Shared functions library for Deker components
A Dash library with various components to make working with Dash easier
An unofficial library for discord components. Mirror only.
An unofficial library for py-cord components.
Support library for (pygame based) UI components
Recursively traverse subprojects and report libraries with vulnerable components in a format suitable for integration with other tools and human consumption.
Python library for easily interacting with trained machine learning models
Aspose.TeX for Python via .NET is a library that enables your Python applications to typeset TeX files and obtain output documents in file formats, such as XPS, PDF, JPEG, PNG, TIFF, and BMP. You can configure typesetting preferences to have your desired output design. It also offers numerous embedded fonts available for typesetting. With Aspose.TeX for Python, you can define your own interface for input gathering or choose to accept input from a local directory or from a ZIP archive.
An unofficial library for discord components.
An unofficial library for pycord components.
Communicating between loosely coupled components
This is the internal Scriptor library that the viur-scriptor utilizes. The API includes components for networking as well as parts related to the Scriptor's files.
This django library allows you to add React components into your django templates.
Button paginator for discord-components library.
Python library for easily interacting with trained machine learning models
Plotly dash React component UI library boilerplate
Python library for easily interacting with trained machine learning models
Storyblok Python library for Richtext component
Python library for easily interacting with trained machine learning models
Building Envelope Components Analysis Library
Standard UPYTL - Ultra Pythonic Template Language component library
dash_mqtt is a Dash component library for adding MQTT messaging functionality to your Dash apps.
Python library for easily interacting with trained machine learning models
A python library that makes is easy to consume bower components with python.
EstNLTK light — core components of the EstNLTK v1.6 library
A Wagtail app for wrapping a custom JavaScript library for frontend user components.
django files Library component
A tiny library inspired by frontend frameworks to experiment with the idea of composable automation scripts reduced to functions.
eventpy is a Python event library that provides tools that enable your application components to communicate with each other by dispatching events and listening for them. With eventpy you can easily implement signal/slot mechanism, or observer pattern.
An unofficial library for disnake components.
Reflex Wrapper for echarts-for-react library.
Python2 library for interfacing with Xiaomi miio components
Reusable Python components to be shared with some Python projects
Streamlit Component wrapper on top of JSConfetti library
Python library for easily interacting with trained machine learning models
A JavaScript library for initialising frontend user components.
Python library for easily interacting with trained machine learning models
Python library for easily interacting with trained machine learning models
Library of galaxy population modelling components
Python library for easily interacting with trained machine learning models
Python library for easily interacting with trained machine learning models
A simple library for learning of connected filters based on component trees
Python library for easily interacting with trained machine learning models
Library of tailwind styled components for Plotly Dash
Python library for easily interacting with trained machine learning models
Independent-component-analysis-based Blind audio source separation library.
Python library for easily interacting with trained machine learning models
Python library for easily interacting with trained machine learning models
PyTorch3D is FAIR's library of reusable components for deep Learning with 3D data. This is a customed version by MCG team
Python library for easily interacting with trained machine learning models