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Interrupt Does Not Work

See original GitHub issue

Issue Type: Bug

Load large TSV of tweets (~3 million rows) into a pandas dataframe.
Convert dataframe to json object using “records” orientation.
Attempt to hit “Interrupt” on top barline, or on the left of the cell.

Nothing happens, the process is not interrupted, even if I close the file, even if I try to restart the kernel, etc.

The process continues to run with no way to kill it reliably or easily.

Extension version: 2021.9.1101343141 VS Code version: Code 1.61.2 (6cba118ac49a1b88332f312a8f67186f7f3c1643, 2021-10-19T15:49:28.381Z) OS version: Darwin x64 18.7.0 Restricted Mode: No Remote OS version: Linux x64 5.0.0-37-generic Remote OS version: Linux x64 5.0.0-37-generic Remote OS version: Linux x64 5.0.0-37-generic

System Info

Item	Value
CPUs	Intel® Core™ i7-8850H CPU @ 2.60GHz (12 x 2600)
GPU Status	2d_canvas: enabled gpu_compositing: enabled metal: disabled_off multiple_raster_threads: enabled_on oop_rasterization: enabled opengl: enabled_on rasterization: enabled skia_renderer: disabled_off_ok video_decode: enabled webgl: enabled webgl2: enabled
Load (avg)	2, 2, 2
Memory (System)	16.00GB (4.18GB free)
Process Argv	-psn_0_663714 --crash-reporter-id c3a0488e-aaab-4775-adee-2d25a70366d9
Screen Reader	no
VM	0%

Item	Value
Remote	SSH: lambda2.cs.ucla.edu
OS	Linux x64 5.0.0-37-generic
CPUs	Intel® Core™ i9-9960X CPU @ 3.10GHz (32 x 1200)
Memory (System)	125.58GB (119.28GB free)
VM	0%

Item	Value
Remote	SSH: lambda2.cs.ucla.edu
OS	Linux x64 5.0.0-37-generic
CPUs	Intel® Core™ i9-9960X CPU @ 3.10GHz (32 x 1200)
Memory (System)	125.58GB (119.28GB free)
VM	0%

Item	Value
Remote	SSH: lambda2.cs.ucla.edu
OS	Linux x64 5.0.0-37-generic
CPUs	Intel® Core™ i9-9960X CPU @ 3.10GHz (32 x 1200)
Memory (System)	125.58GB (119.28GB free)
VM	0%

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Issue Analytics

State:
Created 2 years ago
Comments:6 (3 by maintainers)

Top GitHub Comments

1reaction

davzamancommented, Oct 26, 2021

Yeah makes sense, thanks I appreciate the help! I’ll close the issue now.

0reactions

rchiodocommented, Oct 26, 2021

My guess is the only workaround to this is doing very limited prints / ensuring it’s not trying to generate so many UI components. Is that correct?

Not sure what the bandwidth limit is, but yes printing really really fast can cause this problem. You might try using some sort of progress bar instead? Tqdm might work?