OffsetArrays.jl
advent-of-code
OffsetArrays.jl | advent-of-code | |
---|---|---|
7 | 9 | |
192 | 5 | |
1.0% | - | |
6.0 | 7.1 | |
18 days ago | 3 months ago | |
Julia | Python | |
GNU General Public License v3.0 or later | - |
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.
OffsetArrays.jl
-
Why I am switching my programming language to 1-based array indexing.
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
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 -🎄-
You might be interested in OffsetArrays.jl.
- PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
-
Why does Julia adopt 1-based index?
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
-
Evcxr: A Rust REPL and Jupyter Kernel
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
advent-of-code
-
-🎄- 2022 Day 16 Solutions -🎄-
Python my ugliest solution this year! Kill me 🤮
- -🎄- 2021 Day 23 Solutions -🎄-
- -🎄- 2021 Day 18 Solutions -🎄-
-
-🎄- 2021 Day 16 Solutions -🎄-
On github
-
-🎄- 2021 Day 7 Solutions -🎄-
Python https://github.com/fridokus/advent-of-code/blob/master/2021/7.py
- -🎄- 2021 Day 6 Solutions -🎄-
- -🎄- 2021 Day 3 Solutions -🎄-
-
-🎄- 2020 Day 22 Solutions -🎄-
Python 3
-
2020 Day 21 Solutions
Python 3 solved second part by inspection first but decided to implement it later in code
What are some alternatives?
StarWarsArrays.jl - Arrays indexed as the order of Star Wars movies
personal_code - random code that I have lying around
TwoBasedIndexing.jl - Two-based indexing
advent-of-code-2021 - My solutions for the "Advent of Code 2021"
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.
advent-of-code-2020 - 🎅🌟❄️☃️🎄🎁
TailRec.jl - A tail recursion optimization macro for julia.
adventofcode
julia - The Julia Programming Language
Advent-of-Code - My solutions for the Advent of Code puzzles (work in progress).
StatsBase.jl - Basic statistics for Julia
advent-of-code