Showing 6 open source projects for "mac ipad update"

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  • 1
    Setfield.jl

    Setfield.jl

    Update deeply nested immutable structs

    Update deeply nested immutable structs. We plan to maintain Setfield.jl for a long time. We will however not add new features.
    Downloads: 6 This Week
    Last Update:
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  • 2
    Accessors.jl

    Accessors.jl

    Update immutable data

    The goal of Accessors.jl is to make updating immutable data simple. It is the successor of Setfield.jl.
    Downloads: 4 This Week
    Last Update:
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  • 3
    ProgressMeter.jl

    ProgressMeter.jl

    Progress meter for long-running computations

    ProgressMeter.jl is a lightweight Julia package that provides customizable progress bars for long-running loops and computations. It allows developers to track the progress of tasks with real-time visual feedback in the terminal, making it easier to monitor performance, debug slow operations, or report computational progress in user-facing applications.
    Downloads: 6 This Week
    Last Update:
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  • 4
    CompatHelper.jl

    CompatHelper.jl

    Automatically update the [compat] entries for your Julia dependencies

    CompatHelper.jl is a Julia package which keeps your Project.toml [compat] entries up to date.
    Downloads: 6 This Week
    Last Update:
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  • 5
    Revise.jl

    Revise.jl

    Automatically update function definitions in a running Julia session

    Revise.jl is a Julia package that automatically updates functions, types, and modules in a running Julia session when their source code changes. It significantly improves the development workflow by removing the need to restart the REPL or re-include files after edits. Revise is ideal for iterative coding, package development, and interactive exploration, enabling a fast and fluid programming experience.
    Downloads: 7 This Week
    Last Update:
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  • 6
    Functors.jl

    Functors.jl

    Parameterise all the things

    Functors.jl provides tools to express a powerful design pattern for dealing with large/ nested structures, as in machine learning and optimization. For large machine learning models, it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help manage complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimizer update step.
    Downloads: 6 This Week
    Last Update:
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