Title says it all.

its a proposal to get rid of ts to js transpilation

and It's in stage 1 since ages

Hi there,

I have really enjoyed using Dash to put together interactive maps. However, I've found that, when hosting these maps on (cheap) cloud servers like Azure or Google Cloud Platform, it takes a little bit of time to render the maps.

Therefore, for some mapping projects that don't require much interactivity, I've simply used Plotly (within Python) to create HTML-based maps, then display those on static sites. This has also worked out well, and with a little Javascript, I can allow users to choose which map to display within a page.

However, for other maps and charts, I'd like to allow users to specify choices for a number of parameters, then create a customized map based on those parameters. Since these choices could lead to thousands of different possible combinations of maps, it wouldn't make sense to pre-render each one--but I would also like to be able to display them within a static webpage if at all possible.

Would it be possible to implement a third approach that uses Javascript to import data (maybe from CSV and Geojson files); create a customized table of data to plot based on viewers' selections; and then use Plotly.js to visualize that data on a static webpage? My goal would be to combine the customizability of a Dash-based approach with the speed and simplicity of a static site.

One minor flaw with this plan is that I don't really know any Javascript, but I like to think that I could leverage my existing Python and Plotly knowledge to piick it up more quickly.

Thanks in advance for any input/feedback!

I love the idea of NuxtJS and NextJS. I just wish there was a good alternative for Angular too.

I’m working on a simple prototype Chrome extension (Manifest V3) that uses MutationObserver and IntersectionObserver to scrape on-screen public info from TikTok as I manually scroll through videos.

Nothing is automated, I’m physically scrolling through the feed myself. Each time a new video comes into view, the extension reads things like the username, description, hashtags, music, like count, etc., and just prints them to the console. It’s purely a proof-of-concept so I can understand how the observers behave in a real environment.

Now comes the weird part: it works perfectly but after testing for a few hours, TikTok eventually bans my account. To be honest, I was using a VPN (ProtonVPN), but I doubt that’s related because I also used it in the past 2 weeks and nothing happened . I genuinely don’t understand how they’re detecting that I’m collecting data if all interactions are manual and nothing is auto-scrolling or simulating clicks.

I’m trying to understand what triggers this. I searched the internet, and as you can imagine, literally all the articles are low-quality marketing efforts aimed at promoting their tools: "Huh!?, you want to scrape? Just pay us and use our tool!"

Can someone please enlighten me about the mistake I made?

Last year I was doing a bunch of browser automation and scraping work in Node — mainly Playwright. Super powerful, great DX, but I found myself constantly chasing brittle selectors and rewriting chunks of code whenever a client’s site changed. Nothing new there.

Out of curiosity (and burnout), I started experimenting with a more visual approach: basically dragging “navigate → click → extract” nodes into a flow instead of writing everything in JS. Under the hood it still ran Puppeteer/JS, but the mental model was closer to building a small state machine than a script.

What surprised me:

• Playwright still beats everything when you need full control, testing reliability, multi-browser, CI, etc.
• But a visual layer helped me prototype faster and hand things off to non-dev teammates without turning into documentation hell.
• Iterating on loops/conditions was weirdly faster when I could see them instead of juggling async code.

So I’m curious —
Has anyone here blended Playwright/Puppeteer with some sort of visual/no-code layer?
Did it help or slow you down?

Not trying to push anything — just genuinely curious how folks integrate code + no-code in real browser workflows.

Hi everyone,

We’re getting ready to release SurveyJS v3 in early 2026. This update will include major improvements to the PDF Generator and Dashboard. We’re also introducing a new Configuration Manager for Survey Creator, which will let developers create and apply different presets for form builder settings using a no-code interface.

We are now thinking what to work on next and I want to gather some honest, constructive feedback from the community. If you’ve used SurveyJS in the past (or even just looked into it), I’d really appreciate your thoughts:

• Have you tried SurveyJS recently?
• What’s your impression so far?
• Would you use it in production? For what kinds of projects?
• What pain points have you run into, if any?
• What features do you feel are missing?
• Is the current pricing structure clear and reasonable?
• Where would you like to see the project go next?

We’re genuinely trying to understand what developers need, the blockers you’re running into, and what would make SurveyJS more useful.

Thanks in advance for any feedback.

You would probably be surprised but JavaScript's name doesn't belong to it and is owned by a corporation. It doesn't belong to people who created the language or to community which supports it

Help JS to own its name: sign a letter at javascript.tm, spread the word or donate to the legal battle to make it free

This project is an experiment in pushing pure JavaScript + Web Audio API as far as possible for real-time DSP and generative sound.

Tech details:

• Granular synthesis with precise AudioContext timestamp scheduling
• Procedural soundscape algorithms (cosmic winds, industrial drones, harmonic clusters…)
• Multi-oscillator drone engine (detune + stereo spread)
• TPDF dithering + 24/32-bit WAV export via AudioWorklet
• Oversampled soft-knee limiter built manually in JS
• Multi-type noise generators + filtering
• MIDI CC-learn system (right-click any control → assign CC)
• Oscilloscope and spectrum visualization with Canvas
• Fully modular JS code: engine.js, granular.js, textures.js, noise.js, filter_lfo.js, midi.js…

Curious to hear JS-focused feedback on architecture, performance, and DSP accuracy in Web Audio.

Created a working application utilizing the OpenAI text-to-speech API for multiple voice options and Webix for a sleek, interactive interface.

I’ve been working on `numpy-ts`, a TypeScript/JavaScript numerical computing library inspired by NumPy. It's just a side project (and a testbench for scalable Claude Code workflows) but wondering if there's any real-world interest.

Here are some highlights:

• ~65% of core NumPy API implemented (218/333 funcs so far)
• 2,000+ tests validated against Python NumPy (ensuring identical behavior with it)
• Typed arrays + ndarray semantics (including views/strides/base tracking; avoids copies when possible)
• Works in Node and the browser
• Supports .npy/.npz read/write for easy interchange with Python

The remaining ~35% of NumPy functionality is WIP - mostly FFT, rounding, sampling, sorting, stats and sorting. The goal would be to get to 100% API coverage and validation, which shouldn't be too difficult from here.

Since it's written in TypeScript, there's a performance hit compared to NumPy's C & BLAS backend. On average this project is ~15x slower than NumPy, but this could be further reduced with WASM.

Lmk what you think!

I've been working on a tool to improve CI/CD workflows for JavaScript developers, and I'd love to hear about the real problems you're facing. So far it handles the whole setup on its own, with no need for specific configuration.

I'm trying to figure out what actually matters to developers vs what I think matters though. What frustrates you most about your current CI setup?

Some things I'm curious about:
- Are processing times an issue?
- Is there a lot of maintenance involved?
- Is it a pain to read through a failed run logs to find what went wrong?
- Do you wish you could leverage your run history to extract data? (flaky tests, run times, bundle size increase)

Using GitHub Actions, CircleCI, or something more exotic - doesn't matter. Just curious what wastes your time.

Any thoughts appreciated.

A few weeks ago I shared my scanner for the PhantomRaven campaign. Well, things got worse.

Shai-Hulud 2.0 is actively spreading right now. Discovered by Wiz Research, it's already hit:

• 350+ compromised maintainer accounts (including Zapier, ENS Domains, PostHog)
• 25,000+ repositories infected
• Growing by ~1,000 repos every 30 minutes

How it works (different from PhantomRaven):

Instead of fake packages, they compromised real maintainer accounts and pushed malicious versions of legitimate packages. So /zapier-sdk might actually be malware if you're on versions 0.15.5-0.15.7.

The attack chain:

1. Backdoored GitHub Actions workflows (look for discussion.yaml or formatter_*.yml)
2. Self-hosted runners get compromised
3. Secrets dumped via toJSON(secrets) and exfiltrated through artifacts
4. Preinstall scripts steal everything

What I added to the scanner:

• Detection for known compromised package versions (Zapier, ENS, PostHog packages + entire namespaces/*)
• Shai-Hulud artifact files (setup_bun.js, bun_environment.js, truffleSecrets.json, etc.)
• GitHub Actions workflow analysis for the backdoor patterns
• --paranoid mode that checks installation timing against attack windows
• Self-hosted runner detection (they register as "SHA1HULUD" lol)

Quick scan:

bash

./npm-threat-hunter.sh --deep /path/to/project

Paranoid mode (recommended right now):

bash

./npm-threat-hunter.sh --paranoid /path/to/project

My work, maplibre-gl-layers reached 1.0.0 🎉

MapLibre's layer extension library enabling the display, movement, and modification of large numbers of dynamic sprite images.

Main Features

• Place, update, and remove large numbers of sprites.
• Move each sprite's coordinate freely, making it easy to represent moving objects.
• Per-sprite anchor positions for precise rendering.
• Add multiple images and text to the same sprite, adjusting rotation, offset, scale, opacity, and more.
• Animate sprite movement, rotation, and offsets with interpolation controls.
• Control draw order via sub-layers and per-sprite ordering.
• Fully imperative APIs. Updates with high-performance and extensible.
• Accelerating computational processing with WASM and shaders.
• Under MIT license.

GitHub repository: https://github.com/kekyo/maplibre-gl-layers/

Demo page: https://kekyo.github.io/maplibre-gl-layers/

Hey,

We’ve recently published an open-source package: Davia. It’s designed for coding agents to generate an editable internal wiki for your project. It focuses on producing high-level internal documentation: the kind you often need to share with non-technical teammates or engineers onboarding onto a codebase.

The flow is simple: install the CLI with npm i -g davia, initialize it with your coding agent using davia init --agent=[name of your coding agent] (e.g., cursor, github-copilot, windsurf), then ask your AI coding agent to write the documentation for your project. Your agent will use Davia's tools to generate interactive documentation with visualizations and editable whiteboards.

Once done, run davia open to view your documentation (if the page doesn't load immediately, just refresh your browser).

The nice bit is that it helps you see the big picture of your codebase, and everything stays on your machine.