How to share in memory resources between Flask methods when deploying with Gunicorn – Stack Overflow

Settings — Gunicorn 19.9.0 documentation

“preload_app

* –preload

* False

Load application code before the worker processes are forked.

By preloading an application you can save some RAM resources as well as speed up server boot times. Although, if you defer application loading to each worker process, you can reload your application code easily by restarting workers.”

Handle multiprocess setups using preloading and equivilents · Issue #127 · prometheus/client_python

I have never found a good example of a Python web server that provides some mech… | Hacker News

Python Multithreading Tutorial: Concurrency and Parallelism | Toptal

python – Sharing static global data among processes in a Gunicorn / Flask app – Stack Overflow

“Gunicorn can work with gevent to create a server that can support multiple clients within a single worker process using coroutines, that could be a good option for your needs.”

说是:其实可以换基于gevents的gunicorn,然后只是一个worker process然后内部多个coroutine

python – Gunicorn shared memory between multiprocessing processes and workers – Stack Overflow

python – Sharing Memory in Gunicorn? – Stack Overflow

目前看起来,貌似用gunicorn的gevent最省事?

其次是mmap file

不过,先去改回之前的配置:

<code>import multiprocessing

worker_class = 'sync'                           #默认的是sync模式
workers = multiprocessing.cpu_count() * 2 + 1   #进程数
threads = 2                                     #指定每个进程开启的线程数
</code>

用于去确认之前别人用:

<code>
class Singleton(type):
    """
    reference: https://stackoverflow.com/questions/31875/is-there-a-simple-elegant-way-to-define-singletons

    """

    _instances = {}

    def __call__(cls, *args, **kwargs):
        if cls not in cls._instances:
            cls._instances[cls] = super(
                Singleton, cls).__call__(*args, **kwargs)
        return cls._instances[cls]

class SearchBasedQA(metaclass=Singleton):
...
</code>

对于gunicorn的多worker/多线程中,是否能实现单例

结果也是不行的:

<code>[2018-08-30 09:54:41,923 INFO qa.py:31 &lt;module&gt;] [2018-08-30 09:54:41.923486] loaded SearchBasedQA: searchBasedQa=&lt;nlp.search.qa.iqa.SearchBasedQA object at 0x7f05c87bf978&gt;

[2018-08-30 09:54:46,273 INFO qa.py:31 &lt;module&gt;] [2018-08-30 09:54:46.273489] loaded SearchBasedQA: searchBasedQa=&lt;nlp.search.qa.iqa.SearchBasedQA object at 0x7f05c87beb38&gt;
</code>

然后再去尝试gunicorn的gevent方法:

【已解决】用gunicorn的gevent解决之前多worker多Process线程的单例的数据共享

期间,有点理解逻辑了:

  • gunicorn中的worker=process=进程:相对最消耗资源

  • thread=线程:(内存等)资源消耗比process小

  • coroutine=协程:资源消耗比thread小

期间去:

【已解决】Flask的Celery的log中显示:Stale pidfile exists – Removing it和指定celerybeat.pid位置

虽然解决问题了,但是又出现其他相关的问题:

【未解决】Flask中gunicorn部署和supervisor管理celery的worker导致多线程导致单例失效

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