Python Fire
mypy
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Python Fire | mypy | |
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37 | 112 | |
26,266 | 17,506 | |
0.9% | 1.4% | |
6.8 | 9.7 | |
18 days ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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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.
Python Fire
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CLI tools hidden in the Python standard library
The cli tool [fire](https://github.com/google/python-fire/blob/master/docs/guide...) has a nifty feature where it can generate a cli for any file for you.
So random and math are somewhat usable that way
$ python -m fire random uniform 0 1
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Build CLI blazingly fast with python-fire 🔥
With python-fire you can use either function or class to create your subcommands. But I find working with classes more intuitive and manageable. Our first command is going to be a sub-command that shows us the UTC time.
- What is the status of Python 3.11?
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I am sick of writing argparse boilerplate code, so I made "duckargs" to do it for me
Have you checked out fire? Personally, I think it's a really elegant solution to turning a callable object into command line. Plus, the chaining function calls feature lets you build some pretty complex command line patterns likes you never seen with other frameworks. Definitely worth giving it a try!
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What is your favorite ,most underrated 3rd party python module that made your programming 10 times more easier and less code ? so we can also try that out :-) .as a beginner , mine is pyinputplus
I started with click but found python fire to be so much easier to use.
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Best way to get data into python scripts
I highly recommend checking out fire for adding a CLI quickly to little utility scripts that aren't going to be published to the world but just for you.
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What are your coolest tools for one-liners ?
python fire autogenerates CLI wrappers for python modules, which really synergizes with method-chaining APIs like pandas.
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Show HN: Rocketry – Modern scheduler to power your Python projects
Fire can basically do the first step (object -> CLI):
https://github.com/google/python-fire
Gooey can do (CLI -> GUI):
https://github.com/chriskiehl/Gooey
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What packages replaced standard library modules in your workflow?
also, while we're on the subject, fire may not be the same kind of workhorse as argparse or click, but for really simple stuff it's pretty awesome
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Eclipse: python-fire inspired library to simplify creating CLIs in Go, on top of Cobra
I'm relatively new to Go (coming from Python) so I haven't been using Cobra (or Go, for that matter) for long but it's clearly very polished -- only friction I was experiencing with it is there's a lot of boilerplate to creating commands and subcommands, that IMO (idea as proven by python-fire) can be naturally (better) expressed as types / fields / methods that are already built into the language.
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?
click - Python composable command line interface toolkit
pyright - Static Type Checker for Python
typer - Typer, build great CLIs. Easy to code. Based on Python type hints.
ruff - An extremely fast Python linter and code formatter, written in Rust.
Gooey - Turn (almost) any Python command line program into a full GUI application with one line
pyre-check - Performant type-checking for python.
PyInquirer - A Python module for common interactive command line user interfaces
black - The uncompromising Python code formatter
docopt - This project is no longer maintained. Please see https://github.com/jazzband/docopt-ng
pytype - A static type analyzer for Python code
pydantic-cli - Turn Pydantic defined Data Models into CLI Tools
pydantic - Data validation using Python type hints