dplyr VS Rustler

Compare dplyr vs Rustler and see what are their differences.

dplyr

dplyr: A grammar of data manipulation (by tidyverse)

Rustler

Safe Rust bridge for creating Erlang NIF functions (by rusterlium)
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dplyr Rustler
40 35
4,634 4,130
0.5% 2.3%
7.4 8.6
16 days ago 1 day ago
R Rust
GNU General Public License v3.0 or later Apache License 2.0
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.

dplyr

Posts with mentions or reviews of dplyr. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-15.
  • Show HN: Open-source, browser-local data exploration using DuckDB-WASM and PRQL
    11 projects | news.ycombinator.com | 15 Mar 2024
    That's great feedback, thanks!

    This tool definitely comes from a place of personal need - beyond just handling large files, I've also never really gelled well with the Excel/Google Sheet model of changing data in place as if you were editing text. I'm a Data Scientist and always preferred the chained data transforms you see in things like dplyr (https://dplyr.tidyverse.org/) or Polars (https://pola.rs/) and I feel this tool maps very closely to the chained model.

    Also, thank you for the feature requests! Those would all be very useful - we'll put them on the roadmap.

  • PSA: You don't need fancy stuff to do good work.
    10 projects | /r/datascience | 9 May 2023
    Before diving into advanced machine learning algorithms or statistical models, we need to start with the basics: collecting and organizing data. Fortunately, both Python and R offer a wealth of libraries that make it easy to collect data from a variety of sources, including web scraping, APIs, and reading from files. Key libraries in Python include requests, BeautifulSoup, and pandas, while R has httr, rvest, and dplyr.
  • osdc-2023-assignment1
    5 projects | dev.to | 9 Jan 2023
  • Modern Polars: an extensive side-by-side comparison of Polars and Pandas
    5 projects | news.ycombinator.com | 7 Jan 2023
    It really can't be said enough how pandas is a mess. It has way too much surface area and no common thread pulling it all together. This gets obvious when you work with better dataframe libs like dplyr [1] or DataFramesMeta [2]. I've worked on production systems with all of these libs, this is not gratuitous bashing.

    [1] https://dplyr.tidyverse.org/

  • How do I find R code for R functions?
    2 projects | /r/rprogramming | 21 Nov 2022
    There are two ways you can generally see the source code for packages. The simplest is to look for the github repository for the package (assuming it exists). For dplyr, it's here. Easiest way to find these is to google search "r github" plus the name of the package. Usually it'll be one of the first results. The github repo would also usually be linked on the package's CRAN page. However, be aware that this may be a development version of the package and not the same version that is currently released on CRAN (e.g. dplyr on CRAN is version 1.0.10, but on github it is listed as version 1.0.99.9000, which will probably become version 1.1.0 when it is released onto CRAN).
  • People who live near other people vote for Democrats
    4 projects | /r/dataisbeautiful | 9 Nov 2022
    Tools used: various packages in R (tidycensus, dplyr, ggplot2, sf)
  • Used Cars Data Scraping - R & Github Actions & AWS
    2 projects | dev.to | 11 Sep 2022
    It came up with the idea of how to combine Data Engineering with Cloud and automation. I needed to find a data source as it would be an automated pipeline, so I needed a dynamic source. At the same time, I wanted to find a site where I thought retrieving data would not be a problem and do practice with both rvest and dplyr. After I had no problems with my experiments with Carvago, I added the necessary data cleaning steps. Another thing I aimed for in the project was to keep the data in different ways in different environments. While raw (daily CSV) and processed data were written to the Github repo, I wrote the processed data to PostgreSQL on AWS RDS. In addition, I sync the raw and processed data to S3 to be able to use it with Athena. However, I have separated some stages for GitHub Actions to be a good practice. For example, in the first stage, I added synchronization with AWS S3 as a separate action while scraping data, cleaning, and printing fundamental analysis to a simple log file. If there is no error after all this, I added a report with RMarkdown and the action that will be published on github.io. Thus, I created an end-to-end data pipeline where the data from the source is made to offer basic reporting with simple processing.
  • Quick candlestick summaries with Elixir's Explorer
    8 projects | dev.to | 22 Aug 2022
    The API is heavily influenced by Tidy Data and borrows much of its design from dplyr. The philosophy is heavily influenced by this passage from dplyr's documentation:
  • tidytable v0.8.1 is on CRAN - it also comes with a new logo! Need data.table speed with tidyverse syntax? Check out tidytable.
    2 projects | /r/rstats | 22 Aug 2022
    Also - I might have been the one that put in the request for .by in dplyr 😅
  • ibis-datasette: Query datasette servers without writing a line of SQL
    2 projects | /r/Python | 18 Aug 2022
    For my day job I work on ibis. ibis lets users write queries using a familiar dataframe-like API, and then execute those queries on a number of SQL (and non-SQL) backends. Think of it like dplyr but for Python.

Rustler

Posts with mentions or reviews of Rustler. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-09.
  • AI Toolkit: Give a brain to your game's NPCs, a header-only C++ library
    2 projects | news.ycombinator.com | 9 Jan 2024
    For performance intensive tasks, you could rely on Rust NIFs, there is this great project: https://github.com/rusterlium/rustler

    My last project with Elixir was using Elixir merely as an orchestrator of static binaries (developed in golang) which were talking in JSON via stdin/stdout.

  • Building Apps with Tauri and Elixir
    14 projects | dev.to | 19 Oct 2023
    From the moment we discovered Tauri, we really felt like this was the perfect fit. The API is really solid, the configuration files are minimal and easy to understand, and the usage of Rust makes it way easier to add new functionalities and think about interesting ways of interoperating with Elixir via the Rustler library.
  • Async Rust Is A Bad Language
    11 projects | news.ycombinator.com | 8 Sep 2023
    Elixir/Rust is the new Python/C++, and Rustler makes the communicating between the 2 languages super easy: https://github.com/rusterlium/rustler
  • Why elixir over Golang
    10 projects | /r/elixir | 29 May 2023
    Rustler is so awesome for this. Write Elixir NIFs in Rust? Yes, please!
  • Is RUST a good choice for building web browsers?
    6 projects | /r/rust | 27 May 2023
  • Why do you enjoy systems programming languages?
    2 projects | /r/rust | 25 May 2023
    But really, I would suggest thinking about what you want to build before "how" or "with which tool" - one of the signs of a person becoming a good engineer is having an array of tools at their disposal and being able to choose a correct tool for the correct task. Rust also excels in integrating with other languages - with JS via WebAssembly (a bit of self-promotion, for example), with Elixir via Rustler, with Python via PyO3 and PyOxidizer, etc. So you absolutely can start writing a frontend app with JS, or a distributed system with Elixir, or a data processing/ML app with Python and use Rust to speed up critical parts of those. Or, in reverse, you can start with Rust & add new capabilities to whatever you're building, that being a frontend, a resilient chat interface, or an ML model.
  • PasswordRs 0.1.0 released (Rust NIF for password hashing)
    4 projects | /r/elixir | 24 Apr 2023
    I created a elixir (wrapper) library to generate password hashes. Other Elixir libraries use a C NIF to generate password hashes. This libary uses a Rust NIF (using Rustler) and the Rust libraries the generate the different hashes. Additionally this library uses RustlerPrecompiled so you don't need to have a Rust compiler installed to use this library. It supports argon2, scrypt, brypt and pbkdf2.
  • Elixir and Rust is a good mix
    10 projects | news.ycombinator.com | 13 Apr 2023
    > I guess, why not use Rust entirely instead of as a FFI into Elixir or other backend language?

    Because Rust brings none of the benefits of the BEAM ecosystem to the table.

    I was an early Elixir adopter, not working currently as an Elixir developer, but I have deployed one of the largest Elixir applications for a private company in my country.

    I know it has limits, but the language itself is only a small part of the whole.

    Take ML, Jose Valim and Sean Moriarity have studied the problem, made a plan to tackle it and started solving it piece by piece [1] in a tightly integrated manner, it feels natural, as if Elixir always had those capabilities in a way that no other language does and to put the icing on the cake the community released Livebook [2] to interactively explore code and use the new tools in the simplest way possible, something that Python notebooks only dream of being capable of, after a decade of progress

    That's not to say that Elixir is superior as a language, but that the ecosystem is flourishing and the community is able to extract the 100% of the benefits from the tools and create new marvellously crafted ones, that push the limits forward every time, in such a simple manner, that it looks like magic.

    And going back to Rust, you can write Rust if you need speed or for whatever reason you feel it's the right tool for the job, it's totally integrated [3][4], again in a way that many other languages can only dream of, and it's in fact the reason I've learned Rust in the first place.

    The opposite is not true, if you write Rust, you write Rust, and that's it. You can't take advantage of the many features the BEAM offers, OTP, hot code reloading, full inspection of running systems, distribution, scalability, fault tolerance, soft real time etc. etc. etc.

    But of course if you don't see any advantage in them, it means you probably don't need them (one other option is that you still don't know you want them :] ). In that case Rust is as good as any other language, but for a backend, even though I gently despise it, Java (or Kotlin) might be a better option.

    [1] https://github.com/elixir-nx/nx https://github.com/elixir-nx/axon

    [2] https://livebook.dev/

    [3] https://github.com/rusterlium/rustler

    [4] https://dashbit.co/blog/rustler-precompiled

  • It's legos all the way down
    3 projects | dev.to | 17 Feb 2023
    unfortunately as of the time of this writing, rustler does not support generic type intefaces so I guess this is impossible?
  • When Rust Hurts
    6 projects | news.ycombinator.com | 15 Feb 2023
    One thing that drew me to Rust was actually Elixir/Erlang calling out to it for certain specialized needs. Within Elixir/Erlang you get best of breed concurrency but exiting the BEAM to run other code is unsafe. Calling out to Rust, however, comes with great safety guarantees.

    Managing concurrency outside of Rust and then calling Rust for the more focused and specialized work is a good combination IMO.

    https://github.com/rusterlium/rustler

What are some alternatives?

When comparing dplyr and Rustler you can also consider the following projects:

worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob

gleam - ⭐️ A friendly language for building type-safe, scalable systems!

hsnif - Tool that allows to write Erlang NIF libraries in Haskell

carbon-lang - Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)

nifty - helpful tools for when I need to create an Elixir NIF .

Akka - Build highly concurrent, distributed, and resilient message-driven applications on the JVM

elixir-nodejs - An Elixir API for calling Node.js functions

ggplot2 - An implementation of the Grammar of Graphics in R

crate-deps

nx - Multi-dimensional arrays (tensors) and numerical definitions for Elixir

explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir

rst - The open source design documentation tool for everybody [Moved to: https://github.com/vitiral/artifact]