cols_justification

2022-08-10 Thread Helmut Weingrill
I installed Python 3.11 0b3. In the IDLE, cols_justification works fine 
in my program "sg.Table". When installing Pycharm 2022.2 later, 
"cols_just.." does not work. Error message: File "H:\pf\PyFibu\FIBU.py", 
line 85, in beg_buchen [sg.table(values=list field, headings=header, 
 
^^ TypeError: Table.__init__() received an 
unexpected keyword argument 'cols_justification'. Please, I need help - 
thanks!

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Re: cols_justification

2022-08-10 Thread MRAB

On 2022-08-10 09:02, Helmut Weingrill wrote:

I installed Python 3.11 0b3. In the IDLE, cols_justification works fine
in my program "sg.Table". When installing Pycharm 2022.2 later,
"cols_just.." does not work. Error message: File "H:\pf\PyFibu\FIBU.py",
line 85, in beg_buchen [sg.table(values=list field, headings=header,

^^ TypeError: Table.__init__() received an
unexpected keyword argument 'cols_justification'. Please, I need help -
thanks!


It would've helped if you had mentioned PySimpleGUI. It took me some 
time to figure out what you were talking about!


Anyway, it looks like you're using an older version of it when using 
PyCharm (or PyCharm is finding an older version of it or Python).

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RE: Parallel(?) programming with python

2022-08-10 Thread Dieter Maurer
Schachner, Joseph (US) wrote at 2022-8-9 17:04 +:
>Why would this application *require* parallel programming?   This could be 
>done in one, single thread program.   Call time to get time and save it as 
>start_time.   Keep a count of the number of 6 hour intervals, initialize it to 
>0.

You could also use the `sched` module from Python's library.
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Re: Parallel(?) programming with python

2022-08-10 Thread Dennis Lee Bieber
On Wed, 10 Aug 2022 19:33:04 +0200, "Dieter Maurer" 
declaimed the following:

>Schachner, Joseph (US) wrote at 2022-8-9 17:04 +:
>>Why would this application *require* parallel programming?   This could be 
>>done in one, single thread program.   Call time to get time and save it as 
>>start_time.   Keep a count of the number of 6 hour intervals, initialize it 
>>to 0.
>
>You could also use the `sched` module from Python's library.

 Time to really read the library reference manual again...

Though if I read this correctly, a long running action /will/ delay
others -- which could mean the (FFT) process could block collecting new
1-second readings while it is active. It also is "one-shot" on the
scheduled actions, meaning those actions still have to reschedule
themselves for the next time period.


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Re: Parallel(?) programming with python

2022-08-10 Thread 2QdxY4RzWzUUiLuE
On 2022-08-09 at 17:04:51 +,
"Schachner, Joseph (US)"  wrote:

> Why would this application *require* parallel programming?  This could
> be done in one, single thread program.  Call time to get time and save
> it as start_time.  Keep a count of the number of 6 hour intervals,
> initialize it to 0.

In theory, you are correct.

In practice, [stuff] happens.  What if your program crashes?  Or the
computer crashes?  Or there's a Python update?  Or an OS update?  Where
does all that pending data go, and how will you recover it after you've
addressed whatever happened? ¹

OTOH, once you start writing the pending data to a file, then it's an
extremely simple leap to multiple programs (rather than multiple
threads) for all kinds of good reasons.

¹ FWIW, I used to develop highly available systems, such as telephone
switches, which allow [stuff] to happen, and yet continue to function.
It's pretty cool to yank a board (yes, physically remove it, without
warning) from the system without [apparently] disrupting anything.  Such
systems also allow for hardware, OS, and application upgrades, too
(IIRC, we were allowed a handful of seconds of downtime per year to meet
our availability requirements).  That said, designing and building such
a system for the sakes of simplicity and convenience of the application
we're talking about here would make a pretty good definition of
"overkill."
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RE: Parallel(?) programming with python

2022-08-10 Thread avi.e.gross
There are many possible discussions we can have here and some are not really
about whether and how to use Python.

The user asked how to do what is a fairly standard task for some people and
arguably is not necessarily best done using a single application running
things in parallel. 

So, yes, if you have full access to your machine and can schedule tasks,
then some obvious answers come to mind where one process listens and
receives data and stores it, and another process periodically wakes up and
grabs recent data and processes it and perhaps still another process comes
up even less often and does some re-arrangement of old data.

And, yes, for such large volumes of data it may be a poor design to hold all
the data in memory for many hours or even days and various ways of using a
database or files/folders with a naming structure are a good idea.

But the original question remains, in my opinion, a not horrible one. All
kinds of applications can be written with sets of tasks run largely in
parallel with some form of communication between tasks using shared data
structures like queues and perhaps locks and with a requirement that any
tasks that take nontrivial time need a way to buffer any communications to
not block others. 

Also, for people who want to start ONE process and let it run, and perhaps
may not be able to easily schedule other processes on a system level, it can
be advantageous to know how to set up something along those lines within a
single python session.

Of course, for efficiency reasons, any I/O to files slows things down but
what is described here as the situation seems to be somewhat easier and
safer to do in so many other ways. I think a main point is that there are
good ways to avoid the data from being acted on by two parties that share
memory. One is NOT to share memory for this purpose. Another might be to
have the 6-hour process use a lock to move the data aside or send a message
to the receiving process to pause a moment and set the data aside and begin
collecting anew while the old is processed and so on.

There are many such choices and the parts need not be in the same process or
all written in python. But some solutions can be generalized easier than
others. For example, can there become a need to collect data from multiple
sources, perhaps using multiple listeners?

-Original Message-
From: Python-list  On
Behalf Of Dieter Maurer
Sent: Wednesday, August 10, 2022 1:33 PM
To: Schachner, Joseph (US) 
Cc: Andreas Croci ; python-list@python.org
Subject: RE: Parallel(?) programming with python

Schachner, Joseph (US) wrote at 2022-8-9 17:04 +:
>Why would this application *require* parallel programming?   This could be
done in one, single thread program.   Call time to get time and save it as
start_time.   Keep a count of the number of 6 hour intervals, initialize it
to 0.

You could also use the `sched` module from Python's library.
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Re: Parallel(?) programming with python

2022-08-10 Thread Peter J. Holzer
On 2022-08-10 14:19:37 -0400, Dennis Lee Bieber wrote:
> On Wed, 10 Aug 2022 19:33:04 +0200, "Dieter Maurer" 
> declaimed the following:
> >Schachner, Joseph (US) wrote at 2022-8-9 17:04 +:
> >>Why would this application *require* parallel programming?   This
> >>could be done in one, single thread program.   Call time to get time
> >>and save it as start_time.   Keep a count of the number of 6 hour
> >>intervals, initialize it to 0.
[...]
>   Though if I read this correctly, a long running action /will/
>   delay others -- which could mean the (FFT) process could block
>   collecting new 1-second readings while it is active.

Certainly, but does it matter? Data is received from some network
connection and network connections often involve quite a bit of
buffering. If the consumer is blocked for 3 or 4 or maybe even 20
seconds, the producer might not even notice. (This of course depends
very much on the details which we know nothing about.)

hp

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