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Ethereum Event Loop Error: A Guide to Troubleshooting When the Event Loop is Closed

As a Python developer trading Binance futures, you may have come across the nasty “Event loop closed” error. This issue can cause your program to suddenly stop working, leaving behind incomplete or inconsistent data. In this article, we’ll take a closer look at the causes of this error and provide step-by-step solutions to fix it.

Understanding the Event Loop

In Python’s asyncio library for building concurrent programs, the event loop is responsible for managing the execution of tasks. When a task finishes, the event loop checks to see if there are any other tasks waiting for resources. If there are none, the event loop is considered “closed” and the program exits.

Causes of “Event Loop Closed” Error

The “Event Loop Closed” error typically occurs when one or more tasks are blocked (waiting) on ​​I/O operations (I/O, network, etc.) without returning control to the event loop. This can happen for a variety of reasons, including:

• Input/Output-related operations: When a task is performing an I/O operation, such as reading from a file or sending data over the network, it can become blocked indefinitely.

• Waiting for tasks to complete: If two or more tasks are waiting for each other to complete, the event loop can become blocked, resulting in an “Event Loop Closed” error.

Troubleshooting

To resolve the “Event Loop Closed” error, you must ensure that the program terminates normally and does not become blocked indefinitely. Here are some things to try:

1. Use a blocking I/O library

Instead of using Python’s asynchronous I/O libraries (e.g. “asyncio”, “aiohttp”), use blocking I/O libraries such as “ctypes”, “socket”, or “select”. These libraries allow direct access to system resources and can help prevent bottlenecks.

import ctypes





...
try:

Perform an I/O operation here
ctypes.c_int(1) 
Simulate some I/O operation
except for an exception like e:
print(f"Error: {e}")

2. Use a concurrent execution framework

Python’s asyncio library provides an event loop that can run concurrently across multiple threads or processes. However, when working with external libraries or performing concurrent tasks, it is important to ensure proper synchronization.

To avoid blocking events in the main thread, you can use the ‘threads’ library or the ‘concurrent.futures’ context manager. Here is an example of using threads:

import thread
def perform_task():

Do some I/O here
ctypes.c_int(1) 
Simulate some I/O
block = threading. Block()
def main():
task = threading.Thread(target=execute_task)
task.start()
try:

Do something else while the task is executing
traverse
Finally:
task.join()
main()

3. Use a queue-based solution

A queue-based solution allows tasks to execute in parallel, without blocking each other.

import queue
import thread
TaskQueue class:
def __init__(self):
self.queue = queue.Queue()
def submit_task(self, task):
self.queue.put((task, none))
def perform_task(task, lock):
try:

Do some I/O here
ctypes.c_int(1) 
Simulate some I/O
Finally:
with lock:
print("Task completed")

Create a task queue and submit tasks to it
queue = TaskQueue()
tasks = []
I am in scope (10):
task = thread.Thread(target=perform_task, args=(i,))
task.start()
task.append((task, "Task {}".format(i)))

Start main thread while tasks are executed in parallel
def main():
for task, message in tasks:
task.append()
main()

4.

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