pydantic-core
pytype
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pydantic-core | pytype | |
---|---|---|
18 | 21 | |
1,270 | 4,538 | |
3.1% | 1.0% | |
9.6 | 9.8 | |
6 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.
pydantic-core
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Is there a pydantic.BaseSettings equivalent in rust?
Funny that you ask... https://github.com/pydantic/pydantic-core Unfortunately it seems that the functionality you ask for is not (yet) part of this ...
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Investigating Pydantic v2's Bold Performance Claims
I encourage you to checkout the official benchmarks for more realistic and detailed examples, and, as always, YMMV.
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Pydantic V2 leverages Rust's Superpowers [video]
> to also be constrained by a separate set of data types which are legal in rust.
This isn't really how writing rust/python iterop works. You tend to have opaque handles you call python methods on. Here's a decent example I found skimming the code.
https://github.com/pydantic/pydantic-core/blob/main/src/inpu...
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Pydantic vs Protobuf vs Namedtuples vs Dataclasses
Thanks for pointing out to that, I did not know about it. Also attaching repo in case someone would be interested as well - https://github.com/pydantic/pydantic-core
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Introducing CodSpeed: Continuous Performance Measurement
pydantic-core: The core validation logic for pydantic, a Python data parsing and validation library.
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Show HN: Python framework is faster than Golang Fiber
pydandic-core [0] will hopefully solve this issue (written in Rust)
[0] -- https://github.com/pydantic/pydantic-core
- Scala or Rust? which one will rule in future?
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Rust for Data Engineering—what's the hype about? 🦀
LinkedIn influencers are weird lol. Rust v Python is apples and oranges. Rust would be glued together by python just like it does with C/C++ and Java/Spark today. We’re already seeing some packages go this direction, like pydantic v2 is rewriting its core validation in rust.
- Python file structure with Rust extensions
- Pydantic 2 rewritten in Rust was merged
pytype
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Google lays off its Python team
it's open source! check out https://github.com/google/pytype and https://github.com/google/pytype/blob/main/docs/developers/t... for more on the multi-file runner
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Enhance Your Project Quality with These Top Python Libraries
Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can catch type errors in your Python code before you even run it.
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Pyre from Meta, pyright from Microsoft and PyType from Google provide additional assistance. They can 'infer' types based on code flow and existing types within the code.
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Mypy 1.6 Released
we've written a little bit about what pytype does differently here: https://google.github.io/pytype/
our main focus is to be able to work with unannotated and partially-annotated code, and treat it on par with fully annotated code.
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Mypy 1.5 Released
So, I tried out pytype the other day, and it was a not a good experience. It doesn't support PEP 420 (implicit namespace packages), which means you have to litter __init__.py files everywhere, or it will create filename collisions. See https://github.com/google/pytype/issues/198 for more information. I've since started testing out pyre.
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Writing Python like it's Rust
What is the smart money doing for type checking in Python? I've used mypy which seems to work well but is incredibly slow (3-4s to update linting after I change code). I've tried pylance type checking in VS Code, which seems to work well + fast but is less clear and comprehensive than mypy. I've also seen projects like pytype [1] and pyre [2] used by Google/Meta, but people say those tools don't really make sense to use unless you're an engineer for those companies.
Am just curious if mypy is really the best option right now?
[1] https://github.com/google/pytype
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PyMEL's new type stubs
At Luma, we're using mypy to check nearly our entire code-base, including our Maya-related code, thanks to these latest changes. Fully adopting mypy (or an alternative like pytype) is no small feat, but working within a fully type-annotated code base with a type checker to enforce accuracy is like coding in a higher plane of existence: fewer bugs, easier code navigation, faster dev onboarding, easier refactoring, and dramatically increased confidence about every change. I wrote about some deeper insights in these posts.
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The Python Paradox
Check out https://github.com/google/pytype
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Forma: An efficient vector-graphics renderer
i work on https://github.com/google/pytype which is largely developed internally and then pushed to github every few days. the github commits are associated with the team's personal github accounts. pytype is not an "official google product" insofar as the open source version is presented as is without official google support, but it is "production code" in the sense that it is very much used extensively within google.
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Ruff – an fast Python Linter written in Rust
pytype dev here - thanks for the kind words :) whole-program analysis on unannotated or partially-annotated code is our particular focus, but there's surprisingly little dark PLT magic involved; in particular you don't need to be an academic type theory wizard to understand how it works. our developer docs[1] have more info, but at a high level we have an interpreter that virtually executes python bytecode, tracking types where the cpython interpreter would have tracked values.
it's worth exploring some of the other type checkers as well, since they make different tradeoffs - in particular, microsoft's pyright[2] (written in typescript!) can run incrementally within vscode, and tends to add new and experimentally proposed typing PEPs faster than we do.
[1] https://github.com/google/pytype/blob/main/docs/developers/i...
What are some alternatives?
aiohttp-apispec - Build and document REST APIs with aiohttp and apispec
mypy - Optional static typing for Python
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
pyright - Static Type Checker for Python
pymartini - A Cython port of Martini for fast RTIN terrain mesh generation
pyre-check - Performant type-checking for python.
koda-validate - Typesafe, Composable Validation
pyannotate - Auto-generate PEP-484 annotations
modin - Modin: Scale your Pandas workflows by changing a single line of code
pyanalyze - A Python type checker
typedload - Python library to load dynamically typed data into statically typed data structures
ruff - An extremely fast Python linter and code formatter, written in Rust.