ETHEREUM Event Loop Error: Guide to Close «Event Logs»
As a developer, he uses Python for the Binance Futures transactions, he probably met the fault of the dreaded «event loop». Because of this problem, the program suddenly ceases and leaves incomplete or inconsistent data. In this article, we are immersed in the causes of this error and solve it step by step.
Event Loop Understand
In the Python Asyncio Library, which is used to build concomitant programs, the event logo is responsible for managing tasks. When a task is completed, the event loop checks that any other task awaits the resources. If there are no such tasks, the event loops say «closed» and the program will be completed.
The Causes of «Event Logs Closed» Error
The «event loop closed» error usually occurs when one or more tasks are blocked (waiting) on I/O operations (input/output, network, etc.) if it is returned to the event loop. This can happen for a variety of reasons, including:
1.
Waiting to complete tasks : If two or more tasks await each other to complete, the event loop may block, which is the «event loop is closed» error.
Solutions to solve the error
To solve the «Event loop» error, you must ensure that the program is cleaned clean and does not block it indefinitely. Here are some solutions to try:
1. Use blocking I/O directory
Instead of using Python asynchronous I/O libraries (such as asyncio,aiohttp), use I/O libraries, such as «Ctypes», «SOCKET» or «Select». These libraries provide direct access to system resources and can help prevent obstacles.
`Python
Import Ctypes
…
try:
Do an operation here I/O
ctypes.c_int (1)
simulate some I/O
Except for the exception like E:
Print (F «Error: {E}»)
`
2. Use a simultaneous enforcement framework
Python Asyncio Library provides an event loop that can run on multiple threads or processes simultaneously. However, working with external libraries or simultaneous tasks is essential to ensure proper synchronization.
To avoid events blocking the main thread, you can use a «fiber» directory or a conthent.futures context manager. Here’s an example using the «threads»:
`Python
Import
Def Perform_task ():
Do some I/O operations here
ctypes.c_int (1)
simulate some I/O
Lock = threading.Lock ()
Def Main ():
Task = threading.thread (Target = Perform_task)
Task.start ()
try:
Do something else while the task is running
pass
Finally:
Task.join ()
main()
`
3. Use a line -based solution
The line -based solution allows you to perform the tasks parallel without blocking each other.
Ethereum: How can I except «Event loop is closed» error?
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ETHEREUM Event Loop Error: Guide to Close «Event Logs»
As a developer, he uses Python for the Binance Futures transactions, he probably met the fault of the dreaded «event loop». Because of this problem, the program suddenly ceases and leaves incomplete or inconsistent data. In this article, we are immersed in the causes of this error and solve it step by step.
Event Loop Understand
In the Python Asyncio Library, which is used to build concomitant programs, the event logo is responsible for managing tasks. When a task is completed, the event loop checks that any other task awaits the resources. If there are no such tasks, the event loops say «closed» and the program will be completed.
The Causes of «Event Logs Closed» Error
The «event loop closed» error usually occurs when one or more tasks are blocked (waiting) on I/O operations (input/output, network, etc.) if it is returned to the event loop. This can happen for a variety of reasons, including:
1.
Solutions to solve the error
To solve the «Event loop» error, you must ensure that the program is cleaned clean and does not block it indefinitely. Here are some solutions to try:
1. Use blocking I/O directory
Instead of using Python asynchronous I/O libraries (such as
asyncio,aiohttp), use I/O libraries, such as «Ctypes», «SOCKET» or «Select». These libraries provide direct access to system resources and can help prevent obstacles.`
PythonImport Ctypes
…
try:
Do an operation here I/O
ctypes.c_int (1)
simulate some I/O
Except for the exception like E:
Print (F «Error: {E}»)
`
2. Use a simultaneous enforcement framework
Python Asyncio Library provides an event loop that can run on multiple threads or processes simultaneously. However, working with external libraries or simultaneous tasks is essential to ensure proper synchronization.
To avoid events blocking the main thread, you can use a «fiber» directory or a conthent.futures context manager. Here’s an example using the «threads»:
`
PythonImport
Def Perform_task ():
Do some I/O operations here
ctypes.c_int (1)
simulate some I/O
Lock = threading.Lock ()
Def Main ():
Task = threading.thread (Target = Perform_task)
Task.start ()
try:
Do something else while the task is running
pass
Finally:
Task.join ()
main()
`
3. Use a line -based solution
The line -based solution allows you to perform the tasks parallel without blocking each other.
`
Pythonimport line
Import
Class Taskqueue:
Def __init __ (Self):
Self.queue = row.queue ()
DE Chessk_task (Self, Task):
SELF.QUEUE.PUT ((task, no))
Def performance_task (task, lock):
try:
Do some I/O operations here
ctypes.c_int (1)
simulate some I/O
Finally:
with lock:
Print («The task is filled»)
Create a set of assignments and send the tasks
row = Taskqueue ()
Tasks = []
Because I in the range (10):
Task = threading.thread (Target = Perform_task, Args = (I,))
Task.start ()
tasks.Append ((task, «task {}». Format (i))))
Run the main thread until the tasks run in parallel
Def Main ():
To the task, in the message tasks:
Task.join ()
main()
`
4.
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