Search Results for "easy python decompiler" - Page 8
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Showing 1679 open source projects for "easy python decompiler"
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Qtile
A full-featured, hackable tiling window manager written in Python
A full-featured, hackable tiling window manager written and configured in Python. Optimize your workflow by configuring your environment to fit how you work. Efficiently use screen real-estate by automatically arranging windows with minimal visual cruft. Save your wrists from RSI by ditching the mouse and driving with the keyboard. Qtile is simple, small, and extensible. It's easy to write your own layouts, widgets, and built-in commands. Qtile is written and configured entirely in Python... -
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The Arcade Library
Easy to use Python library for creating 2D arcade games
Arcade is an easy-to-use Python library for creating 2D video games. It provides a modern and straightforward API, enabling developers to craft engaging games and graphical applications efficiently. Arcade supports rendering shapes, handling user input, and managing game physics, making it suitable for both beginners and experienced developers. -
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Pants Build System
The Pants Build System
Pants 2 is a fast, scalable, user-friendly build system for codebases of all sizes. It's currently focused on Python, Go, Java, Scala, Kotlin, Shell, and Docker, with support for other languages and frameworks coming soon. A lot of effort has gone into making Pants easy to adopt, easy to use and easy to extend. We're super excited to bring Pants' distinctive features to Go, Java, Python, Scala, Kotlin, and Shell users. Pants requires very minimal BUILD file metadata/boilerplate. It uses... -
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Requests
A simple, yet elegant, HTTP library.
Requests is the de facto HTTP library for Python—simple, elegant, and human-friendly. It wraps urllib3 to provide intuitive methods for sending HTTP/1.1 requests, handling sessions, cookies, redirects, authentication, proxies, and more. -
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Sanic
Async Python 3.6+ web server/framework
Build fast, run fast with Sanic! Sanic is a Python 3.6+ web server and web framework designed to go fast. It provides a way to get a highly performant HTTP server up and running fast, while also making it easy to build, expand, and eventually scale. Sanic aspires to be as simple as possible while delivering the performance that you require. It allows the usage of the async/await syntax added in Python 3.5, so your code is guaranteed to be non-blocking and speedy. It's also ASGI compliant, so... -
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LightRAG
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
LightRAG is a lightweight Retrieval-Augmented Generation (RAG) framework designed for efficient document retrieval and response generation. It is optimized for speed and lower resource consumption, making it ideal for real-time applications. -
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AutoGPTQ
An easy-to-use LLMs quantization package with user-friendly apis
AutoGPTQ is an implementation of GPTQ (Quantized GPT) that optimizes large language models (LLMs) for faster inference by reducing their computational footprint while maintaining accuracy. -
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Dataproc Templates
Dataproc templates and pipelines for solving simple in-cloud data task
Dataproc templates are designed to address various in-cloud data tasks, including data import/export/backup/restore and bulk API operations. These templates leverage the power of Google Cloud's Dataproc, supporting both Dataproc Serverless and Dataproc clusters. Google provides this collection of pre-implemented Dataproc templates as a reference and for easy customization. -
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Vocode
Build voice-based LLM agents. Modular + open source
Vocode is an open source library that makes it easy to build voice-based LLM apps. Using Vocode, you can build real-time streaming conversations with LLMs and deploy them to phone calls, Zoom meetings, and more. You can also build personal assistants or apps like voice-based chess. Vocode provides easy abstractions and integrations so that everything you need is in a single library. -
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OpenRLHF
An Easy-to-use, Scalable and High-performance RLHF Framework
OpenRLHF is an easy-to-use, scalable, and high-performance framework for Reinforcement Learning with Human Feedback (RLHF). It supports various training techniques and model architectures. -
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OpenLLMetry
Open-source observability for your LLM application
The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly. -
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bbox-visualizer
Make drawing and labeling bounding boxes easy as cake
Make drawing and labeling bounding boxes easy as cake. This package helps users draw bounding boxes around objects, without doing the clumsy math that you'd need to do for positioning the labels. It also has a few different types of visualizations you can use for labeling objects after identifying them. There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have full... -
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Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training... -
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Airweave
Airweave lets agents search any app
Airweave is an open-source platform that enables agents to semantically search across various applications, databases, and APIs. By transforming disparate data sources into a unified, searchable knowledge base, Airweave facilitates intelligent information retrieval through REST APIs or the MCP protocol. It's particularly useful for building AI agents that require access to structured and unstructured data across multiple platforms. -
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TorchMetrics
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 80+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. The module-based metrics contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices! Automatic accumulation over multiple batches. Automatic... -
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Ajenti 2
Ajenti Core and stock plugins
... and management. Ajenti 2 is easily extensible using Python. Plugin development is quick and pleasant with Ajenti APIs. Write your first plugin. Pleasant to look at, satisfying to click and accessible anywhere from tablets and mobile. Small memory footprint and CPU usage. Runs on low-end machines, wall plugs, routers and so on. -
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Django LMS
A learning management system using django web framework
django-lms is an open-source Learning Management System (LMS) built with Django and designed for ease of use and extensibility. It allows administrators to manage courses, lessons, quizzes, and users in an educational environment. The project includes a clean UI and backend tools to help educators create and track learning content. -
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Nautobot
Network Source of Truth & Network Automation Platform
.... With support for plugins and extensibility, Nautobot is used by enterprises to manage IP addresses, devices, circuits, and other networking components while integrating with automation tools like Ansible, Terraform, and custom Python scripts. -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing... -
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Alerta
Alerta monitoring system
Email was not designed to be used as an alert console. It is not a scalable solution when it comes to monitoring and alert visualization. A minimal installation of Alerta can be deployed quickly and easily as monitoring requirements and confidence grow. There are integrations available with Prometheus, Riemann, Nagios, Zabbix, netdata, Sensu, Pingdom and Cloudwatch. Integrating bespoke systems is easy using the API or command-line tool. Alerts are submitted in JSON format to an HTTP API. Alerts... -
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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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FLAML
A fast library for AutoML and tuning
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically. It frees users from selecting learners and hyperparameters for each learner. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources. It supports both classical machine learning models and deep neural networks. It is easy to customize or extend. Users can find... -
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redshift_connector
Amazon Redshift connector for Python
redshift_connector is the Amazon Redshift connector for Python. Easy integration with pandas and numpy, as well as support for numerous Amazon Redshift-specific features help you get the most out of your data. redshift_connector integrates with various open-source projects to provide an interface to Amazon Redshift. Please open an issue with our project to request new integrations or get support for a redshift_connector issue seen in an existing integration. Following the DB-API specification... -
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AI Chatbot Framework
Python chatbot framework with Natural Language Understanding
Building a chatbot can sound daunting, but it’s totally doable. AI Chatbot Framework is an AI powered conversational dialog interface built in Python. With this tool, it’s easy to create Natural Language conversational scenarios with no coding efforts whatsoever. The smooth UI makes it effortless to create and train conversations to the bot and it continuously gets smarter as it learns from conversations it has with people. AI Chatbot Framework can live on any channel of your choice... -
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MicroK8s
Single-package Kubernetes for developers, IoT and edge
Low-ops, minimal production Kubernetes, for devs, cloud, clusters, workstations, Edge and IoT. MicroK8s automatically chooses the best nodes for the Kubernetes datastore. When you lose a cluster database node, another node is promoted. No admin needed for your bulletproof edge. MicroK8s is small, with sensible defaults that ‘just work’. A quick install, easy upgrades and great security make it perfect for micro clouds and edge computing. As the publishers of MicroK8s, we deliver the world’s...
