Elixir Wizards

Elixir Wizards Owen Bickford and Dan Ivovich discuss web development with Elixir and Phoenix vs. Ruby on Rails, comparing history, project structure, programming paradigms, CRUD apps, LiveView vs. Turbolinks, and WebSocket usage. They also touch on testing frameworks and the benefits of knowledge in multiple frameworks.

Today on Elixir Wizards, Manuel Rubio, author of Erlang/OTP: A Concurrent World and Dan Plyukhin, creator of the UIGC Actor Garbage Collector for Akka, join host Dan Ivovich to compare notes on garbage collection in actor models. The discussion digs into the similarities and differences of actor-based garbage collection in Erlang and Akka and introduces Dan's research on how to perform garbage collection in a distributed actor system. Topics discussed: Akka is akin to Erlang actors for the JVM using Scala, with similar principles like supervision trees, messages, and clustering Erlang uses generational garbage collection and periodically copies live data to the old heap for long-lived elements Actor GC aims to determine when an actor's memory can be reclaimed automatically rather than manually killing actors Distributed actor GC is more challenging than object GC due to the distributed nature and relationships between actors across nodes Challenges include reasoning about failures like dropped messages and crashed nodes GC balance requires optimization of resource release and CPU load management Immutability helps Erlang GC, but copying data for messages impacts performance Research into distributed actor GC is still ongoing, with opportunities for improvement Fault tolerance in Erlang relies on user implementation rather than low-level guarantees Asynchronous messages in Erlang/Elixir mean references may become invalid which is similar to the distributed GC approaches in Dan's research Idempotent messaging is recommended to handle possible duplicates from failures Help your local researcher! Researchers encourage communication from practitioners on challenges and use cases Links mentioned: Erlang/OTP Volume 1: A Concurrent World by Manuel Rubio https://altenwald.com/en/book/en-erlang-i  Scala https://www.scala-lang.org/  Akka Framework https://github.com/akka  JVM (Java Virtual Machine) https://www.java.com/en/download/  The BEAM VM https://www.erlang.org/blog/a-brief-beam-primer/ Hadoop Framework https://hadoop.apache.org/   Pony Programming Language https://www.ponylang.io/  SLSA Programming Language https://wcl.cs.rpi.edu/salsa/#:~:text=SALSA%20 Paxos Algorithm https://en.wikipedia.org/wiki/Paxos_(computer_science)  Raft library for maintaining a replicated state machine https://github.com/etcd-io/raft  Dan's Website https://dplyukhin.github.io/  Dan Plyukhin on Twitter: https://twitter.com/dplyukhin  Dan Plyukhin’s YouTube channel: https://m.youtube.com/@dplyukhin UIGC on GitHub https://github.com/dplyukhin/UIGC  Manuel's Website https://altenwald.com/  Manuel Rubio on Twitter: https://twitter.com/MRonErlangSpecial Guests: Dan Plyukhin and Manuel Rubio.

In this episode of Elixir Wizards, Katelynn Burns, software engineer at LaunchScout, and Alexis Carpenter, senior data scientist at cars.com, join Host Dan Ivovich to discuss machine learning with Elixir, Python, SQL, and MATLAB. They compare notes on available tools, preprocessing, working with pre-trained models, and training models for specific jobs. The discussion inspires collaboration and learning across communities while revealing the foundational aspects of ML, such as understanding data and asking the right questions to solve problems effectively. Topics discussed: Using pre-trained models in Bumblebee for Elixir projects Training models using Python and SQL The importance of data preprocessing before building models Popular tools used for machine learning in different languages Getting started with ML by picking a personal project topic of interest Resources for ML aspirants, such as online courses, tutorials, and books The potential for Elixir to train more customized models in the future Similarities between ML approaches in different languages Collaboration opportunities across programming communities Choosing the right ML approach for the problem you're trying to solve Productionalizing models like fine-tuned LLM's The need for hands-on practice for learning ML skills Continued maturation of tools like Bumblebee in Elixir Katelynn's upcoming CodeBeam talk on advanced motion tracking Links mentioned in this episode https://launchscout.com/ https://www.cars.com/ Genetic Algorithms in Elixir by Sean Moriarity Machine Learning in Elixir by Sean Moriarity https://github.com/elixir-nx/bumblebee https://github.com/huggingface https://www.docker.com/products/docker-hub/ Programming with MATLAB https://elixirforum.com/ https://pypi.org/project/pyspark/  Machine Learning Course from Stanford School of Engineering Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron Data Science for Business by Foster Provost & Tom Fawcett https://medium.com/@carscomtech  https://github.com/k-burns  Code Beam America March, 2024Special Guests: Alexis Carpenter and Katelynn Burns.

This week on Elixir Wizards, Connor Rigby, Software Engineer at SmartRent, and Taylor Barto, Lead Embedded Software Engineer at Eaton, join Sundi Myint to compare notes on embedded systems development with Elixir, C, C++, and Java. They discuss using Elixir and the Nerves framework for firmware projects versus more traditional choices like C. The guests ask one another questions and gain valuable insights into challenges, tooling, resources, and more across different embedded ecosystems. In this episode, the guests expand their perspectives and demystify the concept of embedded systems for engineers outside the field. This cross-language exchange of ideas and experiences inspires continued learning and collaboration between embedded software engineers using different programming languages. Topics Discussed: Defining "true embedded": using an operating system vs. bare metal programming Benefits and drawbacks of Elixir, C, C++, and Java for firmware Many embedded systems today use Java as the programming language via Java Native Interface (JNI) to interface with C/C++ code How Elixir expands the toolbox available for firmware projects Testing, tooling, workflows, and debugging across languages Elixir/Nerves features like hot code reloading and testing vs. Java alternatives Learning curves for new languages and frameworks Industry trends around established vs emerging tools Applying functional programming principles like immutability in new domains Scaling firmware updates across large connected networks Continued maturation of Nerves may bring Elixir into consideration for roles where Java is commonly used today Hardening systems for reliability in safety-critical uses Debugging differences between web development and embedded Hiring considerations for niche languages Additional skills needed for embedded engineers, such as technical writing, reading schematics, and writing test instructions Resources and recommendations for getting started with embedded systems Links Mentioned: Nerves: https://github.com/nerves-project/nerves https://nerves-project.org/ AtomVM: https://github.com/atomvm/AtomVM GRiSP: https://github.com/grisp RISC-V: https://github.com/ultraembedded/riscv https://smartrent.com/ https://www.eaton.com/us/en-us.html Zig Programming Language: https://github.com/ziglang Docker: https://github.com/docker Build a Weather Station with Elixir and Nerves by Alexander Koutmos, Bruce A. Tate, Frank Hunleth Build a Binary Clock with Elixir and Nerves by Frank Hunleth and Bruce A. Tate http://esp32.net/ https://www.nordicsemi.com/Special Guests: Connor Rigby and Taylor Barto.

In Episode 4, the Elixir Wizards are joined by Dorian Iacobescu, author of the ECSpanse ECS library for Elixir, and Daniel Luu, founder and CEO of the game development studio AKREW. The guests compare notes on backend game development using ECS, the Entity Component System approach. Akrew is currently building the multiplayer game Galactic Getaway using the Photon Unity networking framework, which employs ECS. They discuss challenges like collections of component types and persistence beyond runtime, building games for various platforms like MacOS, and handling inventory storage in a backend database. Game development is complex and has many technical hurdles, but open communication across different programming communities and game development approaches can foster collaboration, innovation, and continued learning. Topics Discussed in this Episode Dorian explains the ECSpanse ECS library and component-based architecture Dorian took inspiration for ECSpanse from the Rust library Bevy ECS and its component-based API The guests discuss popular game development platforms and languages, including C#, JavaScript, and Godot Owen and Daniel translate ECS concepts to familiar database and backend terminology for devs without game-specific experience ECSpanse uses many tools from the Elixir Erlang toolbox, including GenServers, ETS tables, tasks, queries, and Phoenix LiveView ECS challenges representing inventory collections that broke typical ECS singleton patterns AKREW is developing Galactic Getaway using the Photon Unity framework Relationships between parent and child entities in ECSpanse Persistence, serialization, and replay features to save game state Optimizing assets and code for performance on various devices Links Mentioned https://en.wikipedia.org/wiki/Entity_component_system https://iacobson.medium.com/elixir-for-fun-ecspanse-2852a7993ecd https://hexdocs.pm/ecspanse/Ecspanse.html https://bevyengine.org/learn/book/getting-started/ecs/ https://www.photonengine.com/quantum Add Galactic Getaway to your Steam Wishlist: https://store.steampowered.com/app/2012390/Galactic_Getaway/ https://godotengine.org/ https://unity.com/ https://docs.godotengine.org/en/stable/tutorials/scripting/gdscript/gdscript_basics.html https://www.tiktok.com/@galacticgetaway https://docs.rs/bevy_ecs/latest/bevy_ecs/ Special Guests: Daniel Luu and Dorian Iacobescu.

This week, the Elixir Wizards are joined by Yohana Tesfazgi and Wes Bos to compare notes on the experience of learning Elixir vs. JavaScript as your first programming language. Yohana recently completed an Elixir apprenticeship, and Wes Bos is a renowned JavaScript educator with popular courses for beginner software developers. They discuss a variety of media and resources and how people with different learning styles benefit from video courses, articles, or more hands-on projects. They also discuss the current atmosphere for those looking to transition into an engineering career and how to stick out among the crowd when new to the scene. Topics Discussed in this Episode Pros and cons of learning Elixir as your first programming language Materials and resources for beginners to JavaScript and Elixir Projects and methods for learning Elixir with no prior knowledge Recommendations for sharpening and showcasing skills How to become a standout candidate for potential employers Soft skills like communication translate well from other careers to programming work Learning subsequent languages becomes more intuitive once you learn your first How to decide which library to use for a project How to build an online presence and why it’s important Open-source contributions are a way to learn from the community Ship early and often, just deploying a default Phoenix app teaches deployment skills Attend local meetups and conferences for mentoring and potential job opportunities Links Mentioned https://syntax.fm/ https://fly.io/ https://elixirschool.com/en Syntax.fm: Supper Club × How To Get Your First Dev Job With Stuart Bloxham Quinnwilton.com https://github.com/pallets/flask https://wesbos.com/courses https://beginnerjavascript.com/ Free course: https://javascript30.com/ https://pragmaticstudio.com/ https://elixircasts.io/ https://grox.io/ LiveView Mastery YouTube Channel Contact Yohana: yytesfazgi@gmail.com

In today’s episode, Sundi and Owen are joined by Yordis Prieto and Stephen Chudleigh to compare notes on HTTP requests in Elixir vs. Ruby, JavaScript, Go, and Rust. They cover common pain points when working with APIs, best practices, and lessons that can be learned from other programming languages. Yordis maintains Elixir's popular Tesla HTTP client library and shares insights from building APIs and maintaining open-source projects. Stephen has experience with Rails and JavaScript, and now works primarily in Elixir. They offer perspectives on testing HTTP requests and working with different libraries. While Elixir has matured, there is room for improvement - especially around richer struct parsing from HTTP responses. The discussion highlights ongoing efforts to improve the developer experience for HTTP clients in Elixir and other ecosystems. Topics Discussed in this Episode HTTP is a protocol - but each language has different implementation methods Tesla represents requests as middleware that can be modified before sending Testing HTTP requests can be a challenge due to dependence on outside systems GraphQL, OpenAPI, and JSON API provide clear request/response formats Elixir could improve richer parsing from HTTP into structs Focus on contribution ergonomics lowers barriers for new participants Maintainers emphasize making contributions easy via templates and clear documentation APIs drive adoption of standards for client/server contracts They discuss GraphQL, JSON API, OpenAPI schemas, and other standards that provide clear request/response formats TypeScript brings types to APIs and helps to validate responses Yordis notes that Go and Rust make requests simple via tags for mapping JSON to structs Language collaboration shares strengths from different ecosystems and inspires new libraries and tools for improving the programming experience Links Mentioned Elixir-Tesla Library: https://github.com/elixir-tesla/tesla Yordis on Github: https://github.com/yordis Yordis on Twitter: https://twitter.com/alchemist_ubi Yordis on LinkedIn: https://www.linkedin.com/in/yordisprieto/ Yordis on YouTube: https://www.youtube.com/@alchemistubi Stephen on Twitter: https://twitter.com/stepchud Stephen's projects on consciousness: https://harmonicdevelopment.us Owen suggests: Http.cat HTTParty: https://github.com/jnunemaker/httparty Guardian Library: https://github.com/ueberauth/guardian Axios: https://axios-http.com/ Straw Hat Fetcher: https://github.com/straw-hat-team/nodejs-monorepo/tree/master/packages/%40straw-hat/fetcher Elixir Tesla Wiki: https://github.com/elixir-tesla/tesla/wiki HTTPoison: https://github.com/edgurgel/httpoison Tesla Testing: https://hexdocs.pm/tesla/readme.html#testing Tesla Mock: https://hexdocs.pm/tesla/Tesla.Mock.html Finch: https://hex.pm/packages/finch Mojito: https://github.com/appcues/mojito Erlang Libraries and Frameworks Working Group: https://github.com/erlef/libs-and-frameworks/ and https://erlef.org/wg/libs-and-frameworksSpecial Guests: Stephen Chudleigh and Yordis Prieto.

Hosts Dan Ivovich, Owen Bickford, and Sundi Myint kick off the 11th season of the Elixir Wizards podcast. This season’s theme is “Branching Out from Elixir,” which expands the conversation to compare notes with experts from other communities; they discuss their experiences with other languages like JavaScript, PHP, Python, Ruby, C#, Go, and Dart before and after learning Elixir. This season's conversations will illuminate how problems are solved in different languages vs. Elixir; upcoming episode topics teased include education, data processing, deployment strategies, and garbage collection; the hosts express excitement for conversations analyzing similarities and differences between communities. Topics Discussed in this Episode Season 11 branches out from Elixir to compare notes with other programming communities Sundi, Owen, and Dan introduce the season theme and their interest in exploring these conversations The hosts compare their experiences with PHP, JavaScript, Python, Ruby, C#, Go, Dart and Elixir The Wizards compare and contrast differences in their personal experience building similar things with different languages Dan dreams in Ruby and uses it for quick prototypes Comparing problem-solving approaches across languages will reframe perspectives Upcoming episodes explore data processing workflows, machine learning, and game development Pop Quiz: Who's that Pokémon... or language, or framework? Links Mentioned https://smartlogic.io/ https://codepen.io/ https://i.redd.it/0lg7979qtr511.jpg

It’s the Season 10 finale of the Elixir Wizards podcast! José Valim, Guillaume Duboc, and Giuseppe Castagna join Wizards Owen Bickford and Dan Ivovich to dive into the prospect of types in the Elixir programming language! They break down their research on set-theoretical typing and highlight their goal of creating a type system that supports as many Elixir idioms as possible while balancing simplicity and pragmatism. José, Guillaume, and Giuseppe talk about what initially sparked this project, the challenges in bringing types to Elixir, and the benefits that the Elixir community can expect from this exciting work. Guillaume's formalization and Giuseppe's "cutting-edge research" balance José's pragmatism and "Guardian of Orthodoxy" role. Decades of theory meet the needs of a living language, with open challenges like multi-process typing ahead. They come together with a shared joy of problem-solving that will accelerate Elixir's continued growth. Key Topics Discussed in this Episode: Adding type safety to Elixir through set theoretical typing How the team chose a type system that supports as many Elixir idioms as possible Balancing simplicity and pragmatism in type system design Addressing challenges like typing maps, pattern matching, and guards The tradeoffs between Dialyzer and making types part of the core language Advantages of typing for catching bugs, documentation, and tooling The differences between typing in the Gleam programming language vs. Elixir The possibility of type inference in a set-theoretic type system The history and development of set-theoretic types over 20 years Gradual typing techniques for integrating typed and untyped code How José and Giuseppe initially connected through research papers Using types as a form of "mechanized documentation" The risks and tradeoffs of choosing syntax Cheers to another decade of Elixir! A big thanks to this season’s guests and all the listeners! Links and Resources Mentioned in this Episode: Bringing Types to Elixir | Guillaume Duboc & Giuseppe Castagna | ElixirConf EU 2023 Keynote: Celebrating the 10 Years of Elixir | José Valim | ElixirConf EU 2022 OCaml industrial-strength functional programming https://ocaml.org/ ℂDuce: a language for transformation of XML documents http://www.cduce.org/ Ballerina coding language https://ballerina.io/ Luau coding language https://luau-lang.org/ Gleam type language https://gleam.run/ "The Design Principles of the Elixir Type System" by G. Castagna, G. Duboc, and J. Valim "A Gradual Type System for Elixir" by M. Cassola, A. Talagorria, A. Pardo, and M. Viera "Programming with union, intersection, and negation types", by Giuseppe Castagna "Covariance and Contravariance: a fresh look at an old issue (a primer in advanced type systems for learning functional programmers)" by Giuseppe Castagna "A reckless introduction to Hindley-Milner type inference"Special Guests: Giuseppe Castagna, Guillaume Duboc, and José Valim.

Phoenix core team members Chris McCord and Jason Stiebs join Elixir Wizards Sundi Myint and Owen Bickford the growth of Phoenix and LiveView, the latest updates, and what they're excited to see in the future. They express excitement for the possibilities of machine learning, AI, and distributed systems and how these emerging technologies will enhance the user experience of Elixir and LiveView applications in the next decade. Key Topics Discussed in this Episode: How community contributions and feedback help improve Phoenix LiveView The addition of function components, declarative assigns, HEEx, and streams Why Ecto changesets should be used as "fire and forget" data structures Excitement about machine learning and AI with libraries like NX The possibility of distributed systems and actors in the future Verifying and solving issues in the Phoenix and LiveView issue trackers Why marketing plays a part in the adoption and mindshare of Phoenix How streams provide a primitive for arbitrarily large dynamic lists Elixir VM's ability to scale to millions of connections A creative use of form inputs for associations with dynamic children Links Mentioned in this Episode: Fly Site https://fly.io/ Keynote: The Road To LiveView 1.0 by Chris McCord | ElixirConf EU 2023 Keynote: I Was Wrong About LiveView by Jason Stiebs | ElixirConf 2022 Phoenix Site https://www.phoenixframework.org/ Phoenix Github https://github.com/phoenixframework Two-Story, 10-Room Purple Martin House Blog: The Road to 2 Million Websocket Connections in Phoenix Raxx Elixir Webserver Interface https://hexdocs.pm/raxx/0.4.1/readme.html Livebook Site https://livebook.dev/ Sundi’s 6’x 6’ Phoenix painting Surface on Hex https://hex.pm/packages/surface Axon Deep Learning Framework https://hexdocs.pm/axon/Axon.html Nx Numerical Elixir https://hexdocs.pm/nx/intro-to-nx.html Phoenix PubSub https://hexdocs.pm/phoenix_pubsub/Phoenix.PubSub.html Jason Stiebs on Twitter https://twitter.com/peregrine Jason Stiebs on Mastodon https://merveilles.town/@peregrineSpecial Guests: Chris McCord and Jason Stiebs.