Ycarus Gentoo ebuild

pypi-sci

These ebuilds come from .

If you have some problems, go to the official site first.

dev-python

POT : Python Optimal Transport Library ( https://github.com/PythonOT/POT )

anyio : High level compatibility layer for multiple asynchronous event loop implementations ( HOMEPAGE="" )

awkward : Manipulate JSON-like data with NumPy-like idioms. ( https://github.com/scikit-hep/awkward )

awkward-cpp : CPU kernels and compiled extensions for Awkward Array. ( https://awkward-array.org/ )

bash_kernel : A bash kernel for Jupyter ( https://github.com/takluyver/bash_kernel )

certipy : Utility to create and sign CAs and certificates ( https://github.com/LLNL/certipy )

cupy : CuPy: A NumPy-compatible array library accelerated by CUDA ( https://cupy.dev/ )

cython : A Python to C compiler ( HOMEPAGE=" )

dataclasses : A backport of the dataclasses module for Python 3.6 ( https://github.com/ericvsmith/dataclasses )

datatable : Python library for fast multi-threaded data manipulation and munging. ( https://github.com/h2oai/datatable )

duckdb : DuckDB embedded database ( https://www.duckdb.org )

ecos : Embedded Cone Solver. ( https://github.com/embotech/ecos )

fastrlock : Fast, re-entrant optimistic lock implemented in Cython ( https://github.com/scoder/fastrlock )

hepunits : Units and constants in the HEP system of units ( https://github.com/scikit-hep/hepunits )

ipympl : Matplotlib Jupyter Extension ( http://matplotlib.org )

jax : Differentiate, compile, and transform Numpy code. ( https://github.com/google/jax )

json5 : A Python implementation of the JSON5 data format. ( https://github.com/dpranke/pyjson5 )

jupyter_telemetry : Jupyter telemetry library ( http://jupyter.org )

jupyterhub : JupyterHub: A multi-user server for Jupyter notebooks ( https://jupyter.org )

jupyterhub-nativeauthenticator : JupyterHub Native Authenticator ( https://github.com/jupyterhub/nativeauthenticator )

lightgbm : LightGBM Python Package ( https://github.com/microsoft/LightGBM )

matlab_kernel : ( https://github.com/Calysto/matlab_kernel )

metakernel : Metakernel for Jupyter ( https://github.com/Calysto/metakernel )

mpl_axes_aligner : Align the plotting range of matplotlib axes. ( https://github.com/ryutok/mpl_axes_aligner )

nbclassic : Jupyter Notebook as a Jupyter Server Extension. ( http://jupyter.org )

numba-scipy : numba-scipy extends Numba to make it aware of SciPy ( https://github.com/numba/numba-scipy )

numpyro : Pyro PPL on NumPy ( https://github.com/pyro-ppl/numpyro )

onetimepass : Module for generating and validating HOTP and TOTP tokens ( https://github.com/tadeck/onetimepass/ )

pamela : PAM interface using ctypes ( https://github.com/minrk/pamela )

particle : Extended PDG particle data and MC identification codes ( https://github.com/scikit-hep/particle )

pycwt : ( )

python-json-logger : A python library adding a json log formatter ( http://github.com/madzak/python-json-logger )

robustats : Library for high-performance computation of robust statistical estimators. ( https://github.com/FilippoBovo/robustats )

stockwell : Stockwell transform for Python ( https://github.com/claudiodsf/stockwell )

timm : PyTorch Image Models ( https://github.com/huggingface/pytorch-image-models )

traits : Observable typed attributes for Python classes ( http://docs.enthought.com/traits )

tweedie : Tweedie distribution estimations of pdf and cdf ( https://github.com/thequackdaddy/tweedie )

unidip : Python port of the UniDip clustering algorithm ( https://github.com/BenjaminDoran/unidip )

uproot : ROOT I/O in pure Python and NumPy. ( https://github.com/scikit-hep/uproot4 )

uproot3 : ROOT I/O in pure Python and Numpy. ( https://github.com/scikit-hep/uproot3 )

uproot3-methods : Pythonic mix-ins for ROOT classes. ( https://github.com/scikit-hep/uproot3-methods )

uproot4 : ROOT I/O in pure Python and NumPy. ( https://github.com/scikit-hep/uproot4 )

upsilon : Automated Classification of Periodic Variable Stars Using Machine Learning ( https://github.com/dwkim78/upsilon )

wquantiles : Weighted quantiles, including weighted median, based on numpy ( https://github.com/nudomarinero/wquantiles/ )

xgboost : XGBoost Python Package ( https://github.com/dmlc/xgboost )

xopen : Open compressed files transparently ( https://github.com/marcelm/xopen/ )

zernike : Python code for Zernike polynomials ( https://github.com/jacopoantonello/zernike )

Add an ebuild in portage :

The ebuild is now in the portage tree.

You can also use layman : emerge layman then layman -a pypi-sci

For Paludis use this rsync : rsync://gentoo.zugaina.org/pypi-sci-portage

If you have a problem : ycarus(-at-)zugaina.org