Using PyOpenGL what should I use for a GUI ?

[Gilles Leblanc]

Hi I have started a small project with PyOpenGL. I am wondering what
are the options for a GUI. So far I checked PyUI but it has some
problems with 3d rendering outside the Windows platform.

I know of WxPython but I don't know if I can create a WxPython window,
use gl rendering code in it and then put widgets on top of that...

[Jack Orenstein]

I am using Python 2.2.2 on RH9, and just starting to work with Python
threads.

I started using the threading module and found that 10-20% of the runs
of my test program would hang. I developed smaller and smaller test
cases, finally arriving at the program at the end of this message,
which uses the thread module, not threading. This program seems to
point to problems in Python thread scheduling.

The program is invoked like this:

python threadtest.py THREADS COUNT

THREADS is the number of threads created. Each thread contains a loop
that runs COUNT times, and all threads increment a counter. (The
counter is incremented without locking -- I expect to see a final
count of less than THREADS * COUNT.)

Running with THREADS = 2 and COUNT = 100000, most of the time, the
program runs to completion. About 20% of the time however, I see one
thread finish, but the other thread never resumes.

Here is output from a run that completes normally:

[jao@black]$ python threadtest.py 2 100000
nThreads: 2
nCycles: 100000
thread 1: started
thread 1: i = 0, counter = 1
thread 2: started
thread 2: i = 0, counter = 2691
thread 1: i = 10000, counter = 13496
thread 2: i = 10000, counter = 22526
thread 1: i = 20000, counter = 27120
thread 2: i = 20000, counter = 40365
thread 1: i = 30000, counter = 41264
thread 1: i = 40000, counter = 55922
thread 2: i = 30000, counter = 58416
thread 2: i = 40000, counter = 72647
thread 1: i = 50000, counter = 74602
thread 1: i = 60000, counter = 88468
thread 2: i = 50000, counter = 99319
thread 1: i = 70000, counter = 110144
thread 2: i = 60000, counter = 110564
thread 2: i = 70000, counter = 125306
thread 1: i = 80000, counter = 129252
Still waiting, done = 0
thread 2: i = 80000, counter = 141375
thread 1: i = 90000, counter = 147459
thread 2: i = 90000, counter = 155268
thread 1: leaving
thread 2: leaving
Still waiting, done = 2
All threads have finished, counter = 168322

Here is output from a run that hangs. I killed the process using
ctrl-c.

[jao@black]$ python threadtest.py 2 100000
nThreads: 2
nCycles: 100000
thread 1: started
thread 1: i = 0, counter = 1
thread 2: started
thread 2: i = 0, counter = 990
thread 1: i = 10000, counter = 11812
thread 2: i = 10000, counter = 13580
thread 1: i = 20000, counter = 19127
thread 2: i = 20000, counter = 25395
thread 1: i = 30000, counter = 31457
thread 1: i = 40000, counter = 44033
thread 2: i = 30000, counter = 48563
thread 1: i = 50000, counter = 55131
thread 1: i = 60000, counter = 65291
thread 1: i = 70000, counter = 78145
thread 2: i = 40000, counter = 82715
thread 1: i = 80000, counter = 92073
thread 2: i = 50000, counter = 101784
thread 1: i = 90000, counter = 104294
thread 2: i = 60000, counter = 112866
Still waiting, done = 0
thread 1: leaving
Still waiting, done = 1
Still waiting, done = 1
Still waiting, done = 1
Still waiting, done = 1
Still waiting, done = 1
Still waiting, done = 1
Still waiting, done = 1
Still waiting, done = 1
Traceback (most recent call last):
File "threadtest.py", line 26, in ?
time.sleep(1)
KeyboardInterrupt
[jao@black osh]$

In this case, thread 1 finishes but thread 2 never runs again. Is
this a known problem? Any ideas for workarounds? Are threads widely
used in Python?

Jack Orenstein

# threadtest.py

import sys
import thread
import time

nThreads = int(sys.argv[1])
nCycles = int(sys.argv[2])
print 'nThreads: %d' % nThreads
print 'nCycles: %d' % nCycles
counter = 0
done = 0

def run(id):
global done
print 'thread %d: started' % id
global counter
for i in range(nCycles):
counter += 1
if i % 10000 == 0:
print 'thread %d: i = %d, counter = %d' % (id, i, counter)
print 'thread %d: leaving' % id
done += 1

for i in range(nThreads):
thread.start_new_thread(run, (i + 1,))
while done < nThreads:
time.sleep(1)
print 'Still waiting, done = %d' % done
print 'All threads have finished, counter = %d' % counter

[M.E.Farmer]

This may help.
http://linuxgazette.net/107/pai.html
Also be sure to google.
search strategy:
Python threading
Python threads
Python thread tutorial
threading.py example
Python threading example
Python thread safety
hth,
M.E.Farmer

[Peter Hansen]

Jack Orenstein wrote:

I am using Python 2.2.2 on RH9, and just starting to work with Python
threads.
Is this also the first time you've worked with threads in general,
or do you have much experience with them in other situations?
This program seems to point to problems in Python thread scheduling.
While from time to time bugs in Python are found, it's generally
more productive to suspect one's own code. In any case, you
wouldn't have posted it here if you didn't suspect your own
code at least a bit, so kudos to you for that. :-)
done = 0
def run(id):
global done
print 'thread %d: started' % id
global counter
for i in range(nCycles):
counter += 1
if i % 10000 == 0:
print 'thread %d: i = %d, counter = %d' % (id, i, counter)
print 'thread %d: leaving' % id
done += 1

for i in range(nThreads):
thread.start_new_thread(run, (i + 1,))
while done < nThreads:
time.sleep(1)
print 'Still waiting, done = %d' % done
print 'All threads have finished, counter = %d' % counter

Without having tried to run your code, and without having studied
it for long, I am going to point out something that is at the
very least an inherent defect in your code, though you might
not have used Python (or threads?) for long enough to realize
why. Note that I don't know if this is the cause of your
particular problem, just that it _is_ a bug.

You've got two shared global variables, "done" and "counter".
Each of these is modified in a manner that is not thread-safe.
I don't know if "counter" is causing trouble, but it seems
likely that "done" is.

Basically, the statement "done += 1" is equivalent to the
statement "done = done + 1" which, in Python or most other
languages is not thread-safe. The "done + 1" part is
evaluated separately from the assignment, so it's possible
that two threads will be executing the "done + 1" part
at the same time and that the following assignment of
one thread will be overwritten immediately by the assignment
in the next thread, but with a value that is now one less
than what you really wanted.

Look at the bytecode produced by the statement "done += 1":

import dis
def f(): .... global done
.... done += 1
.... dis.dis(f)

3 0 LOAD_GLOBAL 0 (done)
3 LOAD_CONST 1 (1)
6 INPLACE_ADD
7 STORE_GLOBAL 0 (done)
(ignore the last two lines: they just "return None")
10 LOAD_CONST 0 (None)
13 RETURN_VALUE

Note here the "store_global" that is separate from the add
operation itself. If thread A gets loses the CPU (so to speak)
just before that operation, and thread B executes the entire
suite of operations, then later on when thread A executes
that operation it will effectively result in only a single
addition operation being performed, not two of them.

If you really want to increment globals from the thread, you
should look into locks. Using the "threading" module (as is
generally recommended, instead of using "thread"), you would
use threading.Lock(). There are other thread synchronization
primitives in the threading module as well, some of which
might be more suitable for your purposes. Note also the
oft-repeated (in this forum) recommendation that if you simply
use nothing but the Queue module for inter-thread communication,
you will be very unlikely to stumble over such issues.

-Peter

[Jack Orenstein]

Peter Hansen wrote:

Jack Orenstein wrote:

I am using Python 2.2.2 on RH9, and just starting to work with Python
threads.

Is this also the first time you've worked with threads in general,
or do you have much experience with them in other situations?

Yes, I've used threading in Java.
You've got two shared global variables, "done" and "counter".
Each of these is modified in a manner that is not thread-safe.
I don't know if "counter" is causing trouble, but it seems
likely that "done" is.
I understand that. As I said in my posting, "The counter is
incremented without locking -- I expect to see a final count of less
than THREADS * COUNT." This is a test case, and I threw out more and
more code, including synchronization around counter and done, until it
got as simple as possible and still showed the problem.
Basically, the statement "done += 1" is equivalent to the
statement "done = done + 1" which, in Python or most other
languages is not thread-safe. The "done + 1" part is
evaluated separately from the assignment, so it's possible
that two threads will be executing the "done + 1" part
at the same time and that the following assignment of
one thread will be overwritten immediately by the assignment
in the next thread, but with a value that is now one less
than what you really wanted.
Understood. I was counting on this being unlikely for my test
case. I realize this isn't something to rely on in real software.

If you really want to increment globals from the thread, you
should look into locks. Using the "threading" module (as is
generally recommended, instead of using "thread"), you would
use threading.Lock().

As my note said, I did start with the threading module. And variables
updated by different threads were protected by threading.Condition
variables. As I analyzed my test cases, and threading.py, I started
suspecting thread scheduling. I then wrote the test case in my email,
which does not rely on the threading module at all. The point of the
test is not to maintain counter -- it's to show that sometimes even
after one thread completes, the other thread never is scheduled
again. This seems wrong. Try running the code, and let me see if you
see this behavior.

If you'd like, replace this:

counter += 1

by this:

time.sleep(0.000001 * id)

You should see the same problem. So that removes counter from the
picture. And the two increments of done (one by each thread) are still
almost certainly not going to coincide and cause a problem. Also, if
you look at the output from the code on a hang, you will see that
'thread X: leaving' only prints once. This has nothing to do with what
happens with the done variable.

Jack