setuptools
mypy
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setuptools | mypy | |
---|---|---|
21 | 112 | |
2,307 | 17,541 | |
2.3% | 1.6% | |
9.9 | 9.7 | |
4 days ago | 5 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.
setuptools
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My User Experience Porting Off Setup.py
To be fair, that seems to have been a 2 year warning:
https://github.com/pypa/setuptools/commit/3544de73b3662a27fa...
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Python 3.12.0 from a supply chain security perspective
There was/is some discussion in setuptools about how to normalize the tarball (https://github.com/pypa/setuptools/issues/2133#issuecomment-...) coudl something similar be applied to Building Python itself ?
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ERROR after python3.11 update
❯ yay -Sy python-setuptools python-jaraco.text ❯ pip show setuptools Name: setuptools Version: 67.7.0 Summary: Easily download, build, install, upgrade, and uninstall Python packages Home-page: https://github.com/pypa/setuptools Author: Python Packaging Authority Author-email: [email protected] License: Location: /usr/lib/python3.11/site-packages Requires: jaraco.text, more-itertools, ordered-set, packaging, platformdirs, tomli, validate-pyproject Required-by: Cerberus, fs, httpie, input-remapper, pecan, pycountry, python-lsp-server, reuse, setuptools-scm, zc.lockfile
- InvalidVersion Exception on Setuptools 66
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PIP fails to install correctly in Ubuntu 20.04.Need help.
Link: https://github.com/pypa/setuptools/issues/3772
- If there’s gonna be a Python 4.0 one day, what’s a breaking change you’d like to see? Let’s explore the ideas you have that can make Python even better!
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So how do you actually deploy code/scripts?
For example, when it comes to Python, one option is to use the same packaging system that a huge number of open-source libraries and tools are published with. You can use setuptools or Hatch to build a "packaged" version of your code, and publish it to either the public PyPi repository or an internal one that you set up. Then your users can use pip to install your package, automatically fetch its dependencies, and keep it up to date, just like any other Python module.
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What’s the most convenient way for a non-programmer to run a Python code?
You could maybe make it a click Application, and use setuptools.
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turbo encabulator compliant
Not sure how advisable it is to depend on setup.py given the setuptools team has very clearly stated that they are not interested in supporting any cli commands anymore including setup.py install. Relavant PR
- [BUG] There was an error checking the latest version of pip · Issue #3333 · pypa/setuptools
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.
What are some alternatives?
hatch - Modern, extensible Python project management
pyright - Static Type Checker for Python
Python-docker - Docker Official Image packaging for Python
ruff - An extremely fast Python linter and code formatter, written in Rust.
bottlerocket - An operating system designed for hosting containers
pyre-check - Performant type-checking for python.
python-adblock - Brave's adblock library in Python
black - The uncompromising Python code formatter
htop - htop - an interactive process viewer
pytype - A static type analyzer for Python code
build - A simple, correct Python build frontend
pydantic - Data validation using Python type hints