typeguard
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typeguard | Kategory | |
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7 | 32 | |
1,446 | 5,968 | |
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8.4 | 8.8 | |
22 days ago | 2 days ago | |
Python | Kotlin | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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typeguard
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Returning to snake's nest after a long journey, any major advances in python for science ?
As other folks have commented, type hints are now a big deal. For static typing the best checker is pyright. For runtime checking there is typeguard and beartype. These can be integrated with array libraries through jaxtyping. (Which also works for PyTorch/numpy/etc., despite the name.)
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Boring Python: Code Quality
I got good use of the run-time type checking of typeguard [0] when I recently invoked it via its pytest plugin [2]. For all code visited in the test suite, you get a failing test whenever an actual type differs from an annotated type.
[0]: https://github.com/agronholm/typeguard/
[1]: https://typeguard.readthedocs.io/en/latest/userguide.html#us...
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Im listening...
But you can use a library like typeguard to get runtime typechecking. Or run mypy over the code to get static typechecking.
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Python’s “Type Hints” are a bit of a disappointment to me
Every point in this blog post strikes me as either (1) unaware of the tooling around python typing other than mypy, or (2) a criticism of static-typing-bolted-on-to-a-dynamically-typed-language, rather than Python's hints. Regarding (1), my advise to OP is to try out Pyright, Pydantic, and Typeguard. Pyright, especailly, is amazing and makes the process of working with type hints 2 or 3 times smoother IMO. And, I don't think points that fall under (2) are fair criticisms of type *hints*. They are called hints for a reason.
Otherwise, here's a point-by-point response, either recommending OP checks out tooling, or showing that the point being made is not specific to Python.
> type hints are not binding.
There are projects [0][1] that allow you to enforce type hints at runtime if you so choose.
It's worth mentioning that this is very analogous to how Typescript does it, in that type info is erased completely at runtime.
> Type checking is your job after all, ...[and that] requires maintenance.
There are LSPs like Pyright[2] (pyright specifically is the absolute best, IMO) that report type errors as you code. Again, this is very very similar to typescript.
> There is an Any type and it renders everything useless
I have never seen a static-typing tool that was bolted on to a dynamically typed language, without an `Any` type, including typescript.
> Duck type compatibility of int and float
The author admits that they cannot state why this behavior is problematic, except for saying that it's "ambiguous".
> Most projects need third-party type hints
Again, this is a criticism of all cases where static types are bolted on dynamically typed languages, not Python's implementation specifically.
> Sadly, dataclasses ignore type hints as well
Pydantic[3] is an amazing data parsing library that takes advantage of type hints, and it's interface is a superset of that of dataclasses. What's more, it underpins FastAPI[4], an amazing API-backend framework (with 44K Github stars).
> Type inference and lazy programmers
The argument of this section boils down to using `Any` as a generic argument not being an error by default. This is configurable to be an error both in Pyright[5], and mypy[6].
> Exceptions are not covered [like Java]
I can't find the interview/presentation, but Guido Van Rossum specifically calls out Java's implementation of "exception annotations" as a demonstration of why that is a bad idea, and that it would never happen in Python. I'm not saying Guido's opinion is the absolute truth, but just letting you know that this is an explicit decision, not an unwanted shortcoming.
[0] https://github.com/RussBaz/enforce
[1] https://github.com/agronholm/typeguard
[2] https://github.com/microsoft/pyright
[3] https://pydantic-docs.helpmanual.io
[4] https://github.com/tiangolo/fastapi
[5] https://github.com/microsoft/pyright/blob/main/docs/configur...
[6] https://mypy.readthedocs.io/en/stable/config_file.html#confv...
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Statically typed Python
Personally I find working around mypy's quirks to be more effort than it's worth, so to offer another option: typeguard or beartype can be used to perform run-time type checking.
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Tests aren’t enough: Case study after adding type hints to urllib3
Never checked? They're statically checked.
Also, tooling like https://pydantic-docs.helpmanual.io/ can do runtime checking for important parts of your app or you can add use this https://github.com/agronholm/typeguard to enforce all types at runtime (although I haven't measured the performance impact, probably something to do in a separate environment than production?).
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DoorDash: Migrating From Python to Kotlin for Our Backend Services
typeguard
Kategory
- Arrow Project for Arrow on GitHub
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Java 21 makes me like Java again
Yeah, it has nice funcional capabilities and libraries (like Arrow[0]).
[0]: https://arrow-kt.io
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Is it prudent to use Scala for anything new?
Last but not least, Scala is currently the language with one of the best effect systems in my opinion (https://zio.dev/). Kotlin for example has copied the approach with https://arrow-kt.io/ which I think is great actually. But when comparing Scala and Kotlin here, Scala wins by a large margin, it is a completely different world. It's like building a highly concurrent system in Erlang vs C.
Of course, if you don't want to learn things like union types, traits/typeclasses and effects (similar to async/await but more powerful) you will be annoyed by Scala. But once you learned them, you can never go back.
- Alternatives to scala FP
- Result Class with Generic Type for both Success and Failure States
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Struggling with software robustness with Kotlin
In my own code, I started to use explicit error handling. I'm currently experimenting with Result (from https://github.com/michaelbull/kotlin-result) and Raise (from https://arrow-kt.io/).
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Hey Rustaceans! Got a question? Ask here (5/2023)!
Are there any more-or-less established functional crates in Rust (similar to Kotlin’s Arrow)?
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What's the benefit of using Arrow with Kotlin?
I wonder how the community sees adding Arrow besides standard Kotlin language features. Is it something that's still considered useful or just redundant and causing more confusion?
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ArrowKt/FP - Tracking paths to validation errors
You can define a function like context(EitherEffect) suspend fun MyType.bind(path: String)like the ones in https://github.com/arrow-kt/arrow/blob/b608a054a5318fe57d7055c35bb64a5effb053b6/arrow-libs/core/arrow-core/src/commonMain/kotlin/arrow/core/computations/either.kt
- What advance concept to learn in Kotlin
What are some alternatives?
beartype - Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
cats-effect - The pure asynchronous runtime for Scala
pydantic - Data validation using Python type hints
RxKotlin - RxJava bindings for Kotlin
mypyc - Compile type annotated Python to fast C extensions
kotlin-monads - Monads for Kotlin
react-wasm-github-api-demo - A demo application to serve as a template for your Rust & React needs. With a sample GraphQL backend.
kotlin-result - A multiplatform Result monad for modelling success or failure operations.
dactyl-keyboard - Web generator for dactyl keyboards.
Reduks - A "batteries included" port of Reduxjs for Kotlin+Android
typeshed - Collection of library stubs for Python, with static types
redux-kotlin - Predictable state container for Kotlin apps