Search Results for "source code tracking"
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Showing 107 open source projects for "source code tracking"
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Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
Julia can track how many times, if any, each line of your code is run. This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. -
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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. -
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PythonCall & JuliaCall
Python and Julia in harmony
Bringing Python® and Julia together in seamless harmony. Call Python code from Julia and Julia code from Python via a symmetric interface. Simple syntax, so the Python code looks like Python and the Julia code looks like Julia. Intuitive and flexible conversions between Julia and Python: anything can be converted, you are in control. Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. bytes, array. array, numpy.ndarray) from Julia or Julia arrays... -
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LatticeQCD.jl
A native Julia code for lattice QCD with dynamical fermions in 4D
This code enables you to perform lattice QCD calculations! A native Julia code for Lattice QCD. -
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MacroTools.jl
MacroTools provides a library of tools for working with Julia code
MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system and code-walking tools that let you do deep transformations of code in a few lines. See the docs for more info. -
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Pluto.jl
Simple reactive notebooks for Julia plutojl.org
We are on a mission to make scientific computing more accessible and fun. Writing a notebook is not just about writing the final document, Pluto empowers the experiments and discoveries that are essential to getting there. -
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FourierFlows.jl
Tools for building fast, hackable, pseudospectral equation solvers
This software provides tools for partial differential equations on periodic domains using Fourier-based pseudospectral methods. A central intent of the software's design is also to provide a framework for writing new, fast solvers for new physical problems. The code is written in Julia. -
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Automa.jl
A julia code generator for regular expressions
Automa is a regex-to-Julia compiler. By compiling regex to Julia code in the form of Expr objects, Automa provides facilities to create efficient and robust regex-based lexers, tokenizers and parsers using Julia's metaprogramming capabilities. You can view Automa as a regex engine that can insert arbitrary Julia code into its input-matching process, which will be executed when certain parts of the regex match an input. -
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JuliaFormatter.jl
An opinionated code formatter for Julia
Width-sensitive formatter for Julia code. Inspired by gofmt, refmt, black, and prettier. Built with CSTParser. Sane defaults out of the box with options to customize. Supports YAS, Blue and SciML style guides. JuliaFormatter.toml configuration file to store options. JuliaFormatter exports format, format_file, format_text, and format_md. format_md has the same API as format_text but differ in that format_md expects the text content to be a Markdown document. See format_text docstring for... -
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OpenAPI
OpenAPI helper and code generator for Julia
This is the Julia library needed along with code generated by the OpenAPI generator to help define, produce and consume OpenAPI interfaces. The goal of OpenAPI is to define a standard, language-agnostic interface to REST APIs which allows both humans and computers to discover and understand the capabilities of the service without access to source code, documentation, or through network traffic inspection. -
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LanguageServer.jl
An implementation of the Microsoft Language Server Protocol
This package implements the Microsoft Language Server Protocol for the Julia programming language. Text editors with a client for the Language Server Protocol are able to make use of the Julia Language Server for various code editing features. -
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Finch.jl
Sparse tensors in Julia and more
Finch is a cutting-edge Julia-to-Julia compiler specially designed for optimizing loop nests over sparse or structured multidimensional arrays. Finch empowers users to write conventional for loops which are transformed behind-the-scenes into fast sparse code. -
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Infiltrator.jl
No-overhead breakpoints in Julia
This package provides the @infiltrate macro, which acts as a breakpoint with negligible runtime performance overhead. Note that you cannot access other function scopes or step into further calls. Use an actual debugger if you need that level of flexibility. Running code that ends up triggering the @infiltrate REPL mode via inline evaluation in VS Code or Juno can cause issues, so it's recommended to always use the REPL directly. When the infiltration point is hit, it will drop you into an... -
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oneAPI.jl
Julia support for the oneAPI programming toolkit.
Julia support for the oneAPI programming toolkit. oneAPI.jl provides support for working with the oneAPI unified programming model. The package is verified to work with the (currently) only implementation of this interface that is part of the Intel Compute Runtime, only available on Linux. This package is still under significant development, so expect bugs and missing features. -
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LineSearches.jl
Line search methods for optimization and root-finding
Line search methods for optimization and root-finding. This package provides an interface to line search algorithms implemented in Julia. The code was originally written as part of Optim, but has now been separated out to its own package. -
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KernelAbstractions.jl
Heterogeneous programming in Julia
KernelAbstractions (KA) is a package that enables you to write GPU-like kernels targetting different execution backends. KA is intended to be a minimal and performant library that explores ways to write heterogeneous code. -
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CausalInference.jl
Causal inference, graphical models and structure learning in Julia
Julia package for causal inference and analysis, graphical models and structure learning. This package contains code for the PC algorithm and the extended FCI algorithm, the score based greedy equivalence search (GES) algorithm, the Bayesian Causal Zig-Zag sampler and a function suite for adjustment set search. -
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JET.jl
An experimental code analyzer for Julia
JET employs Julia's type inference system to detect potential bugs and type instabilities. JET is tightly coupled to the Julia compiler, and so each JET release supports a limited range of Julia versions. See the Project.toml file for the range of supported Julia versions. The Julia package manager should install a version of JET compatible with the Julia version you are running. If you want to use JET on unreleased version of Julia where compatibility with JET is yet unknown, clone this git... -
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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. Drag and drop UI components such as text, sliders, plots, and data tables onto a canvas, and connect them to the variables in... -
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Gnuplot.jl
Julia interface to gnuplot
Gnuplot.jl is a simple package able to send both data and commands from Julia to an underlying gnuplot process. Its main purpose it to provide a fast and powerful data visualization framework, using an extremely concise Julia syntax. It also has automatic display of plots in Jupyter, Juno and VS Code. -
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Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
Flux is an elegant approach to machine learning. It's a 100% pure Julia stack and provides lightweight abstractions on top of Julia's native GPU and AD support. Flux makes the easy things easy while remaining fully hackable. Flux provides a single, intuitive way to define models, just like mathematical notation. Julia transparently compiles your code, optimizing and fusing kernels for the GPU, for the best performance. Existing Julia libraries are differentiable and can be incorporated... -
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IJulia.jl
Julia kernel for Jupyter
IJulia is a Julia-language backend (kernel) for Jupyter notebooks, allowing users to write and execute Julia code interactively in browser-based notebooks. It integrates seamlessly with Jupyter’s ecosystem, supporting markdown, plotting, multimedia, and inline output. IJulia is ideal for scientific computing, data analysis, and education, combining the power of Julia with the interactive capabilities of Jupyter. -
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Agents.jl
Agent-based modeling framework in Julia
Agents.jl is a pure Julia framework for agent-based modeling (ABM): a computational simulation methodology where autonomous agents react to their environment (including other agents) given a predefined set of rules. The simplicity of Agents.jl is due to the intuitive space-agnostic modeling approach we have implemented: agent actions are specified using generically named functions (such as "move agent" or "find nearby agents") that do not depend on the actual space the agents exist in, nor... -
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Franklin.jl
Static site generator. Simple, customisable, fast, maths with KaTeX
Franklin is a simple static site generator (SSG) oriented towards technical blogging (code, maths, ...), flexibility and extensibility. The base syntax is plain markdown with a few extensions such as the ability to define and use LaTeX-like commands in or outside of maths environments and the possibility to evaluate code blocks on the fly. -
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SciML Style Guide for Julia
A style guide for stylish Julia developers
The SciML Style Guide is a style guide for the Julia programming language. It is used by the SciML Open Source Scientific Machine Learning Organization. As such, it is open to discussion with the community. If the standard for code contributions is that every PR needs to support every possible input type that anyone can think of, the barrier would be too high for newcomers. Instead, the principle is to be as correct as possible to begin with, and grow the generic support over time. ...
