Showing 5 open source projects for "code framework"

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    MongoDB Atlas runs apps anywhere

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  • 1
    Genie.jl

    Genie.jl

    The highly productive Julia web framework

    Genie Framework includes all you need to quickly build production-ready web applications with Julia. Develop Julia backends, create beautiful web UIs, build data applications and dashboards, integrate with databases and set up high-performance web services and APIs. Genie Builder is a free VSCode plugin for quickly building Julia apps without writing frontend code.
    Downloads: 0 This Week
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  • 2
    ReTest.jl

    ReTest.jl

    Testing framework for Julia

    ReTest is a testing framework for Julia allowing defining tests in source files, whose execution is deferred and triggered on demand. This is useful when one likes to have definitions of methods and corresponding tests close to each other. This is also useful for code that is not (yet) organized as a package, and where one doesn't want to maintain a separate set of files for tests.
    Downloads: 0 This Week
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  • 3
    Agents.jl

    Agents.jl

    Agent-based modeling framework in Julia

    ...Overall this leads to ultra-fast model prototyping where even changing the space the agents live in is a matter of only a couple of lines of code.
    Downloads: 0 This Week
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  • 4
    BenchmarkTools.jl

    BenchmarkTools.jl

    A benchmarking framework for the Julia language

    BenchmarkTools makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results. This package is used to write and run the benchmarks found in BaseBenchmarks.jl. The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl.
    Downloads: 0 This Week
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    Fully Managed MySQL, PostgreSQL, and SQL Server

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  • 5
    Mocha.jl

    Mocha.jl

    Deep Learning framework for Julia

    Mocha.jl is a deep learning framework for Julia, inspired by the C++ Caffe framework. It offers efficient implementations of gradient descent solvers and common neural network layers, supports optional unsupervised pre-training, and allows switching to a GPU backend for accelerated performance. The development of Mocha.jl happens in relative early days of Julia. Now that both Julia and the ecosystem has evolved significantly, and with some exciting new tech such as writing GPU kernels...
    Downloads: 0 This Week
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