`dmypy` - poor performance when a lot of possibly unrelated errors
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 20.6k
- Forks
- 3.3k
- PR merge metrics
- PR metrics pending
Description
Bug Report
The dmypy daemon will experience poor performance if there are a lot of files with errors, even if only a single file is updated.
To Reproduce
Create a ball of mud with errors. This script requires some tweaking to really bring out the issue but its a good starting point:
https://github.com/JamesHutchison/mypy/blob/dmypy-update-perf/ball_of_mud/generate_ball_of_mud.py
The performance deficit is proportionate to the number of failing files.
Expected Behavior
dmypy is always fast for small changes
Actual Behavior
dmypy is slow.
Your Environment
- Mypy version used: 0.991
Why is this important?
When converting a large repo to mypy you will have a lot of failing files at first and you cannot use --follow-imports=silent
Notes
The cause appears to be this code:
https://github.com/python/mypy/blob/master/mypy/server/update.py#L847
From what I can tell, it looks like dmypy relies on files failing their imports to know to revisit them later. This appears to also be the reason that you cannot use --follow-imports=silent with dmypy.
For example, when --follow-imports=error:
- File A is built, and File A imports file B. File A gets errors about B not existing.
- File B is built
- File A gets built again, but this time B is cached (or loaded, or whatever) and no longer fails import
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with mypy/server/update.py around line 847 and reproduce the slowdown using the ball_of_mud/generate_ball_of_mud.py script linked in the issue. Investigate why many failing files are revisited when only one file changes; done means dmypy remains fast for small changes despite unrelated errors, while preserving the relevant import behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- compilers
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100