Ubuntu
freeloader package

Trying on jamendo to download an album with bittorrent

Bug #68138 reported by JIPI
4
Affects Status Importance Assigned to Milestone
freeloader (Ubuntu)
Invalid
Medium
Unassigned
pygtk (Ubuntu)
Invalid
Undecided
Unassigned

Bug Description

I get
ProblemType: Crash
CrashCounter: 1
Date: Wed Oct 25 10:32:55 2006
Dependencies:
 libsepol1 1.12-1
 dpkg 1.13.22ubuntu7
 libattr1 2.4.32-1ubuntu1
 python2.4-minimal 2.4.4~c1-0ubuntu1
 tzdata 2006m-1ubuntu1
 coreutils 5.96-5ubuntu4
 libacl1 2.2.39-1ubuntu2
 zlib1g 1:1.2.3-13ubuntu2
 belocs-locales-bin 2.4-1ubuntu6
 libc6 2.4-1ubuntu12
 libselinux1 1.30-1ubuntu1
 locales 2.3.22
Disassembly:
 (no debugging symbols found)
 Using host libthread_db library "/lib/tls/i686/cmov/libthread_db.so.1".
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 Core was generated by `python /usr/bin/freeloader /tmp/Greg Baumont - Wood -- Jamendo - OGG Vorbis q8'.
 Program terminated with signal 11, Segmentation fault.
 #0 0x0807c966 in PyDict_SetItem ()
 Dump of assembler code from 0x807c966 to 0x807c986:
 0x0807c966 <PyDict_SetItem+86>: addl $0x1,(%eax)
 0x0807c969 <PyDict_SetItem+89>: addl $0x1,(%esi)
 0x0807c96c <PyDict_SetItem+92>: mov %eax,(%esp)
 0x0807c96f <PyDict_SetItem+95>: mov %edi,%eax
 0x0807c971 <PyDict_SetItem+97>: call 0x807aeb0 <PyLong_FromDouble+11200>
 0x0807c976 <PyDict_SetItem+102>: mov 0xc(%edi),%ecx
 0x0807c979 <PyDict_SetItem+105>: cmp %ecx,%ebx
 0x0807c97b <PyDict_SetItem+107>: jge 0x807c9b3 <PyDict_SetItem+163>
 0x0807c97d <PyDict_SetItem+109>: mov 0x8(%edi),%edx
 0x0807c980 <PyDict_SetItem+112>: mov 0x10(%edi),%eax
 0x0807c983 <PyDict_SetItem+115>: lea (%edx,%edx,2),%edx
 End of assembler dump.
DistroRelease: Ubuntu 6.10
ExecutablePath: /usr/bin/python
InterpreterPath: /usr/bin/python2.4
Package: python-minimal 2.4.3-11ubuntu3
ProcCmdline: python /usr/bin/freeloader /tmp/Greg\ Baumont\ -\ Wood\ --\ Jamendo\ -\ OGG\ Vorbis\ q8\ -\ 2005.07.26\ [www.jamendo.com]-1.torrent
ProcCwd: /home/jp
ProcEnviron:
 SHELL=/bin/bash
 PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/bin/X11:/usr/games
 LANG=fr_FR.UTF-8
 LANGUAGE=fr_FR:fr:en_GB:en
ProcMaps:
 08048000-08121000 r-xp 00000000 03:02 422840 /usr/bin/python2.4
 08121000-08142000 rw-p 000d8000 03:02 422840 /usr/bin/python2.4
 08142000-08169000 rw-p 08142000 00:00 0 [heap]
 b7da8000-b7dea000 rw-p b7da8000 00:00 0
 b7dea000-b7f17000 r-xp 00000000 03:02 162210 /lib/tls/i686/cmov/libc-2.4.so
 b7f17000-b7f19000 r--p 0012c000 03:02 162210 /lib/tls/i686/cmov/libc-2.4.so
 b7f19000-b7f1b000 rw-p 0012e000 03:02 162210 /lib/tls/i686/cmov/libc-2.4.so
 b7f1b000-b7f1e000 rw-p b7f1b000 00:00 0
 b7f1e000-b7f42000 r-xp 00000000 03:02 162214 /lib/tls/i686/cmov/libm-2.4.so
 b7f42000-b7f44000 rw-p 00023000 03:02 162214 /lib/tls/i686/cmov/libm-2.4.so
 b7f44000-b7f46000 r-xp 00000000 03:02 162229 /lib/tls/i686/cmov/libutil-2.4.so
 b7f46000-b7f48000 rw-p 00001000 03:02 162229 /lib/tls/i686/cmov/libutil-2.4.so
 b7f48000-b7f49000 rw-p b7f48000 00:00 0
 b7f49000-b7f4b000 r-xp 00000000 03:02 162213 /lib/tls/i686/cmov/libdl-2.4.so
 b7f4b000-b7f4d000 rw-p 00001000 03:02 162213 /lib/tls/i686/cmov/libdl-2.4.so
 b7f4d000-b7f5c000 r-xp 00000000 03:02 162224 /lib/tls/i686/cmov/libpthread-2.4.so
 b7f5c000-b7f5e000 rw-p 0000f000 03:02 162224 /lib/tls/i686/cmov/libpthread-2.4.so
 b7f5e000-b7f60000 rw-p b7f5e000 00:00 0
 b7f7c000-b7f7e000 rw-p b7f7c000 00:00 0
 b7f7e000-b7f97000 r-xp 00000000 03:02 1133461 /lib/ld-2.4.so
 b7f97000-b7f99000 rw-p 00018000 03:02 1133461 /lib/ld-2.4.so
 bfa4a000-bfa60000 rw-p bfa4a000 00:00 0 [stack]
 ffffe000-fffff000 ---p 00000000 00:00 0 [vdso]
ProcStatus:
 Name: python
 State: D (disk sleep)
 SleepAVG: 78%
 Tgid: 12323
 Pid: 12323
 PPid: 12231
 TracerPid: 0
 Uid: 1000 1000 1000 1000
 Gid: 1000 1000 1000 1000
 FDSize: 256
 Groups: 4 20 24 25 29 30 44 46 106 110 112 1000
 VmPeak: 3124 kB
 VmSize: 3120 kB
 VmLck: 0 kB
 VmHWM: 1556 kB
 VmRSS: 1556 kB
 VmData: 452 kB
 VmStk: 88 kB
 VmExe: 868 kB
 VmLib: 1524 kB
 VmPTE: 12 kB
 Threads: 1
 SigQ: 0/4294967295
 SigPnd: 0000000000000000
 ShdPnd: 0000000000000000
 SigBlk: 0000000000000000
 SigIgn: 0000000020001000
 SigCgt: 0000000180000000
 CapInh: 0000000000000000
 CapPrm: 0000000000000000
 CapEff: 0000000000000000
 Cpus_allowed: ff
 Mems_allowed: 1
Registers:
 (no debugging symbols found)
 Using host libthread_db library "/lib/tls/i686/cmov/libthread_db.so.1".
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 Core was generated by `python /usr/bin/freeloader /tmp/Greg Baumont - Wood -- Jamendo - OGG Vorbis q8'.
 Program terminated with signal 11, Segmentation fault.
 #0 0x0807c966 in PyDict_SetItem ()
 eax 0x0 0
 ecx 0x7957ad87 2035789191
 edx 0xb7db3f40 -1210368192
 ebx 0x17 23
 esp 0xbfa5cfc0 0xbfa5cfc0
 ebp 0xbfa5cfd8 0xbfa5cfd8
 esi 0xb7db3f40 -1210368192
 edi 0xb7dab79c -1210402916
 eip 0x807c966 0x807c966 <PyDict_SetItem+86>
 eflags 0x210217 [ CF PF AF IF RF ID ]
 cs 0x73 115
 ss 0x7b 123
 ds 0x7b 123
 es 0xc010007b -1072693125
 fs 0x0 0
 gs 0x33 51
Signal: 11
SourcePackage: python-defaults
Stacktrace:
 (no debugging symbols found)
 Using host libthread_db library "/lib/tls/i686/cmov/libthread_db.so.1".
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 Core was generated by `python /usr/bin/freeloader /tmp/Greg Baumont - Wood -- Jamendo - OGG Vorbis q8'.
 Program terminated with signal 11, Segmentation fault.
 #0 0x0807c966 in PyDict_SetItem ()
 #0 0x0807c966 in PyDict_SetItem ()
 No symbol table info available.
 #1 0x0807ca52 in PyDict_SetItemString ()
 No symbol table info available.
 #2 0x080df9d9 in _PySys_Init ()
 No symbol table info available.
 #3 0x080de79d in Py_InitializeEx ()
 No symbol table info available.
 #4 0x080ded52 in Py_Initialize ()
 No symbol table info available.
 #5 0x08055527 in Py_Main ()
 No symbol table info available.
 #6 0x08055132 in main ()
 No symbol table info available.
ThreadStacktrace:
 (no debugging symbols found)
 Using host libthread_db library "/lib/tls/i686/cmov/libthread_db.so.1".
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 (no debugging symbols found)
 Core was generated by `python /usr/bin/freeloader /tmp/Greg Baumont - Wood -- Jamendo - OGG Vorbis q8'.
 Program terminated with signal 11, Segmentation fault.
 #0 0x0807c966 in PyDict_SetItem ()
 .
 Thread 1 (process 12323):
 #0 0x0807c966 in PyDict_SetItem ()
 No symbol table info available.
 #1 0x0807ca52 in PyDict_SetItemString ()
 No symbol table info available.
 #2 0x080df9d9 in _PySys_Init ()
 No symbol table info available.
 #3 0x080de79d in Py_InitializeEx ()
 No symbol table info available.
 #4 0x080ded52 in Py_Initialize ()
 No symbol table info available.
 #5 0x08055527 in Py_Main ()
 No symbol table info available.
 #6 0x08055132 in main ()
 No symbol table info available.
Uname: Linux jp-laptop 2.6.17-10-generic #2 SMP Fri Oct 13 18:45:35 UTC 2006 i686 GNU/Linux
CoreDump: base64
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Revision history for this message
Daniel Holbach (dholbach) wrote :
Download full text (5.1 KiB)

Debug backtrace:

--- stack trace ---
Using host libthread_db library "/lib/tls/i686/cmov/libthread_db.so.1".
Core was generated by `python /usr/bin/freeloader /tmp/Greg Baumont - Wood -- Jamendo - OGG Vorbis q8'.
Program terminated with signal 11, Segmentation fault.
#0 PyDict_SetItem (op=0xb7dab79c, key=0xb7db3f40, value=0x0) at ../Objects/dictobject.c:587
 in ../Objects/dictobject.c
#0 PyDict_SetItem (op=0xb7dab79c, key=0xb7db3f40, value=0x0) at ../Objects/dictobject.c:587
 mp = <value optimized out>
 hash = 2035789191
 n_used = 23
#1 0x0807ca52 in PyDict_SetItemString (v=0xb7dab79c, key=0x8119f46 "stdout", item=0x0) at ../Objects/dictobject.c:2026
 kv = (PyObject *) 0xb7db3f40
 err = -1
#2 0x080df9d9 in _PySys_Init () at ../Python/sysmodule.c:988
 sb = {st_dev = 13, __pad1 = 0, __st_ino = 4856, st_mode = 8630, st_nlink = 1, st_uid = 0, st_gid = 0, st_rdev = 259, __pad2 = 0, st_size = 0,
  st_blksize = 4096, st_blocks = 0, st_atim = {tv_sec = 1161634156, tv_nsec = 0}, st_mtim = {tv_sec = 1161634156, tv_nsec = 0}, st_ctim = {tv_sec = 1161754515,
    tv_nsec = 457454500}, st_ino = 4856}
 m = (PyObject *) 0xb7da9074
 v = <value optimized out>
 sysdict = (PyObject *) 0xb7dab79c
 sysin = (PyObject *) 0xb7db6020
 sysout = (PyObject *) 0x0
 syserr = (PyObject *) 0xb7db6068
#3 0x080de79d in Py_InitializeEx (install_sigs=1) at ../Python/pythonrun.c:192
 interp = (PyInterpreterState *) 0x8148170
 tstate = (PyThreadState *) 0x81481b0
 bimod = <value optimized out>
 sysmod = <value optimized out>
 p = <value optimized out>
 codeset = <value optimized out>
 saved_locale = <value optimized out>
 sys_stream = <value optimized out>
 sys_isatty = <value optimized out>
#4 0x080ded52 in Py_Initialize () at ../Python/pythonrun.c:287
No locals.
#5 0x08055527 in Py_Main (argc=3, argv=0xbfa5d4b4) at ../Modules/main.c:427
 sb = {st_dev = 770, __pad1 = 0, __st_ino = 425492, st_mode = 33261, st_nlink = 1, st_uid = 0, st_gid = 0, st_rdev = 0, __pad2 = 0, st_size = 39704,
  st_blksize = 4096, st_blocks = 80, st_atim = {tv_sec = 1161765174, tv_nsec = 0}, st_mtim = {tv_sec = 1151058708, tv_nsec = 0}, st_ctim = {tv_sec = 1161681945,
    tv_nsec = 0}, st_ino = 425492}
 c = <value optimized out>
 sts = <value optimized out>
 command = 0x0
 filename = 0xbfa5eb99 "/usr/bin/freeloader"
 module = 0x0
 fp = (FILE *) 0x8148008
 p = <value optimized out>
 inspect = 0
 unbuffered = 0
 skipfirstline = 0
 stdin_is_interactive = 0
 help = 0
 version = 0
 saw_inspect_flag = 0
 saw_unbuffered_flag = 0
 cf = {cf_flags = 0}
#6 0x08055132 in main (argc=) at ../Modules/python.c:23
No locals.
--- thread stack trace ---
Using host libthread_db library "/lib/tls/i686/cmov/libthread_db.so.1".
Core was generated by `python /usr/bin/freeloader /tmp/Greg Baumont - Wood -- Jamendo - OGG Vorbis q8'.
Program terminated with signal 11, Segmentation fault.
#0 PyDict_SetItem (op=0xb7dab79c, key=0xb7db3f40, value=0x0) at ../Objects/dictobject.c:587
 in ../Objects/dictobject.c
.
Thread 1 (process 12323):
#0 PyDict_SetItem (op=0xb7dab79c, key=0xb7db3f40, value=0x0) at ../Objects/dictobject.c:587
 mp = <value optimized out>
 hash = 2035789191
 n_used = 23
#1 0x0807ca52 in PyDict_SetItemStr...

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Revision history for this message
Daniel Holbach (dholbach) wrote :

Is this still a problem?

Changed in pygtk:
status: Unconfirmed → Needs Info
Revision history for this message
Sebastien Bacher (seb128) wrote :

not a pygtk bug

Changed in pygtk:
status: Needs Info → Rejected
Daniel T Chen (crimsun)
Changed in freeloader:
importance: Undecided → Medium
status: New → Incomplete
Revision history for this message
Javier Jardón (jjardon) wrote :

We are closing this bug report because it lacks the information we need to investigate the problem, as described in the previous comments. Please reopen it if you can give us the missing information, and don't hesitate to submit bug reports in the future. To reopen the bug report you can click on the current status, under the Status column, and change the Status back to "New". Thanks again!

Changed in freeloader:
status: Incomplete → Invalid
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