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Top 13 Python Code Analysis and Linter Projects
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scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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MonkeyType
A Python library that generates static type annotations by collecting runtime types (by Instagram)
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coala
coala provides a unified command-line interface for linting and fixing all your code, regardless of the programming languages you use.
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Flake8
flake8 is a python tool that glues together pycodestyle, pyflakes, mccabe, and third-party plugins to check the style and quality of some python code.
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prospector
Inspects Python source files and provides information about type and location of classes, methods etc
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unimport
:rocket: The ultimate linter and formatter for removing unused import statements in your code. (by hakancelikdev)
I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)
A little introduction about pylint. Pylint is a static code analyzer, it analyses your code without actually running it. Pylint looks for potential errors, gives suggestions on coding standards that your code is not adhering to, potential places where refactoring might help, and also warnings about smelly code.
i can't, unfortunately, it was youtube internal code. but by the same token a lot of the performance stuff was specific optimisations for that code and would not really generalise.
one of the current "extremely large python codebase" projects is instagram, and they do have some public repos, notably monkeytype (https://github.com/Instagram/MonkeyType) which youtube did have its own analogue of, and cinder (https://engineering.fb.com/2022/05/02/open-source/cinder-jit...). in general facebook's engineering blog is a great place to read about this sort of thing.
Pylama is a code audit tool for Python that wraps tools like Pylint, pycodestyle, PyFlakes, McCabe, and others to provide a unified interface.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
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Enhance Your Project Quality with These Top Python Libraries
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Static Typing for Python
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Index
What are some of the best open-source Code Analysis and Linter projects in Python? This list will help you:
| Project | Stars | |
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| 1 | mypy | 17,643 |
| 2 | scalene | 11,240 |
| 3 | Pylint | 5,142 |
| 4 | MonkeyType | 4,566 |
| 5 | vprof | 3,948 |
| 6 | code2flow | 3,709 |
| 7 | coala | 3,524 |
| 8 | Flake8 | 3,290 |
| 9 | prospector | 1,912 |
| 10 | pydeps | 1,635 |
| 11 | pylama | 1,040 |
| 12 | PythonBuddy | 273 |
| 13 | unimport | 238 |
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