RDKit VS BinaryBuilder.jl

Compare RDKit vs BinaryBuilder.jl and see what are their differences.

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RDKit BinaryBuilder.jl
4 5
2,452 380
2.8% 1.3%
9.5 6.5
7 days ago 18 days ago
HTML Julia
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 or later
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.

RDKit

Posts with mentions or reviews of RDKit. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-20.

BinaryBuilder.jl

Posts with mentions or reviews of BinaryBuilder.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-30.
  • Is Julia suitable today as a scripting language?
    6 projects | /r/Julia | 30 Jan 2023
    There are some efforts and the startup times are getting better with every release and there's BinaryBuilder.jl.
  • Because cross-compiling binaries for Windows is easier than building natively
    15 projects | news.ycombinator.com | 18 Jun 2022
    There is the Julia package https://github.com/JuliaPackaging/BinaryBuilder.jl which creates an environment that fakes being another, but with the correct compilers and SDKs . It's used to build all the binary dependencies
  • Discussion Thread
    2 projects | /r/neoliberal | 16 Apr 2022
    https://binarybuilder.org/. You can do it manually obviously, but this is easier.
  • PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
    18 projects | news.ycombinator.com | 26 Nov 2021
    > The main pain point is probably the lack of standard, multi-environment packaging solutions for natively compiled code.

    Are you talking about something like BinaryBuilder.jl[1], which provides native binaries as julia-callable wrappers?

    --

    [1] https://binarybuilder.org

  • What to do about GPU packages on PyPI?
    7 projects | news.ycombinator.com | 20 May 2021
    Julia did that for binary dependencies for a few years, with adapters for several linux platforms, homebrew, and for cross-compiled RPMs for Windows. It worked, to a degree -- less well on Windows -- but the combinatorial complexity led to many hiccups and significant maintenance effort. Each Julia package had to account for the peculiarities of each dependency across a range of dependency versions and packaging practices (linkage policies, bundling policies, naming variations, distro versions) -- and this is easier in Julia than in (C)Python because shared libraries are accessed via locally-JIT'd FFI, so there is no need to eg compile extensions for 4 different CPython ABIs (Julia also has syntactic macros which can be helpful here).

    To provide a better experience for both package authors and users, as well as reducing the maintenance burden, the community has developed and migrated to a unified system called BinaryBuilder (https://binarybuilder.org) over the past 2-3 years. BinaryBuilder allows targeting all supported platforms with a single build script and also "audits" build products for common compatibility and linkage snafus (similar to some of the conda-build tooling and auditwheel). There was a nice talk at AlpineConf recently (https://alpinelinux.org/conf/) covering some of this history and detailing BinaryBuilder, although I'm not sure how to link into the video.

    All that to say: it can work to an extent, but it has been tried various times before. The fact that conda and manylinux don't use system packages was not borne out of inexperience, either. The idea of "make binaries a distro packager's problem" sounds like a simplifying step, but that doesn't necessarily work out.

What are some alternatives?

When comparing RDKit and BinaryBuilder.jl you can also consider the following projects:

Biopython - Official git repository for Biopython (originally converted from CVS)

functorch - functorch is JAX-like composable function transforms for PyTorch.

NetworkX - Network Analysis in Python

Yggdrasil - Collection of builder repositories for BinaryBuilder.jl

orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis

HTTP.jl - HTTP for Julia

Numba - NumPy aware dynamic Python compiler using LLVM

dh-virtualenv - Python virtualenvs in Debian packages

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

StarWarsArrays.jl - Arrays indexed as the order of Star Wars movies

Dask - Parallel computing with task scheduling

mxe - MXE (M cross environment)