| Name | Last modified | Size | Description | |
|---|---|---|---|---|
| Parent Directory | - | |||
| __init__.py | 2025-10-09 16:21 | 400 | ||
| __pycache__/ | 2026-05-29 04:52 | - | ||
| procfs.py | 2025-10-09 16:21 | 35K | ||
| utilist.py | 2025-10-09 16:21 | 862 | ||
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$ ea=JJj"Tzţ > a iN @ sf d Z ddlZddlZddlZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZmZmZmZmZmZmZ ee e eeeehZze W n ey i ZY n0 dd ZG dd deZee e fZ dd Z d d Z d d Z!dd Z"d&ddZ#d'ddZ$e$Z%d(ddZ&G dd dZ'G dd d e'Z(d d Z)d)d d Z*ej+d!krbG d"d# d#Z,G d$d% d%e'Z-dS )*a Basic infrastructure for asynchronous socket service clients and servers. There are only two ways to have a program on a single processor do "more than one thing at a time". Multi-threaded programming is the simplest and most popular way to do it, but there is another very different technique, that lets you have nearly all the advantages of multi-threading, without actually using multiple threads. it's really only practical if your program is largely I/O bound. If your program is CPU bound, then pre-emptive scheduled threads are probably what you really need. Network servers are rarely CPU-bound, however. If your operating system supports the select() system call in its I/O library (and nearly all do), then you can use it to juggle multiple communication channels at once; doing other work while your I/O is taking place in the "background." Although this strategy can seem strange and complex, especially at first, it is in many ways easier to understand and control than multi-threaded programming. The module documented here solves many of the difficult problems for you, making the task of building sophisticated high-performance network servers and clients a snap. N) EALREADY EINPROGRESS EWOULDBLOCK ECONNRESETEINVALENOTCONN ESHUTDOWNEISCONNEBADF ECONNABORTEDEPIPEEAGAIN errorcodec C sF z t | W S tttfy@ | tv r4t| Y S d| Y S 0 d S )NzUnknown error %s)osstrerror ValueError OverflowError NameErrorr )err r /usr/lib64/python3.9/asyncore.py _strerrorD s r c @ s e Zd ZdS )ExitNowN)