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pytype | mamba | |
---|---|---|
20 | 15 | |
4,538 | 9,307 | |
1.0% | 26.9% | |
9.8 | 8.3 | |
1 day ago | 8 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
pytype
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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...
- A Python-compatible statically typed language erg-lang/erg
mamba
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Based: Simple linear attention language models
> how the recall can grow unbounded with no tradeoff
this? https://github.com/state-spaces/mamba/issues/175
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Mamba: The Easy Way
If you want to learn this stuff as a computer engineer, you can read the code here [0]. I find the math quite helpful.
[0]: https://github.com/state-spaces/mamba
- FLaNK Stack 05 Feb 2024
- Introduction to State Space Models (SSM)
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Fortran inference code for the Mamba state space language model
This model was discussed recently: https://news.ycombinator.com/item?id=38522428 It's a new kind of ML model architecture that can be used instead of a transformer in LLMs.
See also the original repo from the paper: https://github.com/state-spaces/mamba
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Mamba outperforms transformers "everywhere we tried"
[2] - https://github.com/state-spaces/mamba
Out of curiosity, does anyone feel as though there's any benefit to linking to reddit when we can link to whatever the link is? I for one do not click the link and read discussion on reddit - if I wanted that sort of discussion, I would browse there, not HN.
- GitHub – State-Spaces/Mamba
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Generate valid JSON with Mamba models
The library is compatible with any auto-regressive model, not transformers. To prove our point we integrated Mamba, a new state-space model architecture, to the library. Try it out!
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[D] Thoughts on Mamba?
I ran the NanoGPT of Karparthy replacing Self-Attention with Mamba on his TinyShakespeare Dataset and within 5 minutes it started spitting out the following:
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Mamba-Chat: A Chat LLM based on State Space Models
You might have come across the paper Mamba paper in the last days, which was the first attempt at scaling up state space models to 2.8B parameters to work on language data.
What are some alternatives?
mypy - Optional static typing for Python
miniforge - A conda-forge distribution.
pyright - Static Type Checker for Python
pip - The Python package installer
pyre-check - Performant type-checking for python.
llm.f90 - LLM inference in Fortran
pyannotate - Auto-generate PEP-484 annotations
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
pyanalyze - A Python type checker
mamba-chat - Mamba-Chat: A chat LLM based on the state-space model architecture 🐍
ruff - An extremely fast Python linter and code formatter, written in Rust.
spack - A flexible package manager that supports multiple versions, configurations, platforms, and compilers.