Packages
Provides NVIDIA CUBLAS native runtime libraries for CUDA 11, enabling GPU-accelerated linear algebra operations in Python applications on x86_64 and ARM64 Linux, Windows platforms.
Install only if you are maintaining legacy code explicitly pinned to CUDA 11 and cannot upgrade; otherwise, use current nvidia-cublas packages or let your framework…
Provides the NVIDIA CUDA nvcc compiler for building CUDA applications from Python, bundling the compiler with its runtime dependencies.
PaddleX is a low-code framework for training, inference, and deployment of computer vision and document processing models, integrating pre-trained models across OCR, object detection, image classification, segmentation, and time-series tasks.
Provides cuDNN runtime libraries for GPU-accelerated deep neural network operations on NVIDIA CUDA 11 hardware.
Provides the NVVM compiler IR library for building and optimizing CUDA applications on NVIDIA GPUs.
Provides CUDA 11 runtime native libraries for GPU-accelerated computing on Linux and Windows systems.
Provides NVIDIA CUDA NVRTC (runtime compilation) native libraries for Python, enabling just-in-time compilation of CUDA kernels on x86_64 and aarch64 Linux and Windows systems.
PyTensor is a Python library for defining, optimizing, and evaluating symbolic mathematical expressions on multi-dimensional arrays, with automatic differentiation and compilation to C, JAX, or Numba.
Install it if you're doing probabilistic programming, building custom optimized numerical pipelines, or need fine-grained control over computation graphs.
Provides xarray-friendly wrappers around NumPy linear algebra, SciPy statistics, and einops operations, reducing verbosity while preserving labeled array semantics.
Downloads and loads pre-trained TensorFlow SavedModels from TensorFlow Hub (now redirected to Kaggle Models) for reuse in TensorFlow programs with minimal code.
However, be aware that maintenance is dormant and many models from the original tfhub.dev have been deleted; verify your models exist before committing to this…
Provides functions to test primality, factor integers, generate prime sequences, and compute Euler's totient function for mathematical and cryptographic applications.
Install only if you need a lightweight, dependency-free prime utility for educational or experimental use and can tolerate the lack of maintenance.
FilterPy provides Kalman filters, Extended Kalman filters, Unscented Kalman filters, and related optimal and non-optimal estimation filters for tracking and state estimation.
Provides NVIDIA CUDA C Runtime libraries for Python, enabling GPU-accelerated compute on supported platforms.
Install only if you have a specific dependency requirement from another package or a documented need for CUDA 13.3 runtime support; it is not typically installed…
Provides a Python interface to QDLDL, a free LDL factorization routine for solving linear systems with quasi-definite matrices in sparse format.
Provides NVIDIA CUDA C++ Core Compute Libraries (CCCL) for GPU-accelerated computing on Windows and Linux systems.
However, verify the unclear license terms with NVIDIA and confirm your system architecture matches an available wheel before installing.
TensorFlow CPU provides a machine learning and numerical computation framework for building and training models on CPU-based systems, with support for Python 3.10 through 3.13.
CMA-ES is a derivative-free numerical optimization algorithm for difficult non-convex, multi-modal, or ill-conditioned optimization problems in continuous or mixed-integer search spaces.
Install it if you need derivative-free optimization for difficult non-convex problems in moderate dimensions; skip it if you have gradients available or are…
Solves the linear assignment problem using the Jonker-Volgenant (LAPJV) or Volgenant-Mordecai (LAPMOD) algorithm, returning optimal row-to-column assignments for dense or sparse cost matrices.
Install it if you need to solve linear assignment problems and prefer a specialized implementation over a general-purpose optimizer.
portion provides data structures and operations for working with intervals—including unions, intersections, complements, and containment tests—with automatic simplification and support for any comparable objects.
Install it if you need interval arithmetic or range operations.
Fiddle is a Python-first configuration library that lets you define and manage complex program parameters in readable Python code, particularly suited for machine learning applications.
Install it if configuration-as-code in Python appeals to your workflow; skip it if you prefer external config files or simpler parameter passing.
Detects change points in time series and signal data using exact and approximate algorithms for parametric and non-parametric models.
Install it if you need to detect structural breaks in time series or signal data.
Provides multi-dimensional sparse array data structures compatible with NumPy and Numba, enabling efficient storage and computation on arrays with mostly zero or missing values.
Provides NVIDIA CUFFT native runtime libraries for CUDA 11, enabling GPU-accelerated Fast Fourier Transform computations on compatible systems.
Install only if required as a transitive dependency of an active package, or if you are locked to CUDA 11 and cannot upgrade.
Provides CUSPARSE native runtime libraries for CUDA 11, enabling sparse matrix operations on NVIDIA GPUs.
Provides NVIDIA CUDA solver native runtime libraries for GPU-accelerated linear algebra and matrix operations on CUDA 11 hardware.
nemo-toolkit provides a PyTorch framework for building, training, and deploying speech AI models including automatic speech recognition (ASR), text-to-speech (TTS), and speech-based language models.
Provides NVIDIA CURAND native runtime libraries for CUDA 11, enabling GPU-accelerated random number generation in Python applications on x86_64 and ARM64 Linux, Windows, and legacy x86 platforms.
No—install only if you are locked into CUDA 11 and have no path to upgrade.
Provides NVIDIA CUDA profiling runtime libraries (CUPTI) for GPU performance analysis and monitoring on systems with CUDA 11 support.
Provides a C-based API for annotating events, code ranges, and resources in applications to enable capture and visualization through NVIDIA's Visual Profiler.
SparseDiffPy provides Python bindings to compute sparse Jacobians and Hessians via the SparseDiffEngine C library, enabling efficient algorithmic differentiation for numerical optimization and machine learning workflows.
Provides a portable intermediate representation (TileIR) for CUDA kernels that abstracts away language-specific details, enabling kernel compilation and optimization across different contexts.
Provides NVIDIA's collective communication library (NCCL) runtime for GPU-accelerated all-reduce, all-gather, reduce, broadcast, and reduce-scatter operations optimized for CUDA 11.
PyStan provides a Python interface to Stan for Bayesian statistical inference, with automatic caching of compiled models and posterior samples.
Awkward Array provides NumPy-like operations on nested, variable-sized data structures—lists, records, mixed types, and missing values—with compiled performance and dynamic typing.
Install it if your workflow involves JSON-like structures, ragged arrays, or hierarchical data that NumPy alone cannot handle efficiently.
nvdisasm disassembles NVIDIA CUDA cubin files into human-readable CUDA assembly code, extracting and presenting the compiled GPU kernel information.
Pyomo is a Python framework for formulating and solving optimization problems, supporting linear, quadratic, nonlinear, mixed-integer, stochastic, and constraint programming models with external solvers.
Install it if you are solving any optimization problem and want to work in Python; the main gotcha is that you must separately install or configure a solver backend.
TF-Keras is a pure-TensorFlow implementation of Keras that provides a high-level deep learning API for building and training neural networks.
The nightly build is suitable for developers and researchers who can tolerate frequent changes and want early access to new features, but not for production systems…
gurobipy is a Python interface to the Gurobi Optimizer for solving mixed-integer linear and quadratic optimization problems. It lets you formulate and solve optimization models directly from Python.
The trial license is useful for prototyping but not for production.
Provides the NVIDIA CUDA nvcc compiler for building CUDA applications, packaged as a Python distribution for easy installation across Linux and Windows platforms.
However, verify that the proprietary license terms fit your use case, and confirm that CUDA 12.9.86 matches your GPU and toolkit requirements before committing to…
EigenPy provides Python bindings between NumPy arrays and the Eigen C++ linear algebra library, enabling zero-copy memory sharing and access to Eigen's matrix decomposition and tensor operations from Python.