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Whitespace standardization.

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Tim Peters 2001-01-14 18:09:23 +00:00
parent 538f05c94d
commit 146965abf2
6 changed files with 484 additions and 485 deletions
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22
Lib/asyncore.py
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@ -1,12 +1,12 @@
# -*- Mode: Python -*-
# Id: asyncore.py,v 2.51 2000/09/07 22:29:26 rushing Exp
# Id: asyncore.py,v 2.51 2000/09/07 22:29:26 rushing Exp
# Author: Sam Rushing <rushing@nightmare.com>
# ======================================================================
# Copyright 1996 by Sam Rushing
#
#
# All Rights Reserved
#
#
# Permission to use, copy, modify, and distribute this software and
# its documentation for any purpose and without fee is hereby
# granted, provided that the above copyright notice appear in all
@ -15,7 +15,7 @@
# Rushing not be used in advertising or publicity pertaining to
# distribution of the software without specific, written prior
# permission.
#
#
# SAM RUSHING DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE,
# INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN
# NO EVENT SHALL SAM RUSHING BE LIABLE FOR ANY SPECIAL, INDIRECT OR
@ -28,22 +28,22 @@
"""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
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.
rarely CPU-bound, however.
If your operating system supports the select() system call in its I/O
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.
sophisticated high-performance network servers and clients a snap.
"""
import exceptions
@ -191,7 +191,7 @@ class dispatcher:
ar = repr(self.addr)
except:
ar = 'no self.addr!'
return '<__repr__ (self) failed for object at %x (addr=%s)>' % (id(self),ar)
def add_channel (self, map=None):
@ -324,7 +324,7 @@ class dispatcher:
# log and log_info maybe overriden to provide more sophisitcated
# logging and warning methods. In general, log is for 'hit' logging
# and 'log_info' is for informational, warning and error logging.
# and 'log_info' is for informational, warning and error logging.
def log (self, message):
sys.stderr.write ('log: %s\n' % str(message))
@ -433,7 +433,7 @@ def compact_traceback ():
while 1:
tbinfo.append ((
tb.tb_frame.f_code.co_filename,
tb.tb_frame.f_code.co_name,
tb.tb_frame.f_code.co_name,
str(tb.tb_lineno)
))
tb = tb.tb_next