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Showing 39 open source projects for "project-ascp"
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Pkg Julia
Package manager for the Julia programming language
...In Pkg, since each project maintains its own independent set of package versions, you’ll never have this problem again. Moreover, if you check out a project on a new system, you can simply materialize the environment described by its manifest file and immediately be up and running. -
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CondaPkg.jl
Add Conda dependencies to your Julia project
Add Conda dependencies to your Julia project. This package is a lot like Pkg from the Julia standard library, except that it is for managing Conda packages. Conda dependencies are defined in CondaPkg.toml, which is analogous to Project.toml. CondaPkg will install these dependencies into a Conda environment specific to the current Julia project. Hence dependencies are isolated from other projects or environments. -
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DrWatson.jl
The perfect sidekick to your scientific inquiries
DrWatson is a scientific project assistant software. It helps people manage their scientific projects (or any project for that matter). Specifically, it is a Julia package created to help people "deal" with their simulations, simulation parameters, where files are saved, experimental data, scripts, existing simulations, project source code, establishing reproducibility, and in general, their scientific projects. -
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PkgTemplates.jl
Create new Julia packages, the easy way
PkgTemplates.jl is a Julia package that automates the creation of new Julia packages by generating a project scaffold with common best practices. It helps users quickly set up reproducible project structures with Git integration, CI configuration, testing frameworks, documentation, and more. By using customizable templates, PkgTemplates streamlines package development and enforces consistency across Julia projects. -
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Model Zoo
Please do not feed the models
...The repository provides ready-to-run implementations across multiple domains, including computer vision, natural language processing, and reinforcement learning. Each model is organized into its own project folder with pinned package versions, ensuring reproducibility and stability. The examples serve both as educational tools for learning Flux and as practical starting points for building new models. GPU acceleration is supported for most models through CUDA integration, enabling efficient training on compatible hardware. With community contributions encouraged, the Model Zoo acts as a hub for sharing and exploring diverse machine learning applications in Julia. -
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VIMKiller
Exiting VIM is hard; sometimes we need to take drastic measures
...The project includes CAD files for the enclosure, Arduino code, and setup instructions, making it possible to build your own version. While conceived as a joke originating from a Julia Slack discussion, the device does actually work, blending satire with practical execution. Though sunset in favor of VIMKiller RECHARGED, the original project remains a lighthearted reminder of how software frustrations can inspire inventive, if unconventional, solutions. -
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AbstractAlgebra.jl
Generic abstract algebra functionality in pure Julia
AbstractAlgebra is a pure Julia package for computational abstract algebra. It grew out of the Nemo project and provides all of the abstract types and generic implementations that Nemo relies on. It was originally developed by William Hart, Tommy Hofmann, Fredrik Johansson and Claus Fieker with contributions from others. Current maintainers are Claus Fieker, Tommy Hofmann and Max Horn. -
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Oscar.jl
A comprehensive open source computer algebra system for computations
Welcome to the OSCAR project, a visionary new computer algebra system that combines the capabilities of four cornerstone systems: GAP, Polymake, Antic and Singular. OSCAR requires Julia 1.6 or newer. In principle it can be installed and used like any other Julia package; doing so will take a couple of minutes. A comprehensive open source computer algebra system for computations in algebra, geometry, and number theory. -
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HiGHS.jl
Julia wrapper for the HiGHS solver
HiGHS.jl is a wrapper for the HiGHS solver. -
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DynamicalSystems.jl
Award winning software library for nonlinear dynamics timeseries
DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms... -
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Bukdu.jl
Bukdu is a web development framework for Julia
Bukdu.jl is a web development framework for Julia. -
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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. -
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Hecke.jl
Computational algebraic number theory
Hecke is a software package for algebraic number theory maintained by Claus Fieker, Tommy Hofmann and Carlo Sircana. It is written in julia and is based on the computer algebra packages Nemo and AbstractAlgebra. Hecke is part of the OSCAR project and the development is supported by the Deutsche Forschungsgemeinschaft DFG within the Collaborative Research Center TRR 195. -
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TimerOutputs.jl
Formatted output of timed sections in Julia
TimerOutputs.jl is a lightweight Julia package that provides a structured way to measure and report the execution time of different parts of code. It is particularly useful for performance profiling in scientific computing, allowing developers to annotate sections of code and generate readable timing summaries. TimerOutputs.jl supports nested timers and formatted output to both terminal and files, helping users easily identify bottlenecks in their programs. -
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Braket.jl
Experimental Julia implementation of the Amazon Braket SDK
Braket.jl is not an officially supported AWS product. This package is a Julia implementation of the Amazon Braket SDK allowing customers to access Quantum Hardware and Simulators. This is experimental software, and support may be discontinued in the future. For a fully supported SDK, please use the Python SDK. We may change, remove, or deprecate parts of the API when making new releases. Please review the CHANGELOG for information about changes in each release. -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
...These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for the current project, and other projects that wish to use MKL for FFTs should also set that same preference. Note further that MKL provides only a subset of the functionality provided by FFTW. -
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SCIP.jl
Julia interface to SCIP solver
SCIP.jl is a Julia interface to the SCIP solver. This wrapper is maintained by the SCIP project with the help of the JuMP community. -
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PackageCompiler
Compile your Julia Package
Julia is, in general, a "just-barely-ahead-of-time" compiled language. When you call a function for the first time, Julia compiles it for precisely the types of arguments given. This can take some time. All subsequent calls within that same session use this fast compiled function, but if you restart Julia you lose all the compiled work. PackageCompiler allows you to do this work upfront — further ahead of time — and store the results for a lower latency startup. You can save loaded packages... -
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ArviZ.jl
Exploratory analysis of Bayesian models with Julia
ArviZ.jl (pronounced "AR-vees") is a Julia package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, model checking, comparison and diagnostics. -
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MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
...It uses symbolic expressions for systems of partial differential equations as defined with ModelingToolkit.jl, and Interval from DomainSets.jl to define the space(time) over which the simulation runs. This project is under active development, therefore the interface is subject to change. The docs will be updated to reflect any changes, please check back for current usage information. -
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OpenAPI
OpenAPI helper and code generator for Julia
...Similar to what interfaces have done for lower-level programming, OpenAPI removes the guesswork in calling the service. Check out OpenAPI-Spec for additional information about the OpenAPI project, including additional libraries with support for other languages and more. -
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Query.jl
Query almost anything in julia
Query is a package for querying julia data sources. It can filter, project, join and group data from any iterable data source, including all the sources supported in IterableTables.jl. One can for example query any of the following data sources: any array, DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, Temporal, TypedTables and DifferentialEquations (any DESolution). -
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Comonicon
Your best CLI generator in JuliaLang
Roger's magic book for command line interfaces. -
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FastAI.jl
Repository of best practices for deep learning in Julia
...From loading datasets and creating data preprocessing pipelines to training, FastAI.jl takes the boilerplate out of deep learning projects. It equips you with reusable components for every part of your project while remaining customizable at every layer. FastAI.jl comes with support for common computer vision and tabular data learning tasks, with more to come. -
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ThinkJulia.jl
Port of the book Think Python to the Julia programming language
...By combining clear explanations with practical examples, the project helps both beginners and experienced programmers transition to Julia. The material emphasizes not only writing code but also reasoning about algorithms and problem-solving. Since it is freely available, learners and educators can use, adapt, and contribute to the content, making it a valuable resource for self-study or classroom use.
