Closed yongnuan closed 7 months ago
Please could you enable logging as follows:
Jupyter->Logging
verbose
Jupyter
output panel.Also please disabled all extensions except jupyter, python, notebook renderers, Also, does this make a difference with a smaller notebook. Please share logs for a small notebook.
Yes, especially when using remote-ssh
@zhong-yy in order to help you, please can you share the information requested above
Thanks Don for reaching out. Here are the output as you requested. Thanks for helping.
Based on the logs I do not see any delay,
Jupyter
)Let me know if you can still replicate this issue. If so, then please let me know what is slow, whether its execution or editing or the like, and based on the logs at what time were you experiencing the delays. From the logs, it seems cells get executed very quickly. Based on the logs the first 394 cells get executed in 15 seconds, thats 20 cells getting executed every second.
After that there's an error in one cell 394 and that seems to be taking time,
12:08:01.292 [info] End cell 394 execution after 24.445s, completed @ 1710353281289, started @ 1710353256844
So that cells seems to be whats taking long, unless you are experiencing other delays
@yongnuan You have sent two logs, whats the difference between the two, Did you experience delays in any one of them, if so, at what point in time and what was the delay in, was it execution, typing, etc..
Again, please disable all other extensions & hide the variable viewer.
Based on the logs you restarted the kernel at 12:39:29.403
and a minute later the kernel started 12:40:34.702
That is one whole minute to restart the kernel (this is very slow)
Please can you confirm whether this was the only delay or were there others?
12:39:29.403 [debug] Launching kernel .jvsc74a57bd0e536dccbbd01db8d8081495d3823c64c679deef15e1fcf4dabdbf5fb4a311b57.c:\ProgramData\anaconda_envs\dash2\python.exe.c:\ProgramData\anaconda_envs\dash2\python.exe.-m#ipykernel_launcher for \\test.com\test\users\<username>\Data\code_workplace\mydashboard\DTS_dashboard_v400_addwarmbacktimelist_addCHPheatmap_stackprodinterval_updatewelltype_stackplotunit_grossheatdts_newredrill_newseeq.ipynb in \\test.com\test\users\<username>\Data\code_workplace\mydashboard with ports 9003, 9000, 9006, 9004, 9005
12:39:29.405 [debug] Launching kernel .jvsc74a57bd0e536dccbbd01db8d8081495d3823c64c679deef15e1fcf4dabdbf5fb4a311b57.c:\ProgramData\anaconda_envs\dash2\python.exe.c:\ProgramData\anaconda_envs\dash2\python.exe.-m#ipykernel_launcher for \\test.com\test\users\<username>\Data\code_workplace\mydashboard\.ipynb_checkpoints\DTS_dashboard_v400_addwarmbacktimelist_addCHPheatmap_stackprodinterval_updatewelltype_stackplotunit_grossheatdts_newredrill_newseeq-checkpoint.ipynb in \\test.com\test\users\<username>\Data\code_workplace\mydashboard\.ipynb_checkpoints with ports 9011, 9010, 9014, 9012, 9013
12:39:37.058 [debug] Restart kernel command handler for \\test.com\test\users\<username>\Data\code_workplace\mydashboard\DTS_dashboard_v400_addwarmbacktimelist_addCHPheatmap_stackprodinterval_updatewelltype_stackplotunit_grossheatdts_newredrill_newseeq.ipynb
12:40:07.988 [info] Handle Execution of Cells 1,2,4,6,7,9,11,12,13,16,17,18,21,23,25,27,28,30,31,33,34,36,38,39,41,42,45,46,47,49,51,52,54,57,59,61,63,65,67,69,70,73,77,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,131,133,135,137,139,141,143,145,147,149,151,152,154,155,157,159,161,163,165,167,169,172,174,175,177,179,181,183,185,186,188,190,192,194,195,197,199,200,201,204,206,208,210,212,214,215,216,217,219,223,226,227,231,232,234,237,239,241,243,244,245,247,249,251,253,255,256,258,260,263,265,267,269,273,275,277,280,282,285,286,289,291,293,295,297,298,301,303,305,309,310,313,315,317,319,322,323,325,328,330,331,333,335,337,340,341,342,343,344,345,347,349,352,354,356,358,360,362,364,366,368,370,372,374,376,378,380,383,385,387,389,391,392,394,397,399,401,403,406,407,409,411,413,415,417,419,421,423,425,428,430,432,435,437,439,442,443,445,446,447,448,450,453,455,456,460,462,465,467,468,470,471,473,476,477,479,482,484,485,487,489,493,494,496,498,502,503,506,508,509,511,513,515,516,518,520,522,525,527,529,531,533,535,537,540,542,544,545,547,548,549,551 for \\test.com\test\users\<username>\Data\code_workplace\mydashboard\DTS_dashboard_v400_addwarmbacktimelist_addCHPheatmap_stackprodinterval_updatewelltype_stackplotunit_grossheatdts_newredrill_newseeq.ipynb
12:40:14.129 [debug] Conda file returned by Python Extension is C:\Anaconda3\Scripts\conda.exe
12:40:34.702 [debug] Got env vars with python c:\ProgramData\anaconda_envs\dash2\python.exe, with env var count 84 in 66140ms.
OK Thanks Don, I tried it again and disable all extensions. Here are my findings.
Case 2: with 5 other extensions enabled, first run after reloading vs code it took 6 min, 2nd run it toke 13min, which is very slow. still why 2nd run took double time?
14:38:57.930 [debug] Got env vars with python c:\ProgramData\anaconda_envs\dash2\python.exe, with env var count 84 in 58804ms.
Based on this, Python extension takes 1 minute to activate the conda environment. @yongnuan Please can you open an empty terminal and activate the above conda enviornment. Let me know how long it takes to activate the conda env in the empty terminal. By empty i mean, conda should not already be activated in that terminal. I would expect this to take a few seconds, at least a minute or so, however launching Jupyter from this environment in the terminal should be very fast (at least that is my expectation).
Please let me know.
Once again thanks for your patience and sharing the logs.
. However, 2nd run it toke 10min
How are you measuring this time? Is it the total time to open VS Code, open a notebook and then run all the cells,
Based on the logs,
14:3930
14:39:30.777 [info] Handle Execution of Cells 1,2,4,6...549,551 for \\test.com\test\users\<username>\Data\myworkplace\test_dashboard\test_dashboard_v400_addwarmbacktimelist_addCHPheatmap_stackprodinterval_updatewelltype_stackplotunit_grossheatdts_newredrill_newseeq.ipynb
14:40:23.702
14:40:23.702 [debug] Cell 551 executed successfully
I.e. VS Code was able to run the cell in under 1 minute, I'm not saying you are incorrect in stating that things are slow, but would like to understand how you measure the delay. As mentioned based on the logs I can definitely see delays in activating environments and the like. Please do let me know.
E.g. based on the last logs, VS Code starts at 14:37:57.163
and everything ends at 14:40:23.702
, thats still < 3 minutes, again agree there are definitely some delays that need to be improved.
Do you see this message everytime? Or did you see this just once? If you can repro this, then please do let me know
Hi Don, case 2 1st run log file was the previous log file I posted and you did made comments already before. Sorry I am done work day now. ThxSent from my iPhoneOn Mar 13, 2024, at 4:31 PM, Don Jayamanne @.***> wrote:
Case 2: with 5 other extensions enabled, first run after reloading vs code it took 6 min, 2nd run it toke 13min, which is very slow. still why 2nd run took double time?
Please can you share logs for this. Once again thanks for your patience and sharing the logs.
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you were mentioned.Message ID: @.***>
with 5 other extensions enabled, first run after reloading vs code it took 6 min, 2nd run it toke 13min, which is very slow. still why 2nd run took double time?
Please do share logs for this (when you get back), thanks
Hi Don, thanks, please see attached for the log of case 2 with all extensions enabled.
To answer your previous questions:
record the time difference, the time log in the output is not correct!
This would mean there's a delay in VS Code,
it showed windows is not responding, Do you see this message everytime? Or did you see this just once? -Answer: yes I saw it everytime. This morning when I came in and VS Code was opening from yesterday, when I tried t
@rebornix Any idea which of the options from this WIKI would help us gather more information for this https://github.com/microsoft/vscode/wiki/Performance-Issues#profiling-the-renderer-process
Do you still need any other information in order to troubleshooting the issue? Thanks
Yes, please can you check this link and provide the necessary logs https://github.com/microsoft/vscode/wiki/Performance-Issues#profiling-the-renderer-process
This issue has been closed automatically because it needs more information and has not had recent activity. See also our issue reporting guidelines.
Happy Coding!
Type: Performance Issue
Hi
When running a big jupyter notebook, it is still very slow. I found the first connection to kernel takes really long time before actually running each cell. For same notebook, It take only few seconds to run whe using jupyter lab. So jupyter lab is way much faster than VS Code now.
Could you please fix the issue?
Thanks
VS Code version: Code 1.87.0 (019f4d1419fbc8219a181fab7892ebccf7ee29a2, 2024-02-27T23:41:44.469Z) OS version: Windows_NT x64 10.0.19044 Modes:
System Info
|Item|Value| |---|---| |CPUs|Intel(R) Xeon(R) CPU E5-2690 v4 @ 2.60GHz (4 x 2600)| |GPU Status|2d_canvas: enabledcanvas_oop_rasterization: enabled_on
direct_rendering_display_compositor: disabled_off_ok
gpu_compositing: enabled
multiple_raster_threads: enabled_on
opengl: enabled_on
rasterization: enabled
raw_draw: disabled_off_ok
skia_graphite: disabled_off
video_decode: enabled
video_encode: enabled
vulkan: disabled_off
webgl: enabled
webgl2: enabled
webgpu: enabled| |Load (avg)|undefined| |Memory (System)|64.00GB (45.24GB free)| |Process Argv|| |Screen Reader|no| |VM|100%|
Process Info
``` CPU % Mem MB PID Process 2 143 18292 code main 1 104 1156 window [3] (Issue Reporter) 0 306 10180 window [1] (DTS_dashboard_new_v7.ipynb - analysis (Workspace) - Visual Studio Code) 0 99 10360 ptyHost 0 80 316 C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe 0 8 20472 conpty-agent 0 86 10740 fileWatcher [1] 0 167 11072 extensionHost [1] 0 17 10104 c:\ProgramData\anaconda_envs\dash2\python.exe c:\Users\yongnual\.vscode\extensions\ms-toolsai.jupyter-2024.1.1-win32-x64\pythonFiles\vscode_datascience_helpers\kernel_interrupt_daemon.py --ppid 11072 0 13 6036 C:\WINDOWS\system32\conhost.exe 0x4 0 1002 10116 electron-nodejs (bundle.js ) 0 305 10960 0 17 11124 "PicaVcHost.EXE" 0 49 13712 c:\ProgramData\anaconda_envs\dash2\python.exe c:\Users\yongnual\.vscode\extensions\ms-python.isort-2023.10.1\bundled\tool\lsp_server.py 0 13 17644 C:\WINDOWS\system32\conhost.exe 0x4 6 235 19408 electron-nodejs (eIISaX.js ) 0 13 16648 C:\WINDOWS\system32\conhost.exe 0x4 2 149 11120 gpu-process 0 127 16404 window 0 44 16712 utility-network-service 0 102 19856 shared-process ```Workspace Info
``` | Window (DTS_dashboard_new_v7.ipynb - analysis (Workspace) - Visual Studio Code) | Folder (analysis): 1266 files | File types: csv(607) parquet(480) pkl(61) xlsx(39) PNG(33) html(22) | png(8) xlsm(3) db(2) code-workspace(1) | Conf files:; ```Extensions (10)
Extension|Author (truncated)|Version ---|---|--- debugpy|ms-|2024.2.0 isort|ms-|2023.10.1 python|ms-|2024.2.1 vscode-pylance|ms-|2024.2.3 jupyter|ms-|2024.2.0 jupyter-keymap|ms-|1.1.2 jupyter-renderers|ms-|1.0.17 vscode-jupyter-cell-tags|ms-|0.1.8 vscode-jupyter-slideshow|ms-|0.1.5 html-related-links|rio|1.1.0