Carl Cerecke added the comment:
See section 4.1.5 at https://www.kernel.org/doc/Documentation/networking/can.txt
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Python tracker
<https://bugs.python.org/issue36
New submission from Carl Cerecke :
https://docs.python.org/3/library/socket.html#socket.CAN_RAW_FD_FRAMES
The wording "...however, you one must accept..." doesn't make sense. I think
the "you one" should be "your application", but I'm not sure.
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as
Eric McGraw wrote:
Well, it turns out to be the best way to invert a string, IMO. The
reversed() feature returns a reversed object... not a reversed string.
In short, I have to fool with it again _after_ it has been inverted. The
slicing takes care of the job right away and gives me what I want...
Dave wrote:
This should be simple, but I can't get it:
How do you loop backwards through a list?
For example, in, say, Javascript:
for (var i = list.length - 1; i =0; i--) {
do_stuff()
}
I mean, I could reverse the list, but I don't want to. I want it to
stay exactly the same,
Erik Max Francis wrote:
Terry Hancock wrote:
I doubt that helps much: I pronounce all of those words
(when I use them, which is not too often) as -toopel. The
only tuple I pronounce with the -uh- is couple, and I
usually call that a two-tuple when dealing with Python.
I prefer the name
mwt wrote:
I want to do programmatic terminal commands on unix with python - i.e.
I want my program to issue commands to start and stop scripts, other
programs, etc. I'm sure this must be fairly straightforward, but
haven't been able to find a reference for it. Any help?
Try:
anthonyberet wrote:
Hello again - rather a newbie here...
I want to work on a sudoku brute-forcer, just for fun.
I know what you mean. I wrote one just for fun too.
I am considering different strategies, but first I need to decide on the
data-structure to use for the progress/solution
Well, it doesn't quite rule them all, but it is fast: About three times
faster than using one function per state. Faster than using generators.
Faster than using code objects.
Some, possibly minor, problems:
1. The generated code is ugly.
2. The generated code can be quite large, depending on
Paul Rubin wrote:
Carl Cerecke [EMAIL PROTECTED] writes:
3. Not as fast as byte code hacks, or using pyrex/psyco. Peter Hansen
is right. One of those is likely a better solution if you don't need
pure python.
If you don't need pure python than your approach still beats
everything else
Wolfgang Keller wrote:
On Fri, 20 Jan 2006 05:16:57 +0100, Peter Hansen wrote
(in article [EMAIL PROTECTED]):
I believe the more modern approach to this is to use generators in some
way, yield each other as the next state. This way you avoid all almost
all the function call overhead (the
Fredrik Lundh wrote:
Carl Cerecke wrote:
It turns out that generators are more efficient than the eval function
excuting bits of compiled code. About 20-25% faster.
why are you using generators to return things from a function, when
you can just return the things ?
Trying to find
Carl Cerecke wrote:
Fredrik Lundh wrote:
Carl Cerecke wrote:
It turns out that generators are more efficient than the eval function
excuting bits of compiled code. About 20-25% faster.
why are you using generators to return things from a function, when
you can just return the things
Adding a continue statemtent after the yield statements yields :-) a
speed increase. Still not as good as functions though. (about 30% slower)
Cheers,
Carl
Carl Cerecke wrote:
Carl Cerecke wrote:
Generator FSM done properly (well, better anyway). They are still almost
twice as slow as plain
Randall Parker wrote:
Steve,
This is an aside: I'd love to see someone implement in Python a
framework similar to the Quantum Leaps Quantum Framework for
event-driven programming. I think Python has some features that lend
themselves to a neater implementation than what can be done in
Bengt Richter wrote:
On Thu, 19 Jan 2006 23:16:57 -0500, Peter Hansen [EMAIL PROTECTED] wrote:
How about something like
actions = dict(
...a=compile('print A; state=b','','exec'),
...b=compile('print B; state=c','','exec'),
...c=compile('print C; state=None','','exec')
Petr Jakes wrote:
Sorry, I can't get in. Can you please show me, how to use your approach
on the simple push/push ON/OFF button for example please?
PS: seriously it is not a homework :) and I feel it like a shame I am
asking such a simple questions :(
States: ON, OFF
Transition event:
Petr Jakes wrote:
Hello,
I am trying to study/understand OOP principles using Python. I have
found following code http://tinyurl.com/a4zkn about FSM (finite state
machine) on this list, which looks quite useful for my purposes. As
this code was posted long time ago (November 1998) I would
Dave Hansen wrote:
On Fri, 20 Jan 2006 10:27:58 +1300 in comp.lang.python, Carl Cerecke
[EMAIL PROTECTED] wrote:
[...]
Python has no goto.
+1
[...]
We want a goto.
-1
I agree entirely. My (rather unclearly made) point was that, for the
particular application (FSM
Dan Sommers wrote:
On Fri, 20 Jan 2006 10:27:58 +1300,
Carl Cerecke [EMAIL PROTECTED] wrote:
... now you have a function-call overhead on each state transition ...
Have you profiled your code and demonstrated that this particular
function call consumes too much time?
Yes. For a parser
Steven Bethard wrote:
Carl Cerecke wrote:
Python has no goto.
Not in the standard library. You have to download the module:
http://www.entrian.com/goto/
Haha! Sure. But have you seen how it's implemented? I don't think it
will win many performace prizes. Nifty hack though.
Cheers
Chris Mellon wrote:
I'm not sure why nobody else in this thread said it, but the most
common way of implementing state machines I've seen in Python (unless
theres only a couple states you can manage with if/elif) is to use a
dict to map states to callables.
Ah. Well, my post suggested, as
Carl Cerecke wrote:
Chris Mellon wrote:
I'm not sure why nobody else in this thread said it, but the most
common way of implementing state machines I've seen in Python (unless
theres only a couple states you can manage with if/elif) is to use a
dict to map states to callables.
Ah. Well
2005 Carl Cerecke
# Permission is granted to use, copy, modify, and distribute the code
and/or derived works of the code.
#import psyco
#psyco.full()
import copy
def compute_edge_cells():
global edge_ls
edge_ls = []
for x in range(9):
for y in range(9):
ls
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