mypy daemon consumes an increasing amount of memory every time `run` or `recheck` is invoked
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Description
Bug Report
The amount of memory that the daemon process consumes doesn't drop when typing errors are fixed; the memory consumption appears to stay the same if there are no errors, and when more errors appear, the memory consumption just continues increasing.
This is problematic when running the daemon on initially untyped code bases with large amounts of typing errors (as usually done in code editors integrating with a type-checker), as dmypy becomes sluggish very quickly (because the same existing errors are repeatedly reported).
To Reproduce & Actual Behaviour
-
Repeat this line 2000 times in a file
project/test/__init__.py,aaaaaaaaaaaaaaaaaaaaaaaaand create the following mypy configuration file at
project/mypy.ini[mypy] files = test/ -
Navigate to
project/, then rundmypy run > errors.txtmultiple times without editingproject/test/__init__.py; watch the memory consumption grow for thedmypyprocess. -
Delete all code in
project/test/__init__.py, then rundmypy runagain multiple times. The memory consumption does not decrease.
Expected Behavior
I expect the memory consumption to be proportional to the number of errors, AST nodes, and size of a cache diff since the last time the checked code files have changed. If there's no code changes, it's surprising to me that memory consumption would grow for just repeated reports of the same errors.
Your Environment
- Mypy version used: 1.17.1
- Mypy command-line flags: None
- Mypy configuration options from
mypy.ini(and other config files): See# project/mypy.ini - Operating system: Ubuntu (Pop!_OS) 22.04 LTS
- Python version used: 3.11
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
Reproduce the issue from project/test/init.py using project/mypy.ini, then invoke dmypy run and recheck repeatedly while observing daemon memory. Compare behavior with the repeated errors removed; done means memory no longer grows from repeated reports and decreases when errors and AST nodes are removed, with regression coverage for the scenario.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- tooling
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100