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Looks incredibly powerful

Nice

*FlowStorm: A Powerful Tool for Debugging and Understanding Clojure Code* * *0:00:08** Initial Plan and Change of Agenda:* The speaker initially planned to talk about FlowStorm's internals and new features in FlowStorm 4. However, they realized that much of this content would overlap with a previous talk. * *0:00:58** New Title and Agenda:* The talk's title was changed to "The Power of the Storm," and the agenda shifted to focus on practical usage and demos, including: * FlowStorm refresher * Instrumentation and recording * Workflow tips and tricks * New features like the outputs panel and data windows * *0:02:07** FlowStorm Overview:* FlowStorm is a development tool for Clojure that records program execution and visualizes data. * *0:02:22** Key Difference:* Unlike other tools, FlowStorm records program execution as a "flow," which is a timeline of all thread activities. * *0:02:54** Local vs. Remote Mode:* FlowStorm can operate in local mode (everything on the same JVM) or remote mode (instrumented code and recordings on a separate process). * *0:05:34** Instrumentation with ClojureStorm:* ClojureStorm, a fork of the official Clojure compiler, adds instrumentation to emit extra bytecode for tracing, enabling detailed analysis without modifying the original code. * *0:08:43** Recording in FlowStorm:* The tool hooks into ClojureStorm and stores all events, function calls, and intermediate object references with pointers to source code coordinates. * *0:10:07** Thread Timelines:* FlowStorm organizes recordings into thread timelines, which are arrays of events, providing a detailed view of each thread's execution. * *0:10:59** Demo: Web Applications:* The speaker demonstrates how to use FlowStorm to analyze a web application, showing features like: * Recording requests and responses * Naming and recalling specific requests * Searching for values within recordings * Defining and running print statements on recordings * *0:21:20** Demo: Data Windows for HTML Visualization:* The speaker introduces data windows, a new feature for visualizing data, and demonstrates how to view HTML output directly within FlowStorm. * *0:22:17** Demo: Editor Integration:* The speaker shows how to jump from the editor to recordings and back, using features like: * Quick jump to function * "debugger;" statement for fast positioning * Defining all frame variables in the REPL * Opening source code from recordings * *0:27:45** Demo: Codebase Exploration:* The speaker demonstrates how to use FlowStorm to explore a new codebase (Clojure's core.async flow library), showing how to: * Record and analyze the creation of flows * Identify and analyze threads spawned by the library * Use bookmarks to mark interesting points in the recordings * *0:43:21** Accessing Recordings from the REPL:* FlowStorm allows programmatic access to recordings via the REPL using the `get-timeline` function. * *0:44:13** Demo: Outputs Panel:* The speaker introduces the outputs panel, a replacement for the REPL console that provides enhanced visualization and navigation of evaluation results. * *0:46:24** Demo: Data Windows:* Data windows are a system for data inspection and visualization, supporting: * Lazy navigation of nested data structures * Infinite sequences * Multiple visualizations * Custom visualizations * Clojure datafy and navigation * Real-time data visualization * *0:50:34** Custom Visualizations:* The speaker demonstrates how to create custom visualizations for specific data types, using a chessboard example. * *0:52:25** Datafy and Navigation Integration:* FlowStorm integrates with Clojure's datafy and navigation protocols, allowing seamless exploration of data structures that support these protocols. * *0:56:20** Built-in Visualizations:* FlowStorm provides built-in visualizations for numbers, byte arrays, and other common data types. * *0:56:27** EQL Queries:* Data windows support EQL (Extensible Query Language) queries for filtering and analyzing data. * *0:59:14** Real-time Visualization:* The speaker demonstrates how to create data windows that update in real time, using a sine wave example. * *1:01:04** Ants Demo:* The speaker revisits the classic "ants" demo to showcase how data windows can be used to visualize and debug agent-based simulations. * *1:03:05** Conclusion:* The speaker concludes by encouraging the audience to explore FlowStorm and its features. I used gemini-1.5-pro-exp-0827 on rocketrecap dot com to summarize the transcript. Cost (if I didn't use the free tier): $0.09 Input tokens: 63793 Output tokens: 1076

Amazing... Thanks.

Wonderful talk

Just a little disappointed he didn't run the Clojure and jank ray-tracers side-by-side.

What about clasp?

Jesus Christ please tell me this is workable

Mind blown....

Great video ! Seeing transducers build from scratch was amazing

v cool!!

Amazing technology. Keep insisting and fighting, keep finding more companies that want to use electric.

Looking forward to sneaking this in at work, they say i have to have it run in python ! Now they can't say no.

15:50 Running the debugger 16:30 rtrace 20:45 trace

Is this production ready?

Thank you! This might be the easiest way for my lazy, fragile Python brain to learn Clojure!

Thank you for your work! Clojure on python will be great, Python is almost the most popular language.

w Hy?

Just lost my Clojure job, thought about changing languages based on popularity. Then I found this and decided that I better stick around! That's some refreshing stuff after years of full stack work, I never thought these things can be improved! I can't wait to finish my first project with it!

Per your suggestion, anyone working on rebuilding REBL with electric?

Very interesting. Thanks!

Great talk. Thanks

Any chance this could be used for Emacs? I'm currently using DoomEmacs' repl offering but I'm gluing it together with a bit of elisp.

this is looking better every time. congrats

The implementation of the layer technique showed by Gerald in this video seems to give ability of 'dynamically adding hooks to the continuation, under the convention of layer name' to programmer.

This nigga is on 7G

Keep going,guys, this is important tech.

This is a fantastic talk. It’s impressive to see the progress and capabilities of Electric. I can’t wait to use it in a future project.

Oh boy... I wanted to quit software development because the industry is forcing me to learn React/Angular just to slave away at my job and stay relevant to the latest js framework. I'll just quit my current job and start using electric. Thank you for this tool

wow

Compare something like "lein new luminus guestbook +h2 +http-kit" versus "clojure -Tnew create :template io.github.kit-clj :name eric/guestbook". I prefer that lein command. I hope you guys can make kit command-line usage simpler.

y these kinds of demos never come with "here's what we made with this thing."

Oh my God..... I'm switching to clojure

用graph控制continuation倒真是个好办法. 反正graph也是个值, 求值状态是另外一个graph, 这样执行的高阶抽象就有了.

why clojure? is it fast?

Greetings from Germany to all Germans! and others elsewhere worldwide :D

On the first point, I would like to say that yes, all tools have downsides. However, there are tools whose downsides didn’t originate as a trade-off, but rather as a result of unconsciously bringing what’s familiar into a newly created tool. There are so far tools that are objectively much better than others in their field. And we should improve precisely these tools, preferably by learning from the other awesome tools. Let’s enumerate the best so far: 1. Embedded and low-level: Zig. 2. Theoretical: Haskell. 3. Server systems: Erlang/Clojure. Does the world need more than these languages? No. Moreover, if Haskell, Erlang and Zig were Lisps, nobody could say that there is a language that is better at some tasks than them, since they could just be extended to be semantically like that better language. So, we can all do objectively better, and we should strive to do that.

I lost all interest whatsoever in all other front end related tech - thanks for that :(

This is incredibly impressive

18:13 suddenly LISP stares at me in the face..

Amazing work, thank you for this. Excellent presentation.

54:17 about the name of this "interactive comment" pattern. I realized that the theoretical foundation of this thing might be "The Explicit-Control Evaluator" from SICP 2e Sec 5.4, because exactly what you do is to manually control the evaluator to interprete your source codes beyond the normal opearations of Clojure automatic tool chain. Oh my JVM, the lisp machines are back. Hence, the title may also be dubbed "Turning JVM(or node) into a Modern Lisp Machine".

And not to be that guy but every database is also a database over files. Nice thing here is that you understand and control the formats and indexes.

Great talk and I love the motivation

i am Elixir dev, but this thing remember me to Phoenix in certain things, and I love it, definitely, i will try it

Thank you for Biff. So much care and thought you put into this .

Great demo!!!! Still complete up to date and valid for Pathom!

👍

if only we can port emacs into this.

I find the way you explained the problem very useful as I never thought about using linear algebra directly especially when dealing with large quantities of data. It also help what actually happens inside libraries. Thank you Dragan!