HTTP.jl VS OffsetArrays.jl

Compare HTTP.jl vs OffsetArrays.jl and see what are their differences.

OffsetArrays.jl

Fortran-like arrays with arbitrary, zero or negative starting indices. (by JuliaArrays)
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HTTP.jl OffsetArrays.jl
7 7
623 192
1.3% 1.6%
7.7 6.0
7 days ago 9 days ago
Julia Julia
GNU General Public License v3.0 or later 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.

HTTP.jl

Posts with mentions or reviews of HTTP.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-17.

OffsetArrays.jl

Posts with mentions or reviews of OffsetArrays.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-16.
  • Why I am switching my programming language to 1-based array indexing.
    1 project | /r/ProgrammingLanguages | 27 Oct 2022
    Well, there is OffsetArrays in Julia, but it has acquired a reputation as a poison pill because most code assumes the 1-based indexing and it's easy to forget to convert the indexing and screw up the code.
  • The Julia language has a number of correctness flaws
    19 projects | news.ycombinator.com | 16 May 2022
    Similar correctness issues are a big part of the reason that, several years ago, I submitted a series of pull requests to Julia so that its entire test suite would run without memory errors under Valgrind, save for a few that either (i) we understood and wrote suppressions for, or (ii) we did not understand and had open issues for. Unfortunately, no one ever integrated Valgrind into the CI system, so the test suite no longer fully runs under it, last time I checked. (The test suite took nearly a day to run under Valgrind on a fast desktop machine when it worked, so is infeasible for every pull request, but could be done periodically, e.g. once every few days.)

    Even a revived effort on getting core Julia tests to pass under Valgrind would not do much to help catch correctness bugs due to composing different packages in the ecosystem. For that, running in testing with `--check-bounds=yes` is probably a better solution, and much quicker to execute as well. (see e.g. https://github.com/JuliaArrays/OffsetArrays.jl/issues/282)

  • -🎄- 2021 Day 6 Solutions -🎄-
    225 projects | /r/adventofcode | 5 Dec 2021
    You might be interested in OffsetArrays.jl.
  • PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
    18 projects | news.ycombinator.com | 26 Nov 2021
  • Why does Julia adopt 1-based index?
    3 projects | /r/Julia | 10 Sep 2021
    Counting starts at one, as do most vector/matrix/tensor indices. If it bothers you too much, see OffsetArrays.jl and Arrays with custom indices.
  • some may hate it, some may love it
    5 projects | /r/Julia | 27 Jun 2021
  • Evcxr: A Rust REPL and Jupyter Kernel
    7 projects | news.ycombinator.com | 26 Jan 2021
    No need for another version, Julia supports custom indices by default. Check out https://docs.julialang.org/en/v1/devdocs/offset-arrays/ and https://github.com/JuliaArrays/OffsetArrays.jl

What are some alternatives?

When comparing HTTP.jl and OffsetArrays.jl you can also consider the following projects:

geni-performance-benchmark

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

julia - The Julia Programming Language

TwoBasedIndexing.jl - Two-based indexing

DaemonMode.jl - Client-Daemon workflow to run faster scripts in Julia

Optimization.jl - Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

JET.jl - An experimental code analyzer for Julia. No need for additional type annotations.

TailRec.jl - A tail recursion optimization macro for julia.

BinaryBuilder.jl - Binary Dependency Builder for Julia

PackageCompiler.jl - Compile your Julia Package

StatsBase.jl - Basic statistics for Julia