使用龙卷风ioloop将大蟒蛇泡菜文件加载到内存中

时间:2018-03-09 07:36:35

标签: python asynchronous tornado

我正在构建一个测试服务器,当端点被命中时,它会加载一个巨大的pickle文件(花费大约30秒)。我的目标是在龙卷风Web服务器作为单独的线程启动时更新它以将pickle作为python对象加载到后台的内存中。因此,当端点被命中时,它要么在内存中找到它,要么等待线程完成加载。这样可以使启动速度更快。

我在这里寻求一些建议,了解添加异步的最佳方法,以使此操作正常运行。

my_server.py

    import tornado.ioloop
    import tornado.web

    from my_class import MyClass

    class MainHandler(tornado.web.RequestHandler):
        def get(self):
            m = MyClass.get_foobar_object_by_name('foobar')
            self.write("Hello, world")

    def make_app():
        return tornado.web.Application([
            (r"/", MainHandler),
        ])

    if __name__ == "__main__":
        app = make_app()
        app.listen(8888)
        MyClass.load()  # takes 30s to load
        tornado.ioloop.IOLoop.current().start()

my_class.py

    class MyClass(object):
        pickle_path = '/opt/some/path/big_file.pickle'
        foobar_map = None

        @staticmethod
        def load():
            # this step takes about 30s to load
            MyClass.foobar_map = pickle.load(open(local_path, 'rb'))

        @staticmethod
        def get_foobar_object_by_name(foobar_name):
            if MyClass.foobar_map is None:
                MyClass.load()
            return MyClass.foobar_map.get(foobar_name)

1 个答案:

答案 0 :(得分:2)

pickle模块具有同步接口,因此异步运行它的唯一方法是在另一个线程上运行它。在Tornado 5.0中使用新的IOLoop.run_in_executor接口:

from tornado.ioloop import IOLoop
from tornado.web import RequestHandler
from tornado.locks import Lock

class MyClass:
    lock = Lock()

    @staticmethod
    async def load():
        async with MyClass.lock():
            # Check again inside the lock to make sure we only do this once. 
            if MyClass.foobar_map is None:
                MyClass.foobar_map = await IOLoop.current().run_in_executor(None, pickle.load, open(local_path, 'rb'))

    @staticmethod
    async def get_foobar_object_by_name(foobar_name):
        if MyClass.foobar_map is None:
            await MyClass.load()
        return MyClass.foobar_map.get(foobar_name)

class MainHandler(RequestHandler):
    async def get(self):
        m = await MyClass.get_foobar_object_by_name('foobar')
        self.write("Hello, world")

请注意async具有传染性:调用async函数的任何内容也需要async并使用await