Search Results for "objects" - Page 2
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Showing 183 open source projects for "objects"
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Oceananigans.jl
Julia software for fast, friendly, flexible fluid dynamics on CPUs
Oceananigans is a fast, friendly, flexible software package for finite volume simulations of the nonhydrostatic and hydrostatic Boussinesq equations on CPUs and GPUs. It runs on GPUs (wow, fast!), though we believe Oceananigans makes the biggest waves with its ultra-flexible user interface that makes simple simulations easy, and complex, creative simulations possible. -
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deck.gl
WebGL2 powered visualization framework
...Users can quickly get impressive visual results with minimal effort by composing existing layers, or leveraging deck.gl's extensible architecture to address customer needs. deck.gl maps data (usually an array of JSON objects) into a stack of visual layers - e.g. icons, polygons, texts; and look at them with views: e.g. map, first-person, orthographic. deck.gl handles a number of challenges out of the box. Deck.gl is designed to be highly customizable. All layers come with flexible APIs to allow programmatic control of each aspect of the rendering. All core classes such are easily extendable by the users to address custom use cases. deck.gl is part of vis.gl, an OpenJS Foundation project. ... -
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Winston.jl
2D plotting for Julia
2D plotting for Julia. Winston offers an easy-to-use plot command to create figures without any fuss. After Winston is loaded by typing using Winston, the most basic plot can be created. -
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Arrow Julia
Official Julia implementation of Apache Arrow
This is a pure Julia implementation of the Apache Arrow data standard. This package provides Julia AbstractVector objects for referencing data that conforms to the Arrow standard. This allows users to seamlessly interface Arrow formatted data with a great deal of existing Julia code. -
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Pimcore
Open Source Data & Experience Management Platform
No matter if you're dealing with unstructured web documents or structured data for MDM/PIM, you define the UI design (web documents by a template and structured data with an intuitive graphical editor), Pimcore knows how to persist the data efficiently and optimized for fast access. Due to the framework approach, Pimcore is very flexible and adapts perfectly to your needs. Built on top of the well-known Symfony Framework you have a solid and modern foundation for your project. Benefit from... -
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Symfony PropertyInfo
Extracts information about PHP class' properties using metadata
Symfony PropertyInfo is a component that extracts information about the properties of PHP classes, such as their names, types, visibility, and documentation. It is particularly useful in scenarios like serialization, form generation, and validation, where understanding the structure of an object is essential. PropertyInfo can fetch data from PHPDoc annotations, reflection, and type hints, offering flexible integration with Symfony and other systems. -
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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#. -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase,... -
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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. -
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PhysicalConstants.jl
Collection of fundamental physical constants with uncertainties
PhysicalConstants.jl provides common physical constants. They are defined as instances of the new Constant type, which is a subtype of AbstractQuantity (from Unitful.jl package) and can also be turned into Measurement objects (from Measurements.jl package) at request. Constants are grouped into different submodules so that the user can choose different datasets as needed. Currently, 2014 and 2018 editions of CODATA recommended values of the fundamental physical constants are provided. -
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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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Cassandra Spark Connector
Apache Spark to Apache Cassandra connector
The Apache Cassandra Spark Connector allows Spark jobs (RDDs or DataFrames/Datasets) to read from and write to Cassandra tables. Compatible with Apache Cassandra (v2.1+), Spark 1.0–3.5, and Scala 2.11–2.13, it supports mapping Cassandra rows to Scala case classes, saving results back to Cassandra, and executing arbitrary CQL within Spark applications. -
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NCDatasets.jl
Load and create NetCDF files in Julia
NCDatasets allows one to read and create netCDF files. NetCDF data set and attribute list behave like Julia dictionaries and variables like Julia arrays. This package implements the CommonDataModel.jl interface, which means that the datasets can be accessed in the same way as GRIB files opened with GRIBDatasets.jl. -
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Positron
Positron, a next-generation data science IDE
Positron is a next-generation integrated development environment (IDE) created by Posit PBC (formerly RStudio Inc) specifically tailored for data science workflows in Python, R, and multi-language ecosystems. It aims to unify exploratory data analysis, production code, and data-app authoring in a single environment so that data scientists move from “question → insight → application” without switching tools. Built on the open-source Code-OSS foundation, Positron provides a familiar coding... -
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SPX
A simple & straight-to-the-point PHP profiling extension
...Thus, you are free of manually instrumenting your code (Ctrl-C a long running command line script is even supported). Using a dedicated browser extension or command line launcher. Multi metrics capable: 22 are currently supported (various time & memory metrics, included files, objects in use, I/O...). Able to collect data without losing context. For example Xhprof (and potentially its forks) aggregates data per caller / callee pairs, which implies the loss of the full call stack and forbids timeline or Flamegraph based analysis. -
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Weft
Task management, but AI agents do your tasks
...Instead of just listing to-dos, Weft lets users describe work and attach intelligent agents that read context, perform actions, and request approvals before committing state changes, making task execution partly automated without sacrificing control. It runs entirely on Cloudflare’s platform using Workers, Durable Objects, and Workflows, enabling scalable and persistent task state with minimal backend overhead. Users can set up parallel agents to handle multiple tasks at once and even schedule recurring jobs that trigger daily or weekly to keep workflows on track. Notifications inform the user when tasks are completed or when agent approvals are required, keeping oversight within reach. -
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JuliaConnectoR
A functionally oriented interface for calling Julia from R
...From a technical perspective, R data structures are serialized with an optimized custom streaming format, sent to a (local) Julia TCP server, and translated to Julia data structures by Julia. The results of function calls are likewise translated back to R. Complex Julia structures can either be used by reference via proxy objects in R or fully translated to R data structures. -
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luma.gl
High-performance Toolkit for WebGL-based data visualization
luma.gl is a GPU toolkit for the Web-focused primarily on data visualization use cases. luma.gl aims to provide support for GPU programmers that need to work directly with shaders and want a low abstraction API that remains conceptually close to the WebGPU and WebGL APIs. Unlike other common WebGL APIs, the developer can choose to use the parts of luma.gl that support their use case and leave the others behind. While generic enough to be used for general 3D rendering, luma.gl's mandate is... -
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Semiotic
A data visualization framework combining React & D3
...A guide for creating a line chart, timeseries, difference line, and line percents using XYFrame along with hover behavior, responsive dimensions, and styling. XYFrame takes lines as an object or an array of objects. Each object represents a line. Every object needs a coordinates property with the array of points for that line. The points will be rendered in the order of that array. You can use a key other than coordinates by changing the lineDataAccessor props. -
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vue-chartjs
Vue.js wrapper for Chart.js
...The mixins automatically create chartData as a prop or data. And add a watcher. If data has changed, the chart will update. However, keep in mind the limitations of vue and javascript for mutations on arrays and objects. It is important that you pass your options in a local variable named options! You can create your components in Vues single file components. -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects. -
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Machinery
Machinery is an asynchronous task queue/job queue
...You can use the current V2 in order to avoid having to import all dependencies for brokers and backends you are not using. Instead of factory, you will need to inject broker and backend objects to the server constructor. In order to consume tasks, you need to have one or more workers running. All you need to run a worker is a Server instance with registered tasks. Each worker will only consume registered tasks. For each task on the queue the Worker.Process() method will be run in a goroutine. Use the second parameter of server.NewWorker to limit the number of concurrently running Worker.Process() calls (per worker). ... -
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Vanilla.PDF
Cross-platform SDK for creating and modifying PDF documents
...Vanilla.PDF supports advanced PDF features such as adding CMS (PKCS#7) digital signatures, modifying content streams and metadata, and working with encryption and permissions based on standard PDF security models. It includes tools for parsing PDF internals like cross-reference tables and objects, providing fine-grained document analysis capabilities. The project is unit-tested with continuous integration pipelines, supporting sanitizers for enhanced code quality and stability. -
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JLD.jl
Saving and loading julia variables while preserving native types
...By comparison with "plain" HDF5, JLD files automatically add attributes and naming conventions to preserve type information for each object. For lossless storage of arbitrary Julia objects, the only other complete solution appears to be Julia's serializer, which can be accessed via the serialize and deserialize commands. However, because the serializer is also used for inter-process communication, long-term backward compatibility is currently uncertain. (The JLDArchives repository exists to test the compatibility of older JLD file formats.) ... -
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Sparx' EA - MDG for TRAK
MDG for Sparx' Enterprise Architect to Create TRAK arch. descriptions
Custom add-in (MDG technology) for Sparx Systems Enterprise Architect UML modelling tool (https://sparxsystems.com/products/ea/index.html) to create architecture descriptions using TRAK https://sf.net/projects/trak Provides: - the set of TRAK views that can be represented using UML and SysML . Each view display a custom toolbox palette with the objects and relationships that are needed for that TRAK view - relationships can be made directly from the objects on a view using the Quicklink feature which presents the allowed relationship(s) by TRAK between the pair of objects selected - a custom set of searches. When run these will list objects of a particular type (e.g. all Systems, all Enterprise Goals), potential quality problems (e.g. diagrams and objects without any description, objects not linked to any other), things of interest (e.g. open, closed concerns) and view-like results e.g. all structural relationships in the solution - model views to list object
