JuliaConnectoR VS drake

Compare JuliaConnectoR vs drake and see what are their differences.


A functionally oriented interface for calling Julia from R (by stefan-m-lenz)
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JuliaConnectoR drake
1 1
77 1,320
- -0.2%
7.6 3.1
3 months ago 8 months ago
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.


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 | reddit.com/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?


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.

What are some alternatives?

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

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

easystats - :milky_way: The R easystats-project

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

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

awesome-pipeline - A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin

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

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

drc - Fitting dose-response models in R

ffscrapr - R API Client for Fantasy Football League Platforms

tidyqpcr - quantitative PCR analysis with the tidyverse

droll - An R package to analyze roll distributions

targets-tutorial - Short course on the targets R package