Showing 81-100 of 110 projects
A utility to remove the frame rate limit, change the FOV, and add widescreen support for Elden Ring.
Rocker breaks the limits of Dockerfile, providing a flexible and powerful tool for building and managing containerized applications.
A Python3 and C implementation of a Limit Order Book for high-frequency trading applications.
A rate limiter for ASP.NET Web API to prevent abuse and ensure fair usage.
A Redis module that provides rate limiting as a single command, useful for building scalable APIs.
Ravi is a JIT-enabled dialect of Lua with optional static typing for high-performance applications.
This repository provides a series of GPU optimization topics and CUDA kernel optimizations for high-performance computing.
Nepxion Discovery Guide is a comprehensive example for blue-green deployment, routing, rate limiting, and more on Spring Cloud.
A tool to block certain torrent client connections for qBittorrent, Transmission, and BitComet users.
This is an Android client for the 91Porn website, allowing users to bypass the 10-video daily limit and download videos.
A security audit tool for project dependencies, supporting local repos and containers, with a focus on compliance and supply chain security.
A simple semi-supervised learning method with limited data, useful for AI/ML developers.
A rate limiting extension for the Flask web framework, useful for building API-backed applications.
A C# game framework that can be used for non-game business development as well.
A lightweight, OpenAPI 3.0 and Protobuf-based microservice framework for Go developers.
A PHP-based VPN panel that allows managing users, limits, and online status
Simple, intentionally-limited versions of web3 protocols and applications.
A Rails library that provides validations for Active Storage attachments, including content type, size, and aspect ratio.
Enterprise-grade API gateway for monitoring and managing costs/rates across LLMs like OpenAI, Anthropic, and Azure OpenAI.
A Python library for semi-supervised learning, focused on improving model performance with limited labeled data.
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