MCUboot is a secure bootloader for 32-bit MCUs. This package provides a tool to securely sign firmware images for booting by MCUboot.

This is a Python implementation of the zxcvbn library created at Dropbox. The original library, written for JavaScript, can be found here. This port includes features such as:

1. Accepts user data to be added to the dictionaries that are tested against (name, birthdate, etc.)

2. Gives a score to the password, from 0 (terrible) to 4 (great).

3. Provides feedback on the password and ways to improve it.

4. Returns time estimates on how long it would take to guess the password in different situations.

Pyglet is a Python library for developing games and other visually-rich applications. It supports windowing, user interface event handling, Joysticks, OpenGL graphics, loading images and videos, playing sounds and music.

PySDL2 is a pure Python wrapper around the SDL2,SDL2_mixer, SDL2_image, SDL2_ttf, and SDL2_gfx libraries. Instead of relying on C code, it uses the built-in ctypes module to interface with SDL2, and provides simple Python classes and wrappers for common SDL2 functionality.

Kivy is a software library for rapid development of hardware-accelerated multitouch applications.

This package provides Kivy widgets that approximate Google's Material Design spec without sacrificing ease of use or application performance.

Pyglet is a Python library for developing games and other visually-rich applications. It supports windowing, user interface event handling, Joysticks, OpenGL graphics, loading images and videos, playing sounds and music.

This package provides support for async/await applications without requiring an event loop, useful for creative responsive GUIs.

Pivy provides python bindings for Coin, a 3D graphics library with an Application Programming Interface based on the Open Inventor 2.1 API.

This is the Cython-coded accelerator module for PyOpenGL.

VisPy is a high-performance interactive 2D/3D data visualization library leveraging the computational power of modern Graphics Processing Units (GPUs) through the OpenGL library to display very large datasets.

Python-glcontext is a library providing an OpenGL implementation for ModernGL on multiple platforms.

PyOpenGL is the most common cross platform Python binding to OpenGL and related APIs. The binding is created using the standard ctypes library.

This package provides Python bindings for GLFW OpenGL application development library.

This package provides async versions of Kivy functions to avoid the callback-heavy mode of interaction typical in some Kivy applications.

This package provides a simplified scipy.signal.spectral module to do spectral analysis in Python.

This package contains colormaps for commonly-used oceanographic variables. Most of the colormaps started from matplotlib colormaps, but have now been adjusted using the viscm tool to be perceptually uniform.

Particle provides a pythonic interface to the Particle Data Group (PDG) particle data tables and particle identification codes, with extended particle information and extra goodies.

pyfma provides an implementation of fused multiply-add which computes (x*y) + z with a single rounding. This is useful for dot products, matrix multiplications, polynomial evaluations (e.g., with Horner's rule), Newton's method for evaluating functions, convolutions, artificial neural networks etc.

The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.

PyQtGraph is a Pure-python graphics library for PyQt5, PyQt6, PySide2 and PySide6. It is intended for use in mathematics, scientific or engineering applications.

Formulaic is a high-performance implementation of Wilkinson formulas for Python.

This package provides utilities and tools for open data science including tools for accessing data sets in Python.

Dask is a flexible parallel computing library for analytics. It consists of two components: dynamic task scheduling optimized for computation, and large data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers.