println("hello world")
using Plots
using JuMP
using LinearAlgebra
x = [1,2,3,5]
using Metatheory

hmm if I want julia to work good, I need to make a command that is valid julia but also valid bash

#= =# multiline julia is not a bash comment

bash code julia won't run
# =# julia code bash won't run
# =# julia code bash won't run
"julia": "#=\njulia\n# =#\ninclude($dir * \"$fileName\")",

Yes, that’s right, Mr. Vice President. I am a genius.

packagecompiler make sys images so that packages load faster


If you want just linear problems, you can also try Tulip (this is me self-advertising; I wrote it). It’s pure Julia, and should give you decent performance. If you want nonlinear problems, among the open-source pure Julia solvers, you have: COSMO, which supports several cones & quadratic objective. It’s based on ADMM, same as SCS/OSQP Hypatia, which supports the largest variety of cones (especially the ones you’ve never heard of). It’s based on interior-point, same as ECOS/Mosek. For LP and convex QP, there is also



Evan’s new talk. Seems really cool. Categories for multiphysics?

Interesting project ideas:

  • PyRes translation
  • That prolog engine
  • SMT modulo Convex
  • Interactive Proofs
  • probabilistic games use homotopy continuation
  • Guarded rewrite rules
  • Constraint programming compilation
  • CHC from SSA
  • WP
  • anyon
  • linear relations / modules

Scientific Computing in Julia. Numerical Computing in Julia HPC in Julia Data Science in Julia Deep Learning in Julia Algorithm Design in Julia Physics for Programmers

Audience: Someone at my level or higher? People who do scientific computing? At labs? Engineers? Grad students? Hobbyists?

End Expectations: ? No one actually reads books

that optimization book in julia

Strang Book

Fluid Solver Wave Solver Fitting Data - An Inverse Problem Particle simulation Convnet ODE and PDE

Function Breaks, Type Stability Examining Code, llvm and native Fast Loops SIMD Parallelism GPU DSLs Partial Evaluation / Macros. generative functions Dispatch - Fast matrix overloading

Minimal: you can activate a environment.

From a julia repl, you can press ] to put it into Pkg mode

<code>pkg> activate .</code>

Revise.jl - You can use Revise.jl. If you’re editting a one off file, you can bring it into the repl with includet so that it automatically reloads anytime you change the file.

<code>julia> using Revise
julia> includet("myfile.jl")
julia> myfunction(7)

You should take a gander

This is how you get those slick little badges for documentation and

Unit testing. I don’t write tests for my code often enough, I know it’s a good thing to do. Here’s how you do it.

<code>using MyPkg
using Test

@testset "MyPkg.jl" begin
    # Write your tests here.
    @test true
    @test == 4

<code>pkg> test MyPkg</code>