[issue3060] Warn about tuple parameters

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

Why not warn in the AST, like for the other syntax-related changes?
The relevant location is ast_for_arguments, line 680 in current SVN.

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[issue2349] Py3K warn against assigning to True/False

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

Hmm, I'd even go a step further and factor out the whole checking for
invalid/warnable names, like in Py3k's forbidden_name.

Also the warning text shouldn't start with uppercase and end in a full stop.

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[issue3060] Warn about tuple parameters

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

Also a test is missing.

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[issue3056] Simplify the Integral ABC

[Raymond Hettinger]

Raymond Hettinger <[EMAIL PROTECTED]> added the comment:

Is the patch good to go?

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[issue3061] time.strftime() always decodes result with UTF-8

[Georg Brandl]

New submission from Georg Brandl <[EMAIL PROTECTED]>:

It decodes the system strftime's result using TZNAME_ENCODING which is
also used to decode timezone names.  This may be correct for timezone
names themselves (I don't know), but the strftime result is encoded in
the LC_TIME encoding - at least on my Linux system.

--
assignee: loewis
messages: 67828
nosy: georg.brandl, loewis
priority: high
severity: normal
status: open
title: time.strftime() always decodes result with UTF-8
versions: Python 3.0

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[issue3028] tokenize module: normal lines, not "logical"

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

I got it wrong too at first; the "logical line" refers to the last tuple
item, the line string, not the line *number* passed.

It should now be clear as of r64037.

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status: open -> closed

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[issue3059] Removing .decode calls from Lib/calendar.py

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

Thanks, committed in r64033.

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[issue2523] binary buffered reading is quadratic

[Antoine Pitrou]

Antoine Pitrou <[EMAIL PROTECTED]> added the comment:

Thanks for the fixes.

By the way, I don't know much about non-blocking streams, but it seems
to me that "optimal" non-blocking read() would require that the chunks
we ask to the OS are block-aligned, which is not the case currently (we
use 2*avail, which can be an arbitrary value).

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[issue3062] Turtle speed() function has no effect under Mac OS X

[Pierre Bourdon]

New submission from Pierre Bourdon <[EMAIL PROTECTED]>:

When using the speed() function of the turtle module under Mac OS X, 
it has no effect : the turtle always draws lines with the same speed.

An easy fix is to replace line 553 of the turtle.py file 
by "sleep(self._delay / 1000.0)", however I don't know if it is the 
best solution.

--
components: Tkinter
messages: 67831
nosy: delroth
severity: normal
status: open
title: Turtle speed() function has no effect under Mac OS X
type: behavior
versions: Python 2.5

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[issue1350] IDLE - CallTips enhancement - show full doc-string in new window

[Tal Einat]

Changes by Tal Einat <[EMAIL PROTECTED]>:


Removed file: http://bugs.python.org/file8641/IDLE_CallTips.071028.patch

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[issue1350] IDLE - CallTips enhancement - show full doc-string in new window

[Tal Einat]

Changes by Tal Einat <[EMAIL PROTECTED]>:


Removed file: 
http://bugs.python.org/file8960/IDLE_CallTips.071214.incremental.patch

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[issue3028] tokenize module: normal lines, not "logical"

[Noam Raphael]

Noam Raphael <[EMAIL PROTECTED]> added the comment:

Can I suggest that you also add something like "The row indices in the
(row, column) tuples, however, are physical, and don't treat
continuation lines specially."?

It's just that it took me some time to understand your clarification,
since the row indices I thought the documentation talks about are also
tuple items, they just happen to be the first in the tuple, not the last.

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[issue3063] memory leak in random number generation

[Grant Tang]

New submission from Grant Tang <[EMAIL PROTECTED]>:

#the following code consume about 800M memory, which is normal
n = 1
data = [0.0 for i in xrange(n)]

#however, if I assign random number to data list, it will consume extra 
2.5G memory.
from random import random
for s in xrange(n):
data[i] = random()

#even if I delete data, only 800M memory released
del data

#call gc.collect() does not help, the extra 2.5G memory not released
import gc
gc.collect()

only when I quit Python, the memory is released. Same effect if I use 
random number generator from numpy. 
Same effect even if I just say data[i] = atpof("1.26")
I tried it in both Python 2.4 and 2.5 on linux 64bit and 32bit.

--
components: None
messages: 67833
nosy: gtang
severity: normal
status: open
title: memory leak in random number generation
type: resource usage
versions: Python 2.4, Python 2.5

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[issue3063] memory leak in random number generation

[Facundo Batista]

Facundo Batista <[EMAIL PROTECTED]> added the comment:

Confirmed the issue in the trunk right now:

(the number between square brackets point to the 'top' information below)

[EMAIL PROTECTED]:~/devel/reps/python/trunk$ ./python 
Python 2.6a3+ (trunk:64009, Jun  7 2008, 09:51:56) 
[GCC 4.2.3 (Ubuntu 4.2.3-2ubuntu7)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
[1]
>>> data = [0.0 for i in xrange(1)]
[2]
>>> from random import random
>>> for i in xrange(1):
... data[i] = random()
... 
>>> 
[3]


The memory consumption:

 PID USER  PR  NI  VIRT  RES  SHR S %CPU %MEMTIME+  COMMAND
[1] 4054 facundo   20   0  5032 3264 1796 S  0.0  0.2   0:00.02 python
[2] 4054 facundo   20   0  414m 384m 1888 S  0.0 19.1   0:17.72 python
[3] 4054 facundo   20   0 1953m 1.4g 1952 S  0.0 70.7   1:01.40 python

--
nosy: +facundobatista
versions: +Python 2.6 -Python 2.4, Python 2.5

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[issue3063] memory leak in random number generation

[Tim Peters]

Tim Peters <[EMAIL PROTECTED]> added the comment:

Strongly doubt this has anything to do with random number generation. 
Python maintains a freelist for float objects, which is both unbounded
and immortal.  Instead of doing "data[i] = random()", do, e.g., "data[i]
= float(s)", and I bet you'll see the same behavior.  That is, whenever
you create a number of distinct float objects simultaneously alive, the
space they occupy is never released (although it is available to be
reused for other float objects).  The use of random() here simply
creates a large number of distinct float objects simultaneously alive.

--
nosy: +tim_one

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[issue3063] memory leak in random number generation

[Grant Tang]

Grant Tang <[EMAIL PROTECTED]> added the comment:

I agree with Tim's comment. The problem's why these floats keep alive 
even after random() call returns. Then this becomes a garbage 
collection issue?

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[issue3063] memory leak in random number generation

[Tim Peters]

Tim Peters <[EMAIL PROTECTED]> added the comment:

They stayed alive simultaneously because you stored 100 million of them
simultaneously in a list (data[]).  If instead you did, e.g.,

for i in xrange(1):
x = random()

the problem would go away -- then only two float objects are
simultaneously alive at any given time (the "old" float in `x` stays
alive until the "new" float created by random() replaces it).

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[issue3063] memory leak in random number generation

[Grant Tang]

Grant Tang <[EMAIL PROTECTED]> added the comment:

Here I am confused. 100million floats in a list takes about 800M byte 
memory. This is acceptable. 

for i in xrange(1):
data[i] = random()

so it should be 800M plus a float returned by random(). But the problem 
is after this loop, except 800M bytes list, another >2G memory is 
occupied. And delete data list and call gc.collect() does not release 
these memory. I think you mean there are lots of floats used in random
() call, they should be released after random() returned.

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[issue3063] memory leak in random number generation

[Facundo Batista]

Facundo Batista <[EMAIL PROTECTED]> added the comment:

So, 0.0 would be cached, and the 414m+384m would be from the list
itself, right? I tried,

>>> data = [(1.0/i) for i in xrange(1,1)]

And the memory consumption was the big one.

Grant, the 800 MB is taken by ONE 0.0, and a list of zillion positions.

Furthermore, I did:

>>> for x in xrange(1):
... i = random()

And the memory didn't increase.

Grant, take note that there's no gc issue, the numbers stay alive
because the list itself is pointing to them.

Closing this as invalid.

--
resolution:  -> invalid
status: open -> closed

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[issue2349] Py3K warn against assigning to True/False

[Benjamin Peterson]

Benjamin Peterson <[EMAIL PROTECTED]> added the comment:

Here's a much better patch that delegates checking to a helper.

Added file: http://bugs.python.org/file10551/bool_assign7.patch

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[issue3063] memory leak in random number generation

[Grant Tang]

Grant Tang <[EMAIL PROTECTED]> added the comment:

Facundo:

I understand now. You mean every unique float number used will be an object
in memory. And never been released until Python quit. Is there any way to
reclaim these memory? We need 3G memory to create a list of 100million
randum numbers.

Thank you very much,
Grant

On Sun, Jun 8, 2008 at 11:59 AM, Facundo Batista <[EMAIL PROTECTED]>
wrote:

>
> Facundo Batista <[EMAIL PROTECTED]> added the comment:
>
> So, 0.0 would be cached, and the 414m+384m would be from the list
> itself, right? I tried,
>
> >>> data = [(1.0/i) for i in xrange(1,1)]
>
> And the memory consumption was the big one.
>
> Grant, the 800 MB is taken by ONE 0.0, and a list of zillion positions.
>
> Furthermore, I did:
>
> >>> for x in xrange(1):
> ... i = random()
>
> And the memory didn't increase.
>
> Grant, take note that there's no gc issue, the numbers stay alive
> because the list itself is pointing to them.
>
> Closing this as invalid.
>
> --
> resolution:  -> invalid
> status: open -> closed
>
> ___
> Python tracker <[EMAIL PROTECTED]>
> 
> ___
>

Added file: http://bugs.python.org/file10552/unnamed

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___Facundo:
 
I understand now. You mean every unique float number used will be an 
object in memory. And never been released until Python quit. Is there any way 
to reclaim these memory? We need 3G memory to create a list of 100million 
randum numbers.

 
Thank you very much,
Grant
On Sun, Jun 8, 2008 at 11:59 AM, Facundo Batista 
[EMAIL PROTECTED]> wrote:

Facundo Batista [EMAIL PROTECTED]> added the comment:So, 0.0 
would be cached, and the 414m+384m would be from the list
itself, right? I tried,>>> data = [(1.0/i) for i in 
xrange(1,1)]And the memory consumption was the big 
one.Grant, the 800 MB is taken by ONE 0.0, and a list of zillion 
positions.
Furthermore, I did:>>> for x in xrange(1):... 
    i = random()And the memory didn't 
increase.Grant, take note that there's no gc issue, the numbers 
stay alivebecause the list itself is pointing to them.
Closing this as invalid.--resolution:  -> 
invalidstatus: open -> closed


___Python 
tracker [EMAIL 
PROTECTED]>http://bugs.python.org/issue3063>
___-- Grant Tang 
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[issue3060] Warn about tuple parameters

[Benjamin Peterson]

Benjamin Peterson <[EMAIL PROTECTED]> added the comment:

> Why not warn in the AST, like for the other syntax-related changes?

because I was reading through symtable.c at the time. :)

Anyway, here's a better patch.

Added file: http://bugs.python.org/file10553/tuple_parameters_warn2.patch

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[issue3063] memory leak in random number generation

[Facundo Batista]

Facundo Batista <[EMAIL PROTECTED]> added the comment:

Grant,

A float takes 64 bits. 100 million floats take 800 MB, *just* the
floats. You're also building a list of 100 million places.

Maybe you shouldn't be building this structure in memory?

In any case, you should raise this issue in comp.lang.python, to get advice.

Regards,

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[issue3063] memory leak in random number generation

[Tim Peters]

Tim Peters <[EMAIL PROTECTED]> added the comment:

Float objects also require, as do all Python objects, space to hold a
type pointer and a reference count.  So each float object requires at
least 16 bytes (on most 32-bit boxes, 4 bytes for the type pointer, 4
bytes for the refcount, + 8 bytes for the float).  So 100 million float
objects requires at least 1.6 billion bytes.

It is a gc issue in the sense that the float-object free-list is both
unbounded and immortal.  For that matter, so is the int-object
free-list.  This has been discussed many times over the years on
python-dev, but nobody yet has a thoroughly attractive alternative.

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[issue3060] Warn about tuple parameters

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

Replace "upacking" with "unpacking" and you can commit it :)

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[issue2349] Py3K warn against assigning to True/False

[Georg Brandl]

Georg Brandl <[EMAIL PROTECTED]> added the comment:

The macro at the top of the patch should be removed, then this can be
checked in.

--
resolution:  -> accepted

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[issue2911] rewrite test_struct as a unittest

[Giampaolo Rodola']

Giampaolo Rodola' <[EMAIL PROTECTED]> added the comment:

In attachment. All existing tests are unchanged.
All tests passed on Windows XP sp3 and Linux Ubuntu Breezie both
equipped with Python-2.6a3.

--
keywords: +patch
nosy: +giampaolo.rodola
Added file: http://bugs.python.org/file10554/test_struct.py.diff

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[issue2053] IDLE - standardize dialogs

[Tal Einat]

Tal Einat <[EMAIL PROTECTED]> added the comment:

After more testing, I discovered a bug which broke Goto Line. Attaching
a fixed patch.

Added file: 
http://bugs.python.org/file10555/IDLE_standardize_dialogs.080609.patch

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[issue2053] IDLE - standardize dialogs

[Tal Einat]

Changes by Tal Einat <[EMAIL PROTECTED]>:


Removed file: 
http://bugs.python.org/file10555/IDLE_standardize_dialogs.080609.patch

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[issue2053] IDLE - standardize dialogs

[Tal Einat]

Changes by Tal Einat <[EMAIL PROTECTED]>:


Added file: 
http://bugs.python.org/file10556/IDLE_standardize_dialogs.080609.patch

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[issue2349] Py3K warn against assigning to True/False

[Benjamin Peterson]

Benjamin Peterson <[EMAIL PROTECTED]> added the comment:

Done in r64044.

--
resolution: accepted -> fixed
status: open -> closed

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[issue3060] Warn about tuple parameters

[Benjamin Peterson]

Benjamin Peterson <[EMAIL PROTECTED]> added the comment:

Done with r64045.

--
resolution:  -> fixed
status: open -> closed

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[issue2874] Remove use of the stat module in the stdlib

[Benjamin Peterson]

Benjamin Peterson <[EMAIL PROTECTED]> added the comment:

Can't you just inherit PyStructSequence with tp_base?

--
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[issue2876] Write UserDict fixer for 2to3

[Benjamin Peterson]

Changes by Benjamin Peterson <[EMAIL PROTECTED]>:


--
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[issue2775] Implement PEP 3108

[Benjamin Peterson]

Changes by Benjamin Peterson <[EMAIL PROTECTED]>:


--
dependencies:  -Remove cl usage from aifc, Write UserDict fixer for 2to3

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[issue3064] new turtle module for Python 3.0

[Gregor Lingl]

New submission from Gregor Lingl <[EMAIL PROTECTED]>:

turtle3.zip contains the port of the new turtle module (including demo
viewer and demo scripts) to Python 3.0 . One demo script has been added
(tdemo_forest.py)

It has been tested under Windows/MacOsX/Linux without showing up any
problems. 

I've done a few small changes to the API - as proposed in issue 1513695
- which are described in the docfile. 

Gregor Lingl

--
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files: turtle3.zip
messages: 67852
nosy: gregorlingl, loewis
severity: normal
status: open
title: new turtle module for Python 3.0
type: feature request
versions: Python 3.0
Added file: http://bugs.python.org/file10557/turtle3.zip

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[issue3065] Fix pickling bug of collections.namedtuple

[Alexandre Vassalotti]

New submission from Alexandre Vassalotti <[EMAIL PROTECTED]>:

There is currently a pickling bug in the namedtuple factory:

  >>> from collections import namedtuple
  >>> MemoRecord = namedtuple("MemoRecord", "key, msg")
  >>> m = MemoRecord(1,"hello")
  >>> import pickle
  >>> pickle.loads(pickle.dumps(m))
  Traceback (most recent call last):
...
  TypeError: __new__() takes exactly 3 positional arguments (2 given)

The bug is due to the fact that classes created by namedtuple don't
handle the __new__ arguments in the same fashion as tuple.__new__. The
fix is simply to define __getnewargs__.

--
assignee: rhettinger
components: Library (Lib)
files: fix_namedtuple_pickling.patch
keywords: patch, patch
messages: 67853
nosy: alexandre.vassalotti, rhettinger
priority: normal
severity: normal
status: open
title: Fix pickling bug of collections.namedtuple
type: behavior
versions: Python 2.6, Python 3.0
Added file: http://bugs.python.org/file10558/fix_namedtuple_pickling.patch

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[issue3065] Fix pickling bug of collections.namedtuple

[Raymond Hettinger]

Changes by Raymond Hettinger <[EMAIL PROTECTED]>:


--
priority: normal -> high

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[issue2983] Ttk support for Tkinter

[Kevin Walzer]

Changes by Kevin Walzer <[EMAIL PROTECTED]>:


--
nosy: +wordtech

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[issue3065] Fix pickling bug of collections.namedtuple

[Raymond Hettinger]

Raymond Hettinger <[EMAIL PROTECTED]> added the comment:

Georg, this works fine in Py2.6 but not in Py3.0.  Do you know what 
changed and whether other pickles will fail?

--
assignee: rhettinger -> georg.brandl
nosy: +georg.brandl
versions:  -Python 2.6

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[issue2618] Tile module: Add support for themed widgets

[Kevin Walzer]

Kevin Walzer <[EMAIL PROTECTED]> added the comment:

I would like to close this feature request in favor of 
http://bugs.python.org/issue2983. That project achieves the same goal as 
this code submission in a more comprehensive, better-documented fashion.

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[issue3065] Fix pickling bug of collections.namedtuple

[Raymond Hettinger]

Raymond Hettinger <[EMAIL PROTECTED]> added the comment:

Found it.  Py3.0 uses protocol 2 by default and that protocol has a 
different set of calls.

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versions: +Python 2.6

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[issue2618] Tile module: Add support for themed widgets

[Benjamin Peterson]

Changes by Benjamin Peterson <[EMAIL PROTECTED]>:


--
resolution:  -> duplicate
status: open -> closed
superseder:  -> Ttk support for Tkinter

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[issue3064] new turtle module for Python 3.0

[Benjamin Peterson]

Changes by Benjamin Peterson <[EMAIL PROTECTED]>:


--
assignee:  -> loewis

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[issue3065] Fix pickling bug of collections.namedtuple

[Raymond Hettinger]

Raymond Hettinger <[EMAIL PROTECTED]> added the comment:

Fixed in r64047.
Thanks for the submission.

--
assignee: georg.brandl -> rhettinger
resolution:  -> fixed
status: open -> closed

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[issue3042] Add PEP 8 compliant aliases to threading module

[Nick Coghlan]

Nick Coghlan <[EMAIL PROTECTED]> added the comment:

I'd still be inclined to put a @wraps(meth) decorator on the definition
of the wrapper function (and then override to the supplied name
afterwards) - remember that functools.wraps is a decorator factory
rather than a decorator itself. 

That would ensure that any docstrings and the like would be preserved
(granted, it appears the threading module currently doesn't *have* any
docstrings, but it would still be better to write the wrapping code
correctly).

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[issue2138] Add a factorial function

[Raymond Hettinger]

Raymond Hettinger <[EMAIL PROTECTED]> added the comment:

Added math.factorial() in r64050.

--
resolution:  -> accepted
status: open -> closed

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