Ethereum Event loop earror: advertising “the Event loop is closed”
As a Developer Using Python for Binance Future Transactions, and you’re probably encountered the dough from the “evend loop is closed”. This problem- can result in melting the termination of your program, leaf incomplete or inconsisted data. In this article, wet immerse resort in the causes off the ones’ providing step solutions to resool.
Understand the event loop
In the Asyncio Library in Python, the Which ised For the Creation of Simultaneous Programs, aloop of Events is responsible for managing taxes. The Event Loop checks on the there is ended. The there are no such tasks, the event loop be “closed” and the program ends.
** The case is “even loop are closed” different
The “event buckle is closed” generally occursa one or more Task are blocked (pending) on I / O operations (netry / exit, ethc.) with making control in these. This can I have been for various reasons, including:
- Operations relate to E / O
: When a Task Performs an E / S operations, such as a file or sending data to a network, not can block indefinitely.
- While waiting to end : If you’re tasks exped to end, the event loop can be blocked, leading to them “even buckle is closed”.
Solutions to resolve the different
To resolve the error “the event loop is closed”, you must make sure your program ends clear and does not block indefinitely. Here’s a some some soulions to try:
1. Use an E / S blocking library
Insteted off python asynchronous e / s asynchronous libraries (for example, Asyncio
,aivotp
), use blocking e / libraries like ctypes,' Thesis Libraries Provide Direct access to system resources and can help in the blockages.
Python
Import cty
#
to try:
Perform the E / S operating here
ctypies.c_int (1)
Simulate an E / S operation
experding expertions like E:
print (f "error: {e}")
'
2.
The Python Asyncio Library Provides Provide Provide works simultaneously on several threads or processes. Howver, Whens Yous Work with External Libraries or Simultaneous Tasks, it is essential to ensurre good synchronization.
Tools blocking adents in the thread, you can use a libraryThreading 'or a "competitor" context manager. Here is the example using "thread":
Python
Import fixed
Def Perform_task ():
Perform an E / S operating here
ctypies.c_int (1)
Simulate an E / S operation
lock = finging.lock ()
Def Main ():
task = threading.thread (target = perform_task)
Task.start ()
to try:
Something
pass
Finally:
Task. Join ()
in which
'
3.
A solution based on the queue allows you to perform tasks in parallel with blocking.
Python
Import queue
Import fixed
Taskqueue Class:
Def _init __ (Self):
self.What = tail.
DEF SUDIDE_TASK (self, task):
self.What.put ((task, not))
Def Perform_task (task, locking):
to try:
Perform an E / O operation here
ctypies.c_int (1)
Simulate an E / S operation
Finally:
With locking:
Print ("task finished")
Create a queue queue
tail = taskqueue ()
tasks = []
For I ar range (10):
task = thread.thread (rrget = perform_task, args = (i,))
Task.start ()
Tasks.Append ((task, "task {}". Forms (i))))
Run the tasks work in parallel
Def Main ():
For the task, message in task:
Task. Join ()
in which
` ‘
4.