Ethereum: How can I except “Event loop is closed” error?

** Ethereum Event loop identical:

As a develer who uses Python for the Binance -Future’s transactions, you’re probably folder the mistake off the fairy-to-a. This problem can lead to your program ended abruptly and leaves incomplete or inconsisted data. In the intimidate We will deal with causes off this causes off the provide step-by-step solutions to remedy it.

Understand the event loop

In the Asyncio Library of Python, Which isu isesused to bild simultaneous anados programs, an evening loop is responsible for managing the execution of off. After completing a task, the event loop checks for the resources. The there are no such tasks, the event loop ben “closed” and the program ends.

The “even loop is closed” distinguished

The error “evend loop is closed” apparatus of one one or more tasks in E/A operations (input/output, network, etc.) blocks (wait) with a the event of loop return a control. This can I have been for various reasons, including:

I/O-bound operations

: If a lot does an E/A operation, e.g. B. adhering off the file or senting data to the network it block it unlimited.

Waiting forehead tasks : If you’re just be blocked, which leaves,

Solutions to remedy the different

In order to fix the “even loop completed” distinction, you must make sure your program ends and dos not block an indefinite period. Here’s a some some solutions that you should try:

1. Use a blocking -e/a library

Insteted off pythons asynchronous E/O libraries (e.g. These libraries offen direct to system resources and cans help to bed in the blockage.

`Python



import cty

#

notmpt:




Conduct the E/A Operations here

    ctypies.c_int (1) 

simulate an e/a operation

experding expertion as E:

    print (f "error: {e}")

The Python asyncio library offers an eventful loop that can be carried out on the sightsy or processes. When’s dorming with external libraries or simultaneous tasks, however, it is not important to ensurre proper synchronization.

Toes blocking adents in which thread, you can use a “threading” library or concurrent.futuresContext Manager. Here is example with "threading":

Python



Import threading

DEF Perform_task ():



Do an E/A operation here

    ctypies.c_int (1) 

simulate an e/a operation

lock = threading.lock ()

Def Main ():

    Task = threading.thread (Target = perform_task)

    Task.Start ()

    notmpt:



Do you

        collapsed

    Finally:

        Task.join ()

prirary()

3 ..

With a long -based solution, tasks can be carried out in parallel with a blocking each.

`Python



Import the queue

Import threading

Class task:

    def _init __ (self):

        self.queue = queue.quue ()

    DEF Subjects (self, task):

        self.queue.put ((task, not))

DEF Perform_task (task, lock):

    notmpt:



Do an E/A operation here

        ctypies.c_int (1) 

simulate an e/a operation

    Finally:

        With castle:

            Print ("task completed")

#

Queue = Taskqueue ()

Tasks = []

for I with a realre (10):

    Task = threading.thread (Target = Perform_task, args = (i,))

    Task.Start ()

    the format (i)"))))))))



Executute the them in paralled in parallel

Def Main ():

    For the task, message in task:

        Task.join ()

prirary()

PRIVATE TRADING COMPETITIONS