Search Results for "python::module" - Page 49
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7369 projects for "python::module" with 1 filter applied:
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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BentoCache
Bentocache is a robust multi-tier caching library for Node.js app
Bentocache is a flexible caching library for Python that supports multiple backends like memory, disk, and Redis. It offers decorators for easy function-level caching and is designed to be lightweight, extensible, and developer-friendly. Bentocache is well-suited for performance optimization in web apps, scripts, and data pipelines. -
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libplist
A library to handle Apple Property List format in binary or XML
A small portable C library to handle Apple Property List files in binary, XML, JSON, or OpenStep format. -
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Desktop Commander MCP
AI-powered MCP server for desktop file and terminal automation
Desktop Commander MCP is an advanced Model Context Protocol server designed to extend AI assistants with direct control over a user’s local machine, including the file system and terminal. It integrates with clients like Claude Desktop to enable AI-driven workflows such as editing files, executing commands, and automating development tasks from a single conversational interface. Desktop Commander MCP builds on top of an MCP filesystem server and enhances it with powerful search, replace, and... -
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Dependabot
Dependabot's core logic for creating update PR's
Dependabot-Core is the library at the heart of Dependabot security/version updates. Use it to generate automated pull requests updating dependencies for projects written in Ruby, JavaScript, Python, PHP, Dart, Elixir, Elm, Go, Rust, Java and .NET. It can also update git submodules, Docker files, and Terraform files. Check for the latest version of a dependency that's resolvable given a project's other dependencies. Generate updated manifest and lockfiles for a new dependency version. Generate PR descriptions that include the updated dependency's changelogs, release notes, and commits. -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.6V represents the latest generation of the GLM-V family and marks a major step forward in multimodal AI by combining advanced vision-language understanding with native “tool-call” capabilities, long-context reasoning, and strong generalization across domains. Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and... -
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PaSa
An advanced paper search agent powered by large language models
PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to... -
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel... -
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Flock
Flock is a workflow-based low-code platform for building chatbots
Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Libros de Programación en Español
List of programming books in Spanish for free
Libros de Programación en Español is a curated list of free programming books in Spanish, organized by topic and technology so learners can find high-quality materials without cost. The README is structured as an index with general programming books, followed by sections for specific languages such as JavaScript, TypeScript, Python, Ruby, Rust, PHP, Haskell, Go, Kotlin, Java, and R.Each entry includes the book title, author, and a link to the official or legal free version (PDF, HTML, eBook, etc.), focusing on resources that are legitimately available. Beyond languages, the list also covers frameworks and libraries (like React and Qwik), tools (such as Git), and databases (SQL), grouping them in separate sections for easier browsing. ... -
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MLX Engine
LM Studio Apple MLX engine
MLX Engine is the Apple MLX-based inference backend used by LM Studio to run large language models efficiently on Apple Silicon hardware. Built on top of the mlx-lm and mlx-vlm ecosystems, the engine provides a unified architecture capable of supporting both text-only and multimodal models. Its design focuses on high-performance on-device inference, leveraging Apple’s MLX stack to accelerate computation on M-series chips. The project introduces modular VisionAddOn components that allow image... -
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rust-by-practice
Challenging examples, exercises and projects
rust-by-practice is a hands-on, exercise-oriented learning resource for the Rust programming language that takes users beyond theory into real code challenges and practical patterns. Rather than simply listing Rust syntax or language features, it structures its content around progressively complex problems, each designed to illustrate a core Rust concept such as ownership, borrowing, lifetimes, traits, concurrency, zero-cost abstractions, and safe systems programming idioms. The repository... -
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ccapi
A header-only C++ library for interacting with crypto exchanges
A header-only C++ library for streaming market data and executing trades directly from cryptocurrency exchanges (i.e. the connections are between your server and the exchange server without anything in-between). -
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Google Cloud Platform Node.js Samples
Node.js samples for Google Cloud Platform products
Google Cloud Platform Node.js Samples repository is a large set of Node.js code examples that demonstrate how to build, deploy, and manage applications using Google Cloud Platform services. It mirrors the structure and purpose of the Python and Go sample repositories, providing developers with practical implementations that complement official documentation. The repository includes examples for a wide variety of services, such as Cloud Run, App Engine, storage systems, and APIs, along with full tutorial applications like the Bookshelf app that showcase end-to-end workflows. ... -
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Eidos
An extensible framework for Personal Data Management
...The platform integrates large language models to enable AI-assisted features such as summarizing documents, translating content, and interacting with stored data conversationally. It also includes an extension system that allows developers to create custom tools, scripts, and workflows using programming languages such as TypeScript or Python. -
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Requests for PHP
Requests for PHP is a humble HTTP request library
Requests is a HTTP library written in PHP, for human beings. It is roughly based on the API from the excellent Requests Python library. Requests is ISC Licensed (similar to the new BSD license) and has no dependencies, except for PHP 5.6+. Despite PHP’s use as a language for the web, its tools for sending HTTP requests are severely lacking. cURL has an interesting API, to say the least, and you can’t always rely on it being available. Sockets provide only low-level access and require you to build most of the HTTP response parsing yourself. ... -
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EnvPool
C++-based high-performance parallel environment execution engine
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines. -
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Fury
A blazing fast multi-language serialization framework
Fury is a blazing-fast multi-language serialization framework powered by jit(just-in-time compilation) and zero-copy, providing up to 170x performance and ultimate ease of use. Based on efficient JIT, struct deserialization can get 170x speed up compared to other serialization frameworks. In serialization scenarios, Fury can achieve a 100x speed up compared to traditional serialization frameworks. If you use Java clusters on a large scale, this will save a lot of computing resources. -
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QuantumOptics.jl
Library for the numerical simulation of closed as well as open quantum
QuantumOptics.jl is a numerical framework written in the Julia programming language that makes it easy to simulate various kinds of open quantum systems. It is inspired by the Quantum Optics Toolbox for MATLAB and the Python framework QuTiP. QuantumOptics.jl optimizes processor usage and memory consumption by relying on different ways to store and work with operators. The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics, not on the numerics. Every function in the framework has been severely tested with all tests and their code coverage presented on the framework's GitHub page. -
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CS-Books
Collection of computer science textbooks, learning materials
CS-Books is a massive curated collection of computer science textbooks, learning materials, and resource links that covers a wide range of topics from programming languages like C/C++ and Python to core subjects such as data structures, algorithms, operating systems, databases, networks, and design patterns. The repository aggregates over a thousand classic reference books and educational resources into a single index, making it a valuable starting point for self-learners, students preparing for technical interviews, and professionals deepening their knowledge across different CS domains. ... -
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LuaUnit
LuaUnit is a popular unit-testing framework for Lua
LuaUnit is a popular unit-testing framework for Lua, with an interface typical of xUnit libraries (Python unittest, Junit, NUnit, ...). It supports several output formats (Text, TAP, JUnit, etc.) that can be used directly or work with continuous integration platforms (Jenkins, Maven, etc.). LuaUnit may be installed as a rock or directly added to your project. For simplicity, LuaUnit is contained into a single file and has no external dependency. -
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glbinding
A C++ binding for the OpenGL API, generated using the gl.xml specifica
...It provides type-safe parameters, per-feature API headers, lazy function resolution, multi-context and multi-thread support, global and local function callbacks, meta information about the generated OpenGL binding and the OpenGL runtime, as well as tools and examples for quick-starting your projects. Based on the OpenGL API specification (gl.xml) glbinding is generated using Python scripts and templates that can be easily adapted to fit custom needs. -
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zfoo
Extremely fast enterprise server framework, can be used in RPC
...The framework supports single-server, microservice, cluster, and gateway deployment modes, making it adaptable to different production architectures. Its protocol system supports many languages, including Java, Kotlin, Scala, JavaScript, TypeScript, C#, Go, Python, Rust, C++, PHP, Ruby, Lua, Dart, Swift, and GDScript. zfoo also includes modules for networking, serialization, ORM, scheduling, configuration, and operational development workflows. It is especially useful for teams building high-performance game services or enterprise systems that need a unified backend foundation. -
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any-agent
A single interface to use and evaluate different agent frameworks
any-agent is a Python library that provides a unified interface for working with multiple agent frameworks, allowing developers to create, run, and evaluate AI agents without being locked into a single ecosystem. It abstracts the differences between frameworks such as LangChain, LlamaIndex, OpenAI Agents, and others, enabling users to switch between them with minimal configuration changes. -
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Sample GenLayer project
Includes the boilerplate code for a GenLayer use case implementation
...It includes a complete working example of a prediction market application, demonstrating how developers can structure, deploy, and test decentralized logic in a real-world scenario. The project integrates both backend contract development written in Python and frontend components built with modern frameworks, enabling a seamless full-stack development workflow. It emphasizes best practices such as environment configuration, modular architecture, and comprehensive testing, helping developers avoid common pitfalls when building blockchain-based applications. The boilerplate also includes a testing framework that simulates realistic contract interactions, ensuring reliability and correctness before deployment.