Julia
Julia is a high-performance, dynamically typed programming language designed for numerical and scientific computing, aiming to combine the ease of use of languages like Python with speed closer to compiled languages like C.
26 resources across 3 libraries
Glossary Terms(3)
Julia
Julia is a high-performance, dynamically typed programming language designed for numerical and scientific computing, aiming to combine the ease of use of langu…
JupyterLab
JupyterLab is a web-based interactive development environment for notebooks, code, and data, widely used in data science and scientific computing for combining…
Chapel (language)
Chapel is a parallel programming language developed for high-performance computing that provides high-level, productivity-oriented abstractions for both data p…
Study Notes(22)
Arrays in Julia
Learn how Julia's built-in Array type stores, indexes, and mutates collections of data, and why column-major memory layout matters for performance.
Broadcasting in Julia
Learn Julia's dot-syntax broadcasting mechanism, how chained operations fuse into allocation-free loops, and how to make custom types broadcast correctly.
Calling Python and C from Julia
How PyCall.jl/PythonCall.jl let Julia call Python libraries directly, and how Julia's built-in ccall lets you call C and Fortran functions with zero overhead.
Conditionals in Julia
Learn how Julia evaluates truthiness, structures if/elseif/else blocks, and uses short-circuit and ternary operators for concise control flow.
Functions in Julia
Learn Julia's function syntax, multiple return values, keyword and optional arguments, and the mutating-function naming convention.
Installing Julia and the REPL
How to install Julia with juliaup and navigate the four modes of Julia's interactive REPL for fast, iterative development.
Julia and Jupyter Notebooks
How to run Julia in Jupyter via IJulia, and how Pluto.jl offers a reactive, reproducible alternative notebook experience built specifically for Julia.
Julia and Machine Learning (Flux.jl)
How Flux.jl brings differentiable programming to Julia, letting you build and train neural networks with plain Julia code and automatic differentiation.
Julia Best Practices
Guidelines for writing fast, idiomatic, and maintainable Julia code, from type stability to package structure.
Julia for Scientific Computing
How Julia's multiple dispatch, type system, and native array performance make it a first-class language for numerical and scientific computing.
Julia Interview Questions
Common interview questions and model answers covering Julia fundamentals, performance, and multiple dispatch.
Julia Operators and Expressions
Julia's arithmetic, comparison, and logical operators, the dot-broadcasting syntax, and how the language's expression-oriented design ties it all together.
Julia Quick Reference
A condensed cheat sheet of core Julia syntax: variables, control flow, functions, types, and common collection operations.
Julia Variables and Types
How Julia's dynamic variables work, how its type hierarchy of abstract and concrete types is organized, and why type stability drives performance.
Julia vs Python
A practical comparison of Julia and Python for numerical computing, covering performance, syntax, and ecosystem tradeoffs.
Loops in Julia
Master for and while loops, iteration over collections, break/continue, and performance-minded loop patterns in Julia.
Parallel Computing in Julia
An overview of Julia's parallelism options — multithreading with Threads.@threads, multiprocessing with Distributed.jl, and how to avoid data races.
Performance Tips in Julia
Practical techniques for writing fast, type-stable Julia code, from avoiding global variables to benchmarking with BenchmarkTools.jl.
Testing Julia Code
How to write unit tests for Julia code using the built-in Test standard library, organize test suites, and integrate testing into package development.
The Julia Package Manager (Pkg)
How to use Julia's built-in Pkg to create reproducible environments, add and version packages, and understand Project.toml and Manifest.toml.
What Is Julia?
An introduction to Julia as a high-performance, dynamically typed language for scientific computing, and the problem it was built to solve.
Your First Julia Script
How to write, structure, and run a complete Julia script — from functions and control flow to I/O and the standalone-vs-library entry-point convention.