Subcategories
Packages
This package is deprecated; it redirects users to ydata-profiling for exploratory data analysis of pandas DataFrames with HTML and JSON export.
libkvikio-cu12 provides Python and C++ bindings to NVIDIA's cuFile API, enabling high-performance GPU-accelerated file I/O with support for GPUDirect Storage and seamless host/device memory handling.
Provides NVIDIA GPU acceleration for JAX numerical computing via the PJRT plugin interface, enabling XLA compilation and execution on CUDA 13 hardware.
Datashader converts large datasets into accurate visual representations by rasterizing data through projection, aggregation, and transformation stages, enabling scalable visualization of millions of records.
pylibcudf-cu12 provides Python bindings for libcudf, a CUDA C++ library that accelerates tabular data operations on NVIDIA GPUs using Apache Arrow data structures.
Converts audio into discrete semantic speech tokens using a PyTorch implementation of the S3Tokenizer model, supporting batch inference and online extraction during model training.
GPU-accelerated machine learning algorithms with scikit-learn-compatible APIs for clustering, regression, classification, dimensionality reduction, and time series models.
Dask-awkward integrates Awkward Array with Dask to enable distributed, lazy computation on complex, nested data structures across multiple cores or machines.
Install it if you work with Awkward Arrays at scale or need lazy evaluation of nested structures across multiple workers.
pyxnat provides Python bindings to interact with XNAT (Extensible Neuroimaging Archive Toolkit) servers, enabling programmatic access to medical imaging data and project management through HTTP requests.
Parselmouth provides a Pythonic interface to Praat's speech analysis algorithms by directly binding to Praat's C/C++ code, enabling phonetic and acoustic analysis without reimplementation.
Not recommended if you require Python 3.12+ without building from source or if your project cannot use GPLv3-licensed code.
Gmsh is a three-dimensional finite element mesh generator that wraps the official Gmsh application and SDK for use in Python, providing both a command-line tool and a Python API for mesh generation with pre- and post-processing.
bitmath converts and performs arithmetic on file sizes across SI and NIST prefix units (kB to YiB), with support for human-readable formatting, rich comparisons, and capacity math.
pylibraft-cu12 provides Python bindings to RAFT's CUDA-accelerated primitives for linear algebra, sparse and dense operations, statistics, and solvers, designed for GPU-accelerated algorithm development.
Converts TensorFlow, Keras, TensorFlow.js, and TFLite models to ONNX format via command line or Python API, enabling model portability across different inference runtimes.
librmm-cu12 provides GPU memory allocation and management for CUDA 12 workloads, offering customizable device and host memory pools to optimize GPU-centric applications.
alchemlyb parses molecular dynamics simulation output, extracts uncorrelated samples from timeseries data, and estimates free energies using MBAR, BAR, and thermodynamic integration methods.
Install it if you work with alchemical free energy calculations; skip it if you do not.
Histoprint renders NumPy histograms and compatible histogram objects to the terminal using Unicode and color codes, supporting overlay and stacked display modes.
Install it if you regularly work in terminal environments and need quick histogram visualization.
rpy2 embeds R within Python, allowing you to call R functions and work with R objects directly from Python code without launching a separate R process.
Extends pandas DataFrames with method-chainable data-cleaning functions, enabling readable, verb-based operations for common preprocessing tasks like column renaming, null removal, and data transformation.
Install it if you work with pandas and want method chains to replace imperative preprocessing logic.
Integrates PyTorch profiling data with TensorBoard, providing GPU timeline tracing and performance diagnostics for ML workloads through a TensorBoard plugin interface.
However, the last release was in October 2023; verify compatibility with your current PyTorch version before relying on it for new projects.
build123d is a Python CAD framework for creating 2D and 3D models using boundary representation geometry, built on the Open Cascade kernel, with export to standard formats like STEP and STL.
Command-line interface for managing Bittensor platform operations including wallet creation, subnet registration, delegation, and governance voting.
FastJet provides Python bindings to the FastJet C++ library for clustering particles in high-energy physics, supporting vectorized, out-of-core, and non-vectorized interfaces with Awkward Array integration.
Automatically extracts hundreds of time-series features from sampled data using statistical and signal-processing algorithms, then filters them to identify only those relevant to your machine learning task.
Install it if you work with time-series data and want to avoid manual feature engineering.
libraft-cu12 provides CUDA-accelerated primitives and algorithms for machine learning and data mining, including dense and sparse linear algebra, solvers, statistics, and GPU infrastructure utilities.
Install only if you need low-level GPU acceleration for algorithms—it is not intended for direct data science experimentation.
Extends pandas DataFrames to store and manipulate Awkward Array columns, enabling efficient handling of nested and ragged data structures within pandas workflows.
However, the aging maintenance status (no release in over a year) means you should verify compatibility with your specific pandas and Python versions before relying…
Implements the N4SID algorithm for subspace identification of state-space models, including Kalman filtering and support for ARMAX, ARMA, AR, and MA time-series models.
However, maintenance is aging (last release 386 days ago), so verify that the implementation meets your numerical accuracy requirements and check the documentation…
Provides optimized group-indexing operations on arrays, with `aggregate` as the primary tool for computing reductions (sum, mean, std, etc.) across labeled groups of values.
Extends TensorFlow with support for file systems and data formats not built into TensorFlow, including HTTP/HTTPS access and automatic decompression for remote datasets.
Install only if you have a specific need for extended I/O capabilities; it is not required for standard TensorFlow workflows.
cassIO integrates Apache Cassandra with machine learning and LLM workloads, providing a Python library to connect Cassandra databases to AI/genAI applications.
However, be aware of the aging maintenance cadence (680 days since last release) and the possibility of breaking changes in the 0.* series.
Flox provides fast GroupBy reduction operations for arrays using dask and xarray, offering interfaces for common aggregations like mean and sum, plus custom reductions.
Install it if you need efficient grouped reductions on arrays; the Beta status is not a barrier given the active maintenance and NASA-funded backing.
Vesin computes neighbor lists for atomistic systems—identifying which atoms are within a cutoff distance of each other—with a Python interface backed by compiled code for speed.
Distributes fonts and data files for the mplhep plotting library, including Tex Gyre Heros, Tex Gyre Termes, Fira Sans, and Fira Math with open licenses.
GPU-accelerated physics simulation for robotics using NVIDIA Warp, providing high-throughput MuJoCo-compatible simulation with batch rendering across parallel worlds.
Stim is a fast simulator for quantum stabilizer circuits, providing interactive simulation, high-speed sampling, and independent exploration of quantum states through TableauSimulator, Circuit compilation, and Pauli/Tableau data types.
PyTorch Forecasting provides neural network models and utilities for time series forecasting, including architectures like Temporal Fusion Transformers, N-BEATS, and N-HiTS, with training orchestrated through PyTorch Lightning.
Install it if you need to train neural forecasting models on time series data and want to avoid reimplementing standard architectures or training boilerplate.
Read and write TDMS files (LabVIEW data format) as numpy arrays, with support for hierarchical groups and channels plus optional export to HDF5 or pandas DataFrames.
Install it if you work with LabVIEW data or National Instruments DAQ systems.
Times converts between universal (UTC) time and arbitrary timezones, and parses/formats datetime strings and POSIX timestamps with explicit timezone handling.
No, not for new projects.
A command-line tool for running computer vision inference locally via Docker or against Roboflow's hosted API, supporting object detection, classification, instance segmentation, and foundation models like CLIP and SAM.
However, verify that the GPL-3.0 and AGPL-3.0 licenses on bundled models (YOLOv5, YOLOv8) align with your project's licensing requirements before committing to…
Provides Python bindings to NVIDIA's fatbin compiler library for working with CUDA binary formats and GPU code compilation artifacts.
However, verify the license terms before use in proprietary projects, and confirm that your system meets any undocumented CUDA runtime dependencies.