Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-software-engineering
A curated list of awesome software engineering resources.
https://github.com/Alliedium/awesome-software-engineering
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- Considering Rust by Jon Gjengset
- Rust Crash Course by Traversy Media
- Rust Linz, August 2020 - Ryan Levick - Why should I care about Rust?
- Introduction to Rust Part 1 by Ryan Levick
- Introduction to Rust Part 2 by Ryan Levick
- Understanding Rust Lifetimes by Ryan Levick
- Crust of Rust by Jon Gjengset
- R-Evolution: A Story of Rust Adoption at Microsoft - Ryan Levick
- AWS re:Invent 2020: Next-gen networking infrastructure with Rust and Tokio
- Julia: a post-mortem
- Julia: a post-mortem: discussion on Julia's discourse
- Julia: a post-mortem: discussion on ycombinator
- Julia from the perspective of a pythonista
- What's bad about Julia by Jeff Bezenson
- Julia motivation: why weren’t Numpy, Scipy, Numba, good enough?
- JuliaCon 2019 | The Unreasonable Effectiveness of Multiple Dispatch | Stefan Karpinski
- Julia Academy
- Getting started with Julia
- 9 Cool Julia tricks
- Julia blogs aggregator
- Julia 1.6 highlights
- Julia is production-ready
- JuliaCon 2020 | The ups and downs of convincing to switch to Julia in a company | Jorge Alberto
- JuliaCon 2020 | State of Julia | Jeff Bezanson & Stefan Karpinski
- Interview with Julia Language Co-founders
- Julia performance tips
- Julia performance: benchmarking via BenchmarkTools.jl
- How to benchmark like a pro in Julia | Tom Kwong
- JuliaCon 2020 | Adventures in Avoiding Allocations | Brian Jackson
- How hard would it be to implement Numpy.jl, i.e. Numpy in Julia? Point 1
- How hard would it be to implement Numpy.jl, i.e. Numpy in Julia? Point 2
- How to submit a PR on GitHub
- Working with and emulating references in Julia
- Is Julia Dynamically Typed?
- Julia type system
- Libraries & parameterized types | MIT Computational Thinking Spring 2021 | Lecture 18
- juliaobserver.com
- juliapackages.com
- DataFrames.jl performance benchmark
- DataFrames minilanguage explained
- Welcome to DataFrames.jl with Bogumił Kamiński
- Release announcements for DataFrames.jl
- DataFrames.jl: comparison with Pandas
- DataFrames.jl cheatsheet
- JuliaCon 2020 | Doing Scientific Machine Learning (SciML) With Julia
- MIT Course 18.337 - Parallel Computing and Scientific Machine Learning GitHub Repo
- MIT Course 18.337 - Parallel Computing and Scientific Machine Learning YouTube Channel
- MIT Course 18.337 - Parallel Computing and Scientific Machine Learning GitHub Repo
- MIT Course 18.337 - Parallel Computing and Scientific Machine Learning YouTube Channel
- VSCode Plugin
- JuliaCon 2020 | Dependency-Aware Jupyter Notebooks | Arnav Sood
- JuliaCon 2020 | Interactive notebooks ~ Pluto.jl | Fons van der Plas
- Pluto.jl Notebooks and PlutoUI Tutorial (Julia Programming)
- How to disable authentication
- How to increase notebook width
- Table of contents
- Dark mode
- JuliaCon 2020 | Building Microservices and Applications in Julia
- Custom sysimages: official documentation
- SimpleContainerGenerator
- Running AWS Lambda functions with Julia | Tom Kwong
- Libraries & parameterized types | MIT Computational Thinking Spring 2021 | Lecture 18
- Goodbye OOP
- Type-Dispatch Design: Post Object-Oriented Programming for Julia
- WhereTraits.jl
- BinaryTraits.jl
- Julia: how multiple dispatch works
- JuliaCon 2020 | Lessons learned on trait-based descriptions of graphs | Mathieu Besancon
- JuliaPy
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design-patterns
2
traits
2
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1
gof-patterns
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1
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1
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