Search Results for "linux-firmware" - Page 17
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Showing 3099 open source projects for "linux-firmware"
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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python-binance
Binance Exchange API python implementation for automated trading
This is an unofficial Python wrapper for the Binance exchange REST API v3. I am in no way affiliated with Binance, use at your own risk. Implementation of all General, Market Data and Account endpoints. Asyncio implementation. Testnet Support for Spot, Futures, and Vanilla Options. Simple handling of authentication. No need to generate timestamps yourself, the wrapper does it for you. Response exception handling. Websocket handling with reconnection and multiplexed connections. Symbol Depth... -
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Testinfra
Testinfra test your infrastructures
With Testinfra you can write unit tests in Python to test the actual state of your servers configured by management tools like Salt, Ansible, Puppet, Chef and so on. Testinfra aims to be a Serverspec equivalent in python and is written as a plugin to the powerful Pytest test engine. By default Testinfra launches tests on the local machines, but you can also test remotes systems using paramiko. If you have a lot of tests, you can use the pytest-xdist plugin to run tests using multiple... -
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IceCream
Never use print() to debug again
Do you ever use print() or log() to debug your code? Of course you do. IceCream, or ic for short, makes print debugging a little sweeter. With arguments, ic() inspects itself and prints both its own arguments and the values of those arguments. Just give ic() a variable or expression and you're done. ic() returns its argument(s), so ic() can easily be inserted into pre-existing code. Additionally, ic()'s output can be entirely disabled, and later re-enabled, with ic.disable() and ic.enable()... -
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ggshield
Detect and validate 500+ types of hardcoded secrets
GitGuardian’s ggshield is an open-source command-line interface (CLI) tool designed to help developers and security teams detect hardcoded secrets and sensitive credentials early in the development process, either locally or in CI/CD pipelines. It scans source code, configuration files, commit history, and other artifacts to automatically detect hundreds of different secret types — such as API keys, tokens, and passwords — helping prevent accidental leaks before they reach version control or... -
Loan management software that makes it easy.Bryt Software is ideal for lending professionals who are looking for a feature rich loan management system that is intuitive and easy to use. We are 100% cloud-based, software as a service. We believe in providing our customers with fair and honest pricing. Our monthly fees are based on your number of users and we have a minimal implementation charge.
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to... -
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simple-modern-uv
A minimal, modern Python project template
simple-modern-uv is a minimal yet production-ready Python project template that uses the uv toolchain to streamline dependency management, virtualenvs, and packaging. It aims to be “small but serious,” giving you the essentials—testing, linting, type checking, formatting, GitHub Actions—without burying you in boilerplate. The layout is opinionated around a pyproject.toml so configuration is centralized and easy to inspect. Defaults encourage good hygiene from day one, including reproducible... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems,... -
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pytype
A static type analyzer for Python code
pytype is a static type analyzer that checks and infers types for Python code without executing it, catching errors at “compile time” and generating actionable diagnostics. It grew alongside Python typing at Google and can understand both inline annotations and unannotated code via powerful inference. The tool consumes stub files (.pyi) for the standard library and third-party packages (from typeshed and its own built-ins), enabling accurate checks even in large, mixed-quality codebases.... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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DualPipe
A bidirectional pipeline parallelism algorithm
DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap... -
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Codespell
Check code for common misspellings
Codespell is a lightweight, open-source spell checker designed specifically for detecting and correcting common misspellings in source code, documentation, and text files. Unlike traditional spell checkers, Codespell is optimized for codebases, ensuring that it correctly identifies and suggests fixes for typographical errors without introducing false positives. It integrates easily into CI/CD pipelines, enabling developers to maintain clean and professional code and documentation. By... -
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Trame
Weave various components and technologies into a Web App
Developed by Kitware, trame is a Python-based framework that allows developers to create web applications with desktop-like functionality. It enables the integration of various components and technologies, such as VTK and ParaView, into web applications written entirely in Python. With best-in-class platforms at its core, trame provides complete control of 3D visualizations and data processing. Developers benefit from a write-once environment from trame. trame is an open source project... -
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Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This... -
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GEF
Modern experience for GDB with advanced debugging capabilities
GEF is a set of commands for x86/64, ARM, MIPS, PowerPC and SPARC to assist exploit developers and reverse-engineers when using old-school GDB. It provides additional features to GDB using the Python API to assist during the process of dynamic analysis and exploit development. Application developers will also benefit from it, as GEF lifts a great part of regular GDB obscurity, avoiding repeating traditional commands or bringing out the relevant information from the debugging runtime. -
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Papis
Powerful and highly extensible command-line based document
Papis is a powerful and highly extensible CLI document and bibliography manager. With Papis, you can search your library for books and papers, add documents and notes, import and export to and from other formats, and much much more. Papis uses a human-readable and easily hackable .yaml file to store each entry's bibliographical data. It strives to be easy to use while providing a wide range of features. And for those who still want more, Papis makes it easy to write scripts that extend its... -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
Run ML/AI or any type of workload with optimal performance and infrastructure cost. OptScale allows ML teams to multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing costs associated with cloud and infrastructure resources. OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run... -
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Kapitan
Generic templated configuration management for Kubernetes
Generic templated configuration management for Kubernetes, Terraform, and other things. Kapitan aims to be your one-stop configuration management solution to help you manage the ever-growing complexity of your configurations by enabling Platform Engineering and GitOps workflows. It streamlines complex deployments across heterogeneous environments while providing a secure and adaptable framework for managing infrastructure configurations. Kapitan's inventory-driven model, powerful templating... -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock... -
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VCR.py
Automatically mock your HTTP interactions to simplify testing
Automatically mock your HTTP interactions to simplify and speed up testing. VCR.py simplifies and speeds up tests that make HTTP requests. The first time you run code that is inside a VCR.py context manager or decorated function, VCR.py records all HTTP interactions that take place through the libraries it supports and serializes and writes them to a flat file (in yaml format by default). This flat file is called a cassette. When the relevant piece of code is executed again, VCR.py will read... -
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CTGAN
Conditional GAN for generating synthetic tabular data
CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may... -
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pre-commit-hooks
Some out-of-the-box hooks for pre-commit
Some out-of-the-box hooks for pre-commit. Using pre-commit-hooks with pre-commit. Instead of loading the files, simply parse them for syntax. A syntax-only check enables extensions and unsafe constructs which would otherwise be forbidden. Using this option removes all guarantees of portability to other yaml implementations. Detect symlinks which are changed to regular files with a content of a path that that symlink was pointing to. This usually happens on Windows when a user clones a... -
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Kubernetes Operator Pythonic Framework
A Python framework to write Kubernetes operators in just a few lines
Kopf —Kubernetes Operator Pythonic Framework— is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). The project was originally started as zalando-incubator/kopf in March 2019,... -
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Grab Framework Project
Web Scraping Framework
Grab is a python framework for building web scrapers. With Grab you can build web scrapers of various complexity, from simple 5-line scripts to complex asynchronous website crawlers processing millions of web pages. Grab provides an API for performing network requests and for handling the received content e.g. interacting with DOM tree of the HTML document. The single request/response API that allows you to build network request, perform it and work with the received content. The API is... -
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Flask-Caching
A caching extension for Flask
Flask-Caching is an extension to Flask that adds caching support for various backends to any Flask application. By running on top of cachelib it supports all of werkzeug’s original caching backends through a uniformed API. It is also possible to develop your own caching backend by subclassing flask_caching.backends.base.BaseCache class. Flask’s pluggable view classes are also supported. To cache them, use the same cached() decorator on the dispatch_request method. Using the same @cached...
