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Showing 14 open source projects for "syntax"
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Securing the Cloud Made EasyDesigned for organizations operating in the cloud who need complete, centralized visibility of their entire cloud estate and want more time and resources dedicated to remediating the actual risks that matter, Orca Security is an agentless cloud Security Platform that provides security teams with 100% coverage their entire cloud environment.
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Monitoring, Securing, Optimizing 3rd party scriptsc/side is crawling many sites to get ahead of new attacks. c/side is the only fully autonomous detection tool for assessing 3rd party scripts. We do not rely purely on threat feed intel or easy to circumvent detections. We also use historical context and AI to review the payload and behavior of scripts.
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dplyr
dplyr: A grammar of data manipulation
dplyr is an R package that provides a consistent and intuitive grammar for data manipulation, enabling users to filter, arrange, summarize, and transform data efficiently. Part of the tidyverse ecosystem, dplyr simplifies complex data operations through a clear and readable syntax, whether working with data frames, tibbles, or databases. It is widely used in data science and statistical analysis workflows. -
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blavaan
An R package for Bayesian structural equation modeling
blavaan is a free, open-source R package for Bayesian latent variable analysis. It relies on JAGS and Stan to estimate models via MCMC. The blavaan functions and syntax are similar to lavaan. The development version of blavaan (containing updates not yet on CRAN) can be installed via the command provided in the documentation. Compilation is required; this may be a problem for users who currently rely on a binary version of blavaan from CRAN. The blavaan package depends on the lavaan package for model specification and for some computations. ... -
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lintr
Static Code Analysis for R
lintr is a static code analysis tool for R that identifies syntax errors, style inconsistencies, and other potential issues in R scripts and packages. It supports customizable lint rules and integrates with many editors to provide realtime feedback and enforce coding standards (e.g., tidyverse style). -
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RStudio Cheatsheets
Curated collection of official cheat sheets for data science tools
The cheatsheets repository from RStudio is a curated collection of official cheat sheets for R, RStudio, the tidyverse, Shiny, and related data science tools. Each cheat sheet is a single (or double) page PDF that condenses important syntax, functions, workflows, and best practices into a visually organized format ideal for quick reference. The repository contains source files (R Markdown or LaTeX) that generate the cheat sheets, version history, and metadata (title, author, description) for each. It covers topics such as data wrangling, data import, modeling, visualization, RStudio IDE shortcuts, Shiny development, and the tidyverse suite (dplyr, ggplot2, tidyr, purrr). ... -
The CI/CD Platform built for Mobile DevOpsSave time, money, and developer frustration with fast, flexible, and scalable mobile CI/CD that just works. Whether you swear by native or would rather go cross-platform, we have you covered. From Swift to Objective-C, Java to Kotlin, as well as Xamarin, Cordova, Ionic, React Native, and Flutter: Whatever you choose, we will automatically configure your initial workflows and have you building in minutes.
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Introduction to Zig
An open, technical and introductory book for the Zig programming lang
This is the official repository for the book "Introduction to Zig: a project-based Book", written by Pedro Duarte Faria. To know more about the book, check out the About this book section below. You can read the current version of the book in your web browser. The book is built using the publishing system Quarto in conjunction with a little bit of R code (zig_engine.R), which is responsible for calling the Zig compiler to compile and run the Zig code examples. -
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magrittr
Improve the readability of R code with the pipe
magrittr introduces the pipe operator (%>%) and related functional utilities into R. It underlies the powerful piped syntax widely adopted in tidyverse workflows by enabling left-hand argument passing and providing helpers like compound assignment pipes and exposition pipes. -
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ggpubr
'ggplot2' Based Publication Ready Plots
ggpubr is an R package that provides easy-to-use wrapper functions around ggplot2 to create publication-ready visualizations with minimal code. It streamlines plot creation for researchers and analysts, allowing features such as statistical annotation, theme customization, and plot arrangement with fewer lines of code. -
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reprex
Render bits of R code for sharing, e.g., on GitHub or StackOverflow
reprex is an R package (from the tidyverse / Posit ecosystem) that helps users make reproducible examples (reprexes) of R code: self-contained, shareable, minimal examples capturing an issue or showing desired behavior. It formats code and its output nicely (often using Markdown or syntax appropriate to posting on forums, GitHub, StackOverflow etc.), handles dependencies, session info, etc. The goal is to make debugging, asking for help, or demonstrating code easier through rigorous reproducible examples. Get slightly different Markdown, optimized for Slack messages. Handles dependencies (e.g. load required libraries inside the reprex) so that code example is self-contained. ... -
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brms
brms R package for Bayesian generalized multivariate models using Stan
brms is an R package by Paul Bürkner which provides a high-level interface for fitting Bayesian multilevel (i.e. mixed effects) models, generalized linear / non-linear / multivariate models using Stan as the backend. It allows R users to specify complex Bayesian models using formula syntax similar to lme4 but with far more flexibility (distributions, link functions, hierarchical structure, nonlinear terms, etc.). It supports model diagnostics, posterior predictive checking, model comparison, custom priors, and advanced features such as distributional regression. -
SOCRadar Extended Threat Intelligence PlatformSOCRadar Extended Threat Intelligence, a natively single platform from its inception that proactively identifies and analyzes cyber threats with contextual and actionable intelligence.
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data.table
Extends base R’s data for high-performance data manipulation
data.table is an R package that extends base R’s data.frame for high-performance data manipulation. It offers concise syntax, blazing speed, and memory-efficient operations. It supports fast file reading/writing, joins, grouping, reshaping, and updates by reference. It is heavily used in large data workflows, big data in R, production pipelines, etc. Extremely efficient grouping/aggregation/summarization; can handle very large datasets (hundreds of millions to billions of rows) in memory (if available). ... -
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box
Write reusable, composable and modular R code
...The idea is to let users structure code in a more modular, composable way, without needing every reusable component to be a full CRAN-style package. It also provides a cleaner syntax for importing functions or modules (via box::use) that allows scoping control and avoids global pollution. Such modules can be stored in a central module search path (configured via options('box.path')) analogous to the R package library, or locally in individual projects. Let’s assume the module we just defined is stored in a file hello_world.r inside a directory mod, which is inside the module search path. -
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DiagrammeR
Graph and network visualization using tabular data in R
DiagrammeR is an R package to create, manipulate, and visualize network graphs, flowcharts, diagrams, and more using Graphviz and Mermaid syntax. Integrates with RMarkdown and Shiny apps, supports node/edge traversal, and graph analysis algorithms, making it ideal for documenting processes, causal relationships, or data pipelines. -
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tidyverse
Easily install and load packages from the tidyverse
tidyverse is a meta‑package that installs and loads a cohesive suite of R packages designed for data science, sharing underlying design principles, grammar, and data structures. Core components include ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, forcats, and more. It promotes tidy data workflows and consistency across tasks. -
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rethinking
Statistical Rethinking course and book package
This R package accompanies Richard McElreath’s Statistical Rethinking (2nd edition), offering utilities to fit and compare Bayesian models using both MAP estimation (quap) and Hamiltonian Monte Carlo via RStan (ulam). It supports specifying models via explicit distributional assumptions, providing flexibility for advanced statistical workflows.
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