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Showing 4 open source projects for "low level"

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  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    The database for AI-powered applications.

    MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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  • Create engaging surveys on your tablet or computer with ease. Icon
    Create engaging surveys on your tablet or computer with ease.

    Choose any of our carefully designed themes, or easily customize colors, fonts, and more to reflect your brand's true look and feel.

    Create great-looking surveys, forms, polls, voting, questionnaires, NPS, customer satisfaction, customer experience, employee satisfaction surveys... on your computer or tablet, customize the look of your survey however you like, & display collected data with eye-catching and insightful graphics.
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  • 1
    SwiftNIO

    SwiftNIO

    Network application framework for protocol servers and clients

    SwiftNIO is a cross-platform asynchronous event-driven network application framework for rapid development of maintainable high performance protocol servers & clients. Low-level protocol implementations are often a collection of ChannelHandlers that implement a protocol but still require the user to have a good understanding of SwiftNIO. Often, low-level protocol implementations will then be wrapped in high-level libraries with a nicer, more user-friendly API. High-level implementations are usually libraries that come with an API that doesn't expose SwiftNIO's ChannelPipeline and can therefore be used with very little (or no) SwiftNIO-specific knowledge. ...
    Downloads: 0 This Week
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  • 2
    Swift System

    Swift System

    Low-level system calls and types for Swift

    Swift System provides idiomatic Swift interfaces to low-level system calls and types, aiming to be the canonical home for these building blocks on all supported Swift platforms. It wraps platform details behind portable APIs while still allowing you to drop down to exact OS semantics when needed. The design follows Swift’s value semantics and protocol orientation to keep code predictable and testable.
    Downloads: 3 This Week
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  • 3
    SwiftTreeSitter

    SwiftTreeSitter

    Swift API for the tree-sitter incremental parsing system

    Swift API for the tree-sitter incremental parsing system. The SwiftTreeSitter target is a close match to the C runtime API. It adds only a few additional types to help support querying. It is fairly low-level, and there will be significant work to use it in a real project. SwiftTreeSitterLayer is an abstraction built on top of SwiftTreeSitter. It supports documents with nested languages and transparent querying across those nestings. It also supports asynchronous language resolution. While still low-level, SwiftTreeSitterLayer is easier to work with while also supporting more features.
    Downloads: 0 This Week
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  • 4
    Attabench

    Attabench

    Microbenchmarking app for Swift with nice log-log plots

    Attabench is a microbenchmarking app for macOS, designed to measure and visualize the performance of Swift code. This app is for microbenchmarking low-level algorithms with one degree of freedom (usually size). It works by repeatedly performing the same operation on random data of various sizes, while continuously charting the results in nice plots. Attabench's default log-log plots are ideal for seeing your algorithm's performance at a glance. Attabench was originally created to supply nice log-log charts for my dotSwift 2017 talk and Optimizing Collections book. ...
    Downloads: 0 This Week
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  • All-in-One Inspection Software Icon
    All-in-One Inspection Software

    flowdit is a connected worker platform tailored for industry needs in commissioning, quality, maintenance, and EHS management.

    Optimize Frontline Operations: Elevate Equipment Uptime, Operational Excellence, and Safety with Connected Teams and Data, Including Issue Capture and Corrective Action.
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