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Package Name Access Summary Updated
langchain-core public Core APIs for LangChain, the LLM framework for buildilng applications through composability 2025-10-01
input4mips-validation public Validation of input4MIPs data (checking file formats, metadata etc.). 2025-10-01
input4mips-validation-locked public Validation of input4MIPs data (checking file formats, metadata etc.). 2025-10-01
slepc4py public Python bindings for SLEPc 2025-10-01
bitsandbytes public The bitsandbytes library is a lightweight Python wrapper around CUDA custom functions, in particular 8-bit optimizers, matrix multiplication (LLM.int8()), and 8 & 4-bit quantization functions. 2025-10-01
bioimageio.spec public Parser and validator library for BioImage.IO specifications 2025-10-01
pydantic-core public Core validation logic for pydantic written in rust 2025-10-01
libsemigroups public C++ library for semigroups and monoids 2025-10-01
euporie public Euporie is a suite of terminal applications for interacting with Jupyter kernels 2025-10-01
geographiclib-cpp public A small C++ library for geographic conversions 2025-10-01
evalica public Evalica, your favourite evaluation toolkit. 2025-10-01
qt6-graphs public Qt is a cross-platform application and UI framework. 2025-10-01
coremltools public Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. 2025-10-01
octave public GNU Octave is a high-level language, primarily intended for numerical computations 2025-10-01
pcmdi_metrics public The PCMDI metrics package is used to objectively compare results from climate models with observations using well-established statistical tests. Results are produced in the context of all model simulations contributed to CMIP5 and earlier CMIP phases. Among other purposes, this enables modeling groups to evaluate changes during the development cycle in the context of the structural error distribution of the multi-model ensemble. Currently, the comparisons are focused on large- to global-scale annual cycle performance metrics. 2025-10-01
amrex public A software framework for massively parallel, block-structured adaptive mesh refinement (AMR) applications 2025-10-01
databricks-cli public A command line interface for Databricks 2025-10-01
dingo-gw public Deep inference for gravitational-wave observations 2025-10-01
r-terra public Methods for spatial data analysis with raster and vector data. Raster methods allow for low-level data manipulation as well as high-level global, local, zonal, and focal computation. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. 'terra' is very similar to the 'raster' package; but 'terra' can do more, is simpler to use, and it is faster. 2025-10-01
impactx public ImpactX enables high-performance modeling of beam dynamics in particle accelerators with collective effects. 2025-10-01
cylc-uiserver-base public Cylc UI Server 2025-10-01
cylc-uiserver-hub-base public Cylc UI Server 2025-10-01
cylc-uiserver public Cylc UI Server 2025-10-01
spiceypy public The NASA JPL NAIF SPICE toolkit wrapper written in Python 2025-10-01
r-spdep public A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' (1999) <doi:10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I> Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x> and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) <doi:10.1111/j.1538-4632.2007.00708.x>, local 'Moran's I', 'Gearys C' ('Anselin' 1995) <doi:10.1111/j.1538-4632.1995.tb00338.x> and 'Getis/Ord' G ('Ord' and 'Getis' 1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>, 'saddlepoint' approximations ('Tiefelsdorf' 2002) <doi:10.1111/j.1538-4632.2002.tb01084.x> and exact tests for global and local 'Moran's I' ('Bivand et al.' 2009) <doi:10.1016/j.csda.2008.07.021> and 'LOSH' local indicators of spatial heteroscedasticity ('Ord' and 'Getis') <doi:10.1007/s00168-011-0492-y>. The implementation of most of the measures is described in 'Bivand' and 'Wong' (2018) <doi:10.1007/s11749-018-0599-x>. From 'spdep' and 'spatialreg' versions >= 1.2-1, the model fitting functions previously present in this package are defunct in 'spdep' and may be found in 'spatialreg'. 2025-10-01

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