Packages
Kedro-Viz is an interactive web-based visualization tool for Kedro data science pipelines that displays pipeline structure, parameters, and metadata in a searchable, filterable interface.
Query Amazon product data and pricing history from the Keepa API, with support for both synchronous and asynchronous requests, and optional visualization of price trends.
Parse, manipulate, and generate changelog files in Keep a Changelog format, converting between markdown and Python dictionaries, and automating semantic version releases.
Install it if you maintain a changelog and want to automate release workflows or programmatically access changelog data; skip it if you manage changelogs manually…
Python SDK for Keeper Secrets Manager that retrieves and manages secrets from a Keeper vault, with support for custom server configurations and encrypted credential access.
Install it if your application needs to retrieve secrets from a Keeper vault at runtime.
Keeper Commander is a command-line and terminal UI tool for managing Keeper Password Manager and KeeperPAM vaults, supporting vault access, administrative tasks, password rotation, session management, and REST service deployment.
Provides Bluetooth Low Energy (BLE) support for Kegtron devices, enabling communication with and data retrieval from Kegtron beer dispensing systems over BLE.
Writes trace events in Perfetto/Chrome trace format for performance profiling, with minimal overhead and optional output.
Kenbun statically discovers and analyzes applications in Python and JavaScript/TypeScript repositories, reporting frameworks, dependencies, build scripts, and entrypoints without executing code or installing dependencies.
However, the project is very new (first release May 2026) with minimal adoption (1 star, top 15000 tier), so expect limited community support and possible API changes.
A Jupyter widget that embeds kepler.gl's interactive geospatial visualization into notebooks, enabling visual exploration of large-scale location data with spatial aggregations.
Keras 3 is a multi-backend deep learning framework supporting JAX, TensorFlow, PyTorch, and OpenVINO, enabling you to build and train neural networks for computer vision, NLP, audio, timeseries, and recommender systems.
Install it if you're building deep learning models and want flexibility; skip it only if you're committed to a single framework and don't need Keras's high-level API.
Provides pre-trained deep learning model definitions and weights for architectures like VGG16, ResNet50, Xception, and MobileNet, ready to use with Keras.
No—not recommended for new projects.
KerasHub provides Keras 3 implementations of pretrained model architectures for text, image, and audio tasks, with checkpoints available on Kaggle Models and support for JAX, TensorFlow, and PyTorch backends.
However, the library is in pre-release (0.31.0) with no backwards compatibility guarantees, so APIs may break.
A multi-backend deep learning framework that lets you build and train neural networks using JAX, TensorFlow, PyTorch, or OpenVINO as the compute engine, without rewriting your model code.
Keras-NLP provides pretrained models and utilities for natural language processing tasks built on Keras 3, supporting multiple backends (JAX, TensorFlow, PyTorch, OpenVINO).
However, the Alpha development status means the API may change; verify that the specific models and tasks you need are available in version 0.31.0 before committing…
keras-ocr detects and recognizes text in images using pre-trained deep learning models (CRAFT for detection, CRNN for recognition), providing a high-level API for text extraction from photos and documents.
However, the aging maintenance status (last release 1012 days ago) means it may not track the latest TensorFlow or dependency versions—verify compatibility with your…
Provides data preprocessing and augmentation utilities for deep learning models, built on numpy and six.
KerasTuner automates hyperparameter optimization for Keras models using built-in search algorithms (Bayesian Optimization, Hyperband, Random Search) and a define-by-run configuration syntax.
However, its maintenance status is aging (276 days since last release), so verify compatibility with your keras version and check for any recent issues before…
Provides a high-level Python wrapper for Kerberos (GSSAPI) authentication operations, enabling client and server Kerberos authentication based on RFC 4559.
Kerchunk extracts metadata from chunked, compressed data formats (NetCDF, HDF5, GRIB, TIFF, FITS, Zarr) and stores it separately, enabling efficient cloud-friendly access to archival data without copying or translating original files.
Provides a Python client library for the Kernel REST API, with synchronous and asynchronous interfaces, full type hints, and automatic pagination support.
Loads optimized compute kernels from Hugging Face Hub into Python applications at runtime, enabling dynamic kernel loading without modifying PYTHONPATH.
However, it requires Python 3.10+ and a working compute environment; without those, it will not function.
kernels-data provides Python bindings for kernel data structures used by the Hugging Face kernels ecosystem, enabling dynamic loading and execution of optimized compute kernels from the Hub.
However, verify the unclear license terms before use in proprietary projects, and confirm your environment meets the stated requirements.
Kerykeion computes planetary and house positions, detects astrological aspects, and generates SVG birth, synastry, transit, and composite charts with customizable planet selections.
Provides a Python client to interact with Kestra servers for triggering flows, sending metrics and outputs, and retrieving execution status and logs.
Install it if you are already using or planning to use Kestra for workflow orchestration.
KeyBERT extracts keywords and keyphrases from documents by computing BERT embeddings and finding n-grams most similar to the document as a whole using cosine similarity.
Hook global keyboard events, register hotkeys, and simulate key presses across Windows, Linux, and macOS from Python.
Unpack, edit, and re-pack Apple Keynote .key files by converting their proprietary compressed binary format into editable YAML, then back into working Keynote archives.
Extracts keyphrases from text documents using part-of-speech patterns and produces document-keyphrase matrices compatible with scikit-learn's vectorizer interface.
However, do not expect active development or rapid bug fixes; treat it as a research tool rather than a production library with ongoing support.
Keyring provides safe password and credential storage by interfacing with the system's native credential manager (macOS Keychain, Windows Credential Locker, Freedesktop Secret Service, or KDE KWallet).
Install it if your application needs to store or retrieve passwords securely without managing encryption yourself.
Provides alternate keyring backend implementations for the keyring package, including plaintext and other non-standard credential storage methods.
Install only if you have a specific need for an alternate backend and accept responsibility for the security implications.
Provides AWS CodeArtifact authentication for pip and twine by extending the keyring library to automatically inject time-limited access tokens.
A keyring backend that stores passwords in an encrypted file using Argon2 key derivation and authenticated AES encryption, integrating with the keyring package for portable credential storage.
A keyring backend that authenticates to Google Cloud Artifact Registry using Application Default Credentials or gcloud SDK tokens, enabling pip and twine to access private Python repositories.
OpenStack Keystone provides authentication, authorization, and service discovery for OpenStack cloud infrastructure via HTTP, typically deployed as an interface to existing identity systems like LDAP.
However, this is not a library for general application use—it is a service component.
Keystone is a lightweight assembler framework that translates assembly code into machine instructions across multiple CPU architectures including Arm, Arm64, Mips, PowerPC, Sparc, SystemZ, X86, and others.
Provides authentication plugins, API discovery, and session management for OpenStack-based cloud services, supporting password, token, and federation-based authentication methods.
Provides authentication and authorization middleware for OpenStack web services through token validation against the Keystone identity service.
Provides X11 and XF86 keysym definitions as Python data structures, mapping mnemonic names to integer values and optional Unicode code points.
However, the last update was in February 2023 and the repository shows no recent commits, so expect no bug fixes or updates.
KFactory is a Python framework for designing photonic and electronic chip layouts, providing parametric cells, routing primitives, cross-section definitions, and schematic-driven design with layout verification on top of KLayout's geometry engine.
Kubeflow Pipelines is a Python SDK for defining, deploying, and managing machine learning workflows as containerized task graphs on Kubernetes clusters.
Install only if you already have or plan to set up a Kubeflow infrastructure; it is not a standalone ML framework.