Reported slowness due in variable expansion
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 32/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- devtools, performance
Research direction
The issue names no file, test, or reproducible case. Start by tracing how debugpy handles variable presentation and expansion for very large values, then compare that behavior with the DAP lazy and indexedVariables mechanisms described here. Done means large variables no longer block debugger interaction or overwhelm clients.
Written by the indexing model from the issue text.
Description
Isidor pointed out a tweet that mentions
S Code’s debugger would lock up whenever I stepped past a line like: S=tensor.untyped_storage()... the debugger window that automatically displays local variables started a dump of over a billion elements from the debug server before it would process any other commands.
I have not attempted to repro myself, but there are a few ways in the debug protocol that cases like this can be handled:
- Set
lazy: trueon theVariablePresentationHints of potentially expensive variables so that they aren't expanded without user action - Use
indexedVariablesto allow the client to request a small number of a variable's contained data and page through it
Even if it's unavoidable that a giant variable's data is loaded into the debug adapter, it should use these mechanisms to avoid overloading clients and slowing down interaction on the protocol.
Let me know if there's anything I can help with from the VS Code side :)
- Dominant language
- Python
- Stars
- 2.5k
- Forks
- 202
- Avg merge
- 5d 1h
- Merged PRs (30d)
- 1
Contributor guide
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