Thanks for your reply.
On 08.08.22 13:20, Stefan Ram wrote:
Yes, but this is difficult. If you ask this question here,
you might not be ready for this.
Indeed.
I haven't learned it yet myself, but nevertheless tried to
write a small example program quickly, which might still
contain errors because of my lack of education.
import threading
import time
def write_to_list( list, lock, event ):
for i in range( 10 ):
lock.acquire()
try:
list.append( i )
finally:
lock.release()
event.set()
time.sleep( 3 )
def read_from_list( list, lock, event ):
while True:
event.wait()
print( "Waking up." )
event.clear()
if len( list ):
print( "List contains " + str( list[ 0 ]) + "." )
lock.acquire()
try:
del list[ 0 ]
finally:
lock.release()
else:
print( "List is empty." )
list = []
lock = threading.Lock()
event = threading.Event()
threading.Thread( target=write_to_list, args=[ list, lock, event ]).start()
threading.Thread( target=read_from_list, args=[ list, lock, event ]).start()
If I understand some things correctly, a "lock" would be something that,
as the name says, locks, meaning prevents parts of the program from
executing on the locked resource until ohter parts have finished doing
their things and have released the lock. If this is correct, it's not
exactly what I wanted, because this way "parts of the program" would not
"keep doing their things, while other parts do other things on the same
data".
I'm in principle ok with locks, if it must be. What I fear is that the
lock could last long and prevent the function that writes into the list
from doing so every second. With an FFT on a list that contains a few
bytes taken every second over one week time (604.800 samples), I believe
it's very likely that the FFT function takes longer than a second to return.
Then I would have to import all the data I have missed since the lock
was aquired, which is doable, but I would like to avoid it if possible.
In basketball, first you must learn to dribble and pass,
before you can begin to shoot.
Sure.
With certain reservations, texts that can be considered
to learn Python are:
"Object-Oriented Programming in Python Documentation" - a PDF file,
Introduction to Programming Using Python - Y Daniel Liang (2013),
How to Think Like a Computer Scientist - Peter Wentworth (2012-08-12),
The Coder's Apprentice - Pieter Spronck (2016-09-21), and
Python Programming - John Zelle (2009).
Thank you for the list. I an currently taking a Udemy course and at the
same time reading the tutorials on python.org. I hope I will some day
come to any of the books you suggest (I'm doing this only in my spare
time and it will take forever).
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