Search Results for "data structures c" - Page 2
Sort By:
Showing 59 open source projects for "data structures c"
View related business solutions-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
1
Clustering.jl
A Julia package for data clustering
Methods for data clustering and evaluation of clustering quality. -
2
MATLAB.jl
Calling MATLAB in Julia through MATLAB Engine
The MATLAB.jl package provides an interface for using MATLAB® from Julia using the MATLAB C api. In other words, this package allows users to call MATLAB functions within Julia, thus making it easy to interoperate with MATLAB from the Julia language. You cannot use MATLAB.jl without having purchased and installed a copy of MATLAB® from MathWorks. This package is available free of charge and in no way replaces or alters any functionality of MathWorks's MATLAB product. -
3
DataFramesMeta.jl
Metaprogramming tools for DataFrames
Metaprogramming tools for DataFrames.jl objects to provide more convenient syntax. DataFrames.jl has the functions select, transform, and combine, as well as the in-place select! and transform! for manipulating data frames. DataFramesMeta.jl provides the macros @select, @transform, @combine, @select!, and @transform! to mirror these functions with more convenient syntax. Inspired by dplyr in R and LINQ in C#. -
4
GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
JDF.jl
Julia DataFrames serialization format
...JDF.jl is a pure-Julia solution and there are a lot of ways to do nifty things like compression and encapsulating the underlying struture of the arrays that's hard to do in R and Python. E.g. Python's numpy arrays are C objects, but all the vector types used in JDF are Julia data types. -
6
HiGHS.jl
Julia wrapper for the HiGHS solver
HiGHS.jl is a wrapper for the HiGHS solver. -
7
GLM.jl
Generalized linear models in Julia
GLM.jl is a Julia package for fitting linear and generalized linear models (GLMs) with a syntax and functionality familiar to users of R or other statistical environments. It is part of the JuliaStats ecosystem and is tightly integrated with StatsModels.jl for formula handling, and Distributions.jl for specifying error families. The package supports modeling through both formula-based (e.g. @formula) and matrix-based interfaces, allowing both high-level convenience and low-level control.... -
8
VimBindings.jl
Vim bindings for the Julia REPL
Vim bindings for the Julia REPL. VimBindings.jl is a Julia package which brings vim emulation directly to the Julia REPL. -
9
Julia VS Code
Julia extension for Visual Studio Code
This VS Code extension provides support for the Julia programming language. We build on Julia’s unique combination of ease-of-use and performance. Beginners and experts can build better software more quickly, and get to a result faster. With a completely live environment, Julia for VS Code aims to take the frustration and guesswork out of programming and put the fun back in. A hybrid “canvas programming” style combines the exploratory power of a notebook with the productivity and static... -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
-
10
NFFT
The official NFFT library repository
NFFT is a software library, written in C, for computing non-equispaced fast Fourier transforms and related variations. -
11
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. -
12
GLFW.jl
Julia interface to GLFW, a multi-platform library for creating windows
Julia interface to GLFW 3, a multi-platform library for creating windows with OpenGL or OpenGL ES contexts and receiving many kinds of input. GLFW has native support for Windows, OS X and many Unix-like systems using the X Window System, such as Linux and FreeBSD. -
13
ImplicitGlobalGrid.jl
Distributed parallelization of stencil-based GPU and CPU applications
ImplicitGlobalGrid is an outcome of a collaboration of the Swiss National Supercomputing Centre, ETH Zurich (Dr. Samuel Omlin) with Stanford University (Dr. Ludovic Räss) and the Swiss Geocomputing Centre (Prof. Yuri Podladchikov). It renders the distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid almost trivial and enables close to ideal weak scaling of real-world applications on thousands of GPUs [1, 2, 3]. ImplicitGlobalGrid relies on the... -
14
jlrs
Julia bindings for Rust
jlrs is a crate that provides access to most of the Julia C API, it can be used to embed Julia in Rust applications and to use functionality it provides when writing ccallable functions in Rust. Currently, this crate is only tested in combination with Julia 1.6 and 1.9, but also supports Julia 1.7, 1.8, and 1.10. Using the current stable version is highly recommended. The minimum supported Rust version is currently 1.65. Julia must be installed before jlrs can be used, jlrs is compatible... -
15
ParallelStencil.jl
Package for writing high-level code for parallel stencil computations
ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array... -
16
QML
Build Qt6 QML interfaces for Julia programs
This package provides an interface to Qt6 QML (and to Qt5 for older versions). It uses the CxxWrap package to expose C++ classes. Current functionality allows interaction between QML and Julia using Observables, JuliaItemModels and function calling. There is also a generic Julia display, as well as specialized integration for image drawing, GR plots and Makie. -
17
LibPQ.jl
A Julia wrapper for libpq
LibPQ.jl is a Julia wrapper for the PostgreSQL libpq C library. -
18
LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
19
LIBSVM.jl
LIBSVM bindings for Julia
LIBSVM bindings for Julia. This is a Julia interface for LIBSVM and for the linear SVM model provided by LIBLINEAR. Supports all LIBSVM models: classification C-SVC, nu-SVC, regression: epsilon-SVR, nu-SVR and distribution estimation: one-class SVM. Model objects are represented by Julia-type SVM which gives you easy access to model features and can be saved e.g. as JLD file. -
20
PeriodicTable.jl
Periodic Table for Julians
...PeriodicTable.jl provides a Julia interface to a small database of element properties for all of the elements in the periodic table. In particular PeriodicTable exports a global variable called elements, which is a collection of Element data structures. -
21
PyCall.jl
Package to call Python functions from the Julia language
...You can import arbitrary Python modules from Julia, call Python functions (with automatic conversion of types between Julia and Python), define Python classes from Julia methods, and share large data structures between Julia and Python without copying them. -
22
Bayesian Julia
Bayesian Statistics using Julia and Turing
Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from... -
23
IndexedTables.jl
Flexible tables with ordered indices
IndexedTables provides tabular data structures where some of the columns form a sorted index. It provides the backend to JuliaDB, but can be used on its own for efficient in-memory data processing and analytics. -
24
Mousetrap.jl
Finally, a GUI Engine made for Julia
Mousetrap is a GUI library designed for Julia. It fully wraps GTK4 (which is written in C), vastly simplifying its interface to improve ease of use without sacrificing flexibility. It aims to give developers of all skill levels the tools to start creating complex GUI applications with little time and effort while taking full advantage of Julia's idiosyncrasies. -
25
ThinkJulia.jl
Port of the book Think Python to the Julia programming language
...It provides a comprehensive introduction to programming and computational thinking using Julia’s modern, high-performance features. The book is structured to gradually teach core concepts such as variables, control flow, functions, recursion, object-oriented programming, and data structures, while offering hands-on exercises to reinforce each topic. 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.
