Search Results for "raspberry-gpio-python" - Page 17
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Showing 3454 open source projects for "raspberry-gpio-python"
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parallel-ssh
Asynchronous parallel SSH client library.
parallel-ssh is an asynchronous parallel SSH library designed for large-scale automation. It differentiates itself from alternatives, other libraries and higher-level frameworks like Ansible or Chef in several ways. -
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aws-encryption-sdk-cli
CLI wrapper around aws-encryption-sdk-python
This command line tool can be used to encrypt and decrypt files and directories using the AWS Encryption SDK. If you have not already installed cryptography, you might need to install additional prerequisites as detailed in the cryptography installation guide for your operating system. Installation using a python virtual environment is recommended to avoid conflicts between system packages and user-installed packages. For the most part, the behavior of aws-encryption-cli in handling files... -
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Mopidy
Mopidy is an extensible music server written in Python
Mopidy plays music from local disk, Spotify, SoundCloud, TuneIn, and more. You can edit the playlist from any phone, tablet, or computer using a variety of MPD and web clients. Vanilla Mopidy only plays music from files and radio streams. Through extensions, Mopidy can play music from cloud services like Spotify, SoundCloud, and TuneIn. With Mopidy's extension support, you can easily add backends for new music sources. Mopidy is a Python application that runs in a terminal or in the background... -
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tqdm
A Fast, Extensible Progress Bar for Python and CLI
tqdm is a fast, extensible progress bar for Python and CLI that enables you to see the progress of your loops in a clear and smart way. Simply wrap any iterable with tqdm(iterable), and sit back and watch that progress meter go! tqdm can be wrapped around any iterable, or executed as a module with pipes. Just by inserting tqdm (or python -m tqdm) between pipes will pass through all stdin to stdout while printing progress to stderr. tqdm does not require any dependencies, has a very low... -
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Frappe
Low code web framework for real world applications
Frappe is a full-stack, low-code web framework written in Python and JavaScript, used to build scalable and modular enterprise applications. It powers ERPNext and includes tools for REST APIs, user management, document modeling, workflows, and real-time updates. Frappe uses a "model-view-controller" approach with its own ORM and frontend system, enabling rapid development without sacrificing control or performance. -
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npm-clang-format-node
Node repackaging(wrapping) of the LLVM Clang's clang-format
A Node.js package that integrates the clang-format tool for formatting C, C++, and JavaScript code, enhancing code quality and consistency. -
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Database-backed Periodic Tasks
Celery Periodic Tasks backed by the Django ORM
This extension enables you to store the periodic task schedule in the database. The periodic tasks can be managed from the Django Admin interface, where you can create, edit and delete periodic tasks and how often they should run. Usage and installation instructions for this extension are available from the Celery documentation. If you change the Django TIME_ZONE setting your periodic task schedule will still be based on the old timezone. To create a periodic task executing at an interval... -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily... -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To run... -
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Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together... -
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SeleniumBase
A framework for browser automation and testing with Selenium
SeleniumBase automatically handles common WebDriver actions such as launching web browsers before tests, saving screenshots during failures, and closing web browsers after tests. SeleniumBase lets you customize test runs from the command line. SeleniumBase uses simple syntax for commands. pytest includes automatic test discovery. If you don't specify a specific file or folder to run, pytest will automatically search through all subdirectories for tests to run. No More Flaky Tests!... -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy... -
13
cuDF
GPU DataFrame Library
... with conda (miniconda, or the full Anaconda distribution) from the rapidsai channel. cuDF is supported only on Linux, and with Python versions 3.7 and later. The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. -
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Easy3D
Efficient library for processing 3D data
Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data. -
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PyObjC
The Python <-> Objective-C Bridge with bindings for macOS frameworks
PyObjC is a Python-Objective-C bridge that allows Python scripts to interact with macOS Cocoa libraries. It enables developers to write native macOS apps entirely in Python by accessing Objective-C APIs. -
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SickChill
Less rage, more chill
Automatic Video Library Manager for TV shows. It watches for new episodes of your favorite shows, and when they are posted it does its magic. Select the show you want to grab, add it, and let SickChill handle the rest. See what SickChill holds in store for you. SickChill has a nice calendar that allows you to know what you will see next. It watches for new episodes of your favorite shows, and when they are posted it does its magic: automatic torrent/nzb searching, downloading, and processing... -
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databooks
A CLI tool to reduce the friction between data scientists
databooks is a package to ease the collaboration between data scientists using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and resolution of git conflicts when encountered. Simply specify the paths for notebook files to remove metadata. By doing so, we can already avoid many of the conflicts. Specify the paths for notebook files with conflicts to be fixed. Then, databooks finds the source notebooks that caused the conflicts and compares them (so no... -
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NumCpp
C++ implementation of the Python Numpy library
A Templatized Header Only C++ Implementation of the Python NumPy Library. The main data structure in NumCpp is the NdArray. It is inherently a 2D array class, with 1D arrays being implemented as 1xN arrays. There is also a DataCube class that is provided as a convenience container for storing an array of 2D NdArrays, but it has limited usefulness past a simple container. -
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Spotless
Keep your code spotless
Spotless is a tool for formatting and enforcing consistent code style in various languages, streamlining code quality across teams. -
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SENAITE LIMS
SENAITE Meta Package
SENAITE is a beautiful trigonal, oil-green to greenish-black crystal, with almost the hardness of a diamond. Although the crystal is described with a complex formula, it still has clear and straight shapes. Therefore, it reflects nicely the complexity of the LIMS, while providing a modern, intuitive, and friendly UI/ UX. Amongst other functionalities, SENAITE comes with highly-customizable workflows to drive users through the analytical process, easy-to-use UI for data registration,... -
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EasyAuth
Create a centralized Authentication and Authorization token server
Create a centralized Authentication and Authorization token server. Easily secure FastAPI endpoints based on Users, Groups, Roles or Permissions with very little database usage. Centralized Auth - Single location for Users & Permissions to share across apps. Granular Endpoint Security - Verify user identity, and define explicitly who and what each user or group of users may access. Admin GUI - easy management of users, permissions, tokens, OAuth, and more! Advanced JWT - Token Based Client... -
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DVC
Data Version Control | Git for Data & Models
DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets,... -
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Flask App Builder
Simple and rapid application development framework
Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. Automatic permissions lookup, based on exposed methods. Inserts on the Database all the detailed permissions possible on your application. Public (no authentication needed) and Private permissions. Role-based permissions. Authentication support for OpenID, Database and LDAP. Support for self-user registration. Automatic,... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
... memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
