Where I'm using PLY in Coopr, the parsetab.py file is deep in a
hierarchy of source code.  Thus, that directory wasn't on my import
path.

On Oct 16, 4:00 pm, David Beazley <[email protected]> wrote:
> The parsetab.py file created by PLY is supposed to be placed alongside your 
> other source code (hence easily available via import).   If giving code away, 
> you would typically include the parsetab.py file along with your code so that 
> it doesn't have to be regenerated by PLY.   Therefore, I consider this 
> behavior to be an intended feature, not a bug.   I think there is a 
> "picklefile" argument to yacc() that writes the tables to a datafile using 
> pickle instead.  That might be another option to consider.
>
> Cheers,
> Dave
>
> On Oct 16, 2010, at 1:06 PM, Bill Hart wrote:
>
>
>
> > I think I found a work-around.  PLY does do some interesting cache
> > checking, but it does this by 'reading' the parse table file.  Under
> > the hood, this does an 'import', which means that a user needs to
> > augment their sys.path environment if this file is stored in an out-of-
> > the-way location!!
>
> > This sounds like a bug to me...
>
> > --Bill
>
> > On Oct 16, 10:20 am, Bill Hart <[email protected]> wrote:
> >> PLY is used within the Coopr software, and a Coopr user recently noted
> >> that the LR table was being repeatedly written.  I've taken a look at
> >> the code, and I don't see any caching logic.
>
> >> If the write_table option to the yacc() function is 1, then the table
> >> gets written (this is the default).  Otherwise, it looks like it's not
> >> written.
>
> >> Is this correct? I think the intent was for the table signature to
> >> provide a mechanism for detecting when no writing is necessary, but I
> >> don't see that that logic in the code.
>
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