Returning to snake's nest after a long journey, any major advances in python for science ?

1. jax

   1 89 32,032 10.0 Python

   Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

   

   It's relatively early days yet, but JAX is in the process of developing its nascent scientific computing / scientific machine learning ecosystem. Mostly because of its strong autodifferentiation capabilities, excellent JIT compiler etc. (E.g. to show off one of my own projects, Diffrax is the library of diffeq solvers for JAX.)

2. Judoscale

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   Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.

   

3. diffrax

   2 23 1,604 8.6 Python

   Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

   

   It's relatively early days yet, but JAX is in the process of developing its nascent scientific computing / scientific machine learning ecosystem. Mostly because of its strong autodifferentiation capabilities, excellent JIT compiler etc. (E.g. to show off one of my own projects, Diffrax is the library of diffeq solvers for JAX.)

4. esm

   3 5 3,051 4.6 Python

   Discontinued Evolutionary Scale Modeling (esm): Pretrained language models for proteins (by facebookresearch)

   

   Likewise PyTorch is seeing a lot of sciml work, in particular to do with protein design. (See e.g. ESM2.)

5. pyright

   4 145 14,202 9.8 Python

   Static Type Checker for Python

   

   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.)

6. typeguard

   5 9 1,638 7.9 Python

   Run-time type checker for Python

   

   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.)

7. beartype

   6 23 2,991 9.5 Python

   Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.

   

   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.)

8. jaxtyping

   7 8 1,385 8.6 Python

   Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/

   

   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.)

9. InfluxDB

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   InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.

   

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