JuliaConnectoR VS drake

Compare JuliaConnectoR vs drake and see what are their differences.

JuliaConnectoR

A functionally oriented interface for calling Julia from R (by stefan-m-lenz)
Julia r-package Interoperability R
Source Code
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drake

An R-focused pipeline toolkit for reproducibility and high-performance computing (by ropensci)
Reproducibility high-performance-computing R Data Science drake Makefile Pipeline Workflow reproducible-research Rstats r-package ropensci peer-reviewed
Source Code
docs.ropensci.org
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JuliaConnectoR drake
1 1
96 1,330
- 0.2%
7.5 6.1
5 months ago about 2 months ago
R R
GNU General Public License v3.0 or later GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

JuliaConnectoR

Posts with mentions or reviews of JuliaConnectoR. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-10.
  • Convert Random Forest from Julia to R
    2 projects | /r/Julia | 10 Jun 2021
    Awesome resource!! On my side, I found the opposite R package to use Julia directly in R (https://github.com/stefan-m-lenz/JuliaConnectoR). In your opinion, what would be the most efficient?

drake

Posts with mentions or reviews of drake. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-02.
  • Your impression of {targets}? (r package)
    3 projects | /r/Rlanguage | 2 May 2021
    The targets package is the official successor to Drake, and has the same primary author (Will Landau). He has explained why he created targets, which includes stronger guardrails for users and better UX.

What are some alternatives?

When comparing JuliaConnectoR and drake you can also consider the following projects:

RCall.jl - Call R from Julia

targets - Function-oriented Make-like declarative workflows for R

rtweet - 🐦 R client for interacting with Twitter's [stream and REST] APIs

easystats - :milky_way: The R easystats-project

shinyjs - 💡 Easily improve the user experience of your Shiny apps in seconds

tabulapdf - Bindings for Tabula PDF Table Extractor Library

rmarkdown - Dynamic Documents for R

ncaahoopR - An R package for working with NCAA Basketball Play-by-Play Data

fiery - A flexible and lightweight web server

causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning

droll - An R package to analyze roll distributions

disk.frame - Fast Disk-Based Parallelized Data Manipulation Framework for Larger-than-RAM Data

JuliaConnectoR vs RCall.jl drake vs targets JuliaConnectoR vs rtweet drake vs easystats JuliaConnectoR vs shinyjs drake vs tabulapdf JuliaConnectoR vs rmarkdown drake vs ncaahoopR drake vs fiery drake vs causalglm drake vs droll drake vs disk.frame