mypy
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mypy | Flake8 | |
---|---|---|
112 | 33 | |
17,506 | 3,257 | |
1.4% | 1.7% | |
9.7 | 7.5 | |
8 days ago | 9 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mypy
- The GIL can now be disabled in Python's main branch
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Polars – A bird's eye view of Polars
It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282
- Static Typing for Python
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Python 3.13 Gets a JIT
There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.
And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.
And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.
[0] https://nuitka.net/
[1] https://github.com/python/mypy/tree/master/mypyc
- Introducing Flask-Muck: How To Build a Comprehensive Flask REST API in 5 Minutes
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WeveAllBeenThere
In Python there is MyPy that can help with this. https://www.mypy-lang.org/
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It's Time for a Change: Datetime.utcnow() Is Now Deprecated
It's funny you should say this.
Reading this article prompted me to future-proof a program I maintain for fun that deals with time; it had one use of utcnow, which I fixed.
And then I tripped over a runtime type problem in an unrelated area of the code, despite the code being green under "mypy --strict". (and "100% coverage" from tests, except this particular exception only occured in a "# pragma: no-cover" codepath so it wasn't actually covered)
It turns out that because of some core decisions about how datetime objects work, `datetime.date.today() < datetime.datetime.now()` type-checks but gives a TypeError at runtime. Oops. (cause discussed at length in https://github.com/python/mypy/issues/9015 but without action for 3 years)
One solution is apparently to use `datetype` for type annotations (while continuing to use `datetime` objects at runtime): https://github.com/glyph/DateType
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What's New in Python 3.12
PEP 695 is great. I've been using mypy every day at work in last couple years or so with very strict parameters (no any type etc) and I have experience writing real life programs with Rust, Agda, and some Haskell before, so I'm familiar with strict type systems. I'm sure many will disagree with me but these are my very honest opinions as a professional who uses Python types every day:
* Some types are better than no types. I love Python types, and I consider them required. Even if they're not type-checked they're better than no types. If they're type-checked it's even better. If things are typed properly (no any etc) and type-checked that's even better. And so on...
* Having said this, Python's type system as checked by mypy feels like a toy type system. It's very easy to fool it, and you need to be careful so that type-checking actually fails badly formed programs.
* The biggest issue I face are exceptions. Community discussed this many times [1] [2] and the overall consensus is to not check exceptions. I personally disagree as if you have a Python program that's meticulously typed and type-checked exceptions still cause bad states and since Python code uses exceptions liberally, it's pretty easy to accidentally go to a bad state. E.g. in the linked github issue JukkaL (developer) claims checking things like "KeyError" will create too many false positives, I strongly disagree. If a function can realistically raise a "KeyError" the program should be properly written to accept this at some level otherwise something that returns type T but 0.01% of the time raises "KeyError" should actually be typed "Raises[T, KeyError]".
* PEP 695 will help because typing things particularly is very helpful. Often you want to pass bunch of Ts around but since this is impractical some devs resort to passing "dict[str, Any]"s around and thus things type-check but you still get "KeyError" left and right. It's better to have "SomeStructure[T]" types with "T" as your custom data type (whether dataclass, or pydantic, or traditional class) so that type system has more opportunities to reject bad programs.
* Overall, I'm personally very optimistic about the future of types in Python!
[1] https://github.com/python/mypy/issues/1773
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Mypy 1.6 Released
# is fixed: https://github.com/python/mypy/issues/12987.
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Ask HN: Why are all of the best back end web frameworks dynamically typed?
You probably already know but you can add type hints and then check for consistency with https://github.com/python/mypy in python.
Modern Python with things like https://learnpython.com/blog/python-match-case-statement/ + mypy + Ruff for linting https://github.com/astral-sh/ruff can get pretty good results.
I found typed dataclasses (https://docs.python.org/3/library/dataclasses.html) in python using mypy to give me really high confidence when building data representations.
Flake8
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To Review or Not to Review: The Debate on Mandatory Code Reviews
Automating code checks with static code analysis allows us to enforce code styling effectively. By integrating tools into our workflow, we can identify errors at an early stage, while coding instead of blocking us at the end. For instance, flake8 checks Python code for style and errors, eslint performs similar checks for JavaScript, and prettier automatically formats code to maintain consistency.
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Enhance Your Project Quality with These Top Python Libraries
Flake8. This library is a wrapper around pycodestyle (PEP8), pyflakes, and Ned Batchelder’s McCabe script. It is a great toolkit for checking your code base against coding style (PEP8), programming errors (like SyntaxError, NameError, etc) and to check cyclomatic complexity.
- Django Code Formatting and Linting Made Easy: A Step-by-Step Pre-commit Hook Tutorial
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Enhancing Python Code Quality: A Comprehensive Guide to Linting with Ruff
Flake8 combines the functionalities of the PyFlakes, pycodestyle, and McCabe libraries. It provides a streamlined approach to code linting by detecting coding errors, enforcing style conventions, and measuring code complexity.
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Which is your favourite or go-to YouTube channel for being up-to-date on Python?
He made yesqa and pyupgrade (among others), and also works on flake8. His main job is for https://sentry.io/.
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The Power of Pre-Commit for Python Developers: Tips and Best Practices
repos: - repo: https://github.com/psf/black rev: 21.7b0 hooks: - id: black language_version: python3.8 - repo: https://github.com/PyCQA/flake8 rev: 3.9.2 hooks: - id: flake8
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Is it considered rude to completely change the formatting of someone else's code when making a PR?
https://github.com/psf/black it’s a PEP8 compliant formatter for Python codebases. If you don’t like auto formatting files you can use https://github.com/PyCQA/flake8 it just lists out all of the style issues so you can fix them manually.
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Ruff: one Python linter to rule them all
I have no stake in that, but my observation is that the actual discussion appears to have both supporters and detractors rather than overwhelming support. Either way, it has nothing to do with whether or not it is realistic to say that Ruff is the "one Python linter to rule them all".
- Improve your Django Code with pre-commit
What are some alternatives?
pyright - Static Type Checker for Python
Pylint - It's not just a linter that annoys you!
ruff - An extremely fast Python linter and code formatter, written in Rust.
black - The uncompromising Python code formatter [Moved to: https://github.com/psf/black]
pyre-check - Performant type-checking for python.
autopep8 - A tool that automatically formats Python code to conform to the PEP 8 style guide.
black - The uncompromising Python code formatter
pylama - Code audit tool for python.
pytype - A static type analyzer for Python code
autoflake - Removes unused imports and unused variables as reported by pyflakes
pydantic - Data validation using Python type hints
prospector - Inspects Python source files and provides information about type and location of classes, methods etc