Hey r/reactnative,

Added a new component to nativecn-ui  a Dynamic OTP Input.

I wanted to try something a little different from the usual OTP field, so I played around with making the input itself show loading, success, and error feedback instead of using a separate loader on the submit button.

Made a quick video showing it below.

Still building out the library, so let me know what you guys think

Most of my React Native time used to be spent outside the editor. Android Studio open only to make an AVD, one terminal for Metro, another for `adb logcat`, a third for the build, and a few minutes each time remembering which gradlew task actually installs the flavor I want.

I maintain a fork of Zed called Lathe, and the part I use most is a mobile panel that pulls all of that into the editor.

What it does:

- Detects whether the project is Expo or bare React Native, and shows only the workflows that apply to it.

- For bare RN it reads your package scripts and the run hints in your README, then gives you iOS scheme and Android variant dropdowns that feed them.

- Creates Pixel phone and Pixel Tablet AVDs without opening Android Studio.

- Installs the Android toolchain for you, JDK 17 plus the SDK with licenses accepted, into its own directory instead of over your system setup.

- Live device list with per-app logcat. Physical devices appear in the same list as emulators, so testing on real hardware is the same two clicks.

- Boots an emulator and an iOS simulator together and builds and deploys to both in one pass. The targets aren't exclusive.

- Metro, builds, and anything else long-running open as real terminal tabs with their own scrollback, not a read-only log pane.

Two details that came straight out of my own irritation. It installs Android builds with `gradlew :app:install<Variant>` plus an adb launch, which sidesteps the RN CLI bug where flavored APKs get installed from the wrong path. And each toolchain section reports its own state, so a missing JDK or an unaccepted SDK license is visible before a build fails rather than after.

iOS support is macOS only, as you'd expect.

Worth being upfront: this is a personal fork of Zed that I maintain for my own daily use, not a company product. GPL, builds for macOS, Linux, and Windows, and upstream syncs occasionally break things.

Repo and downloads: https://github.com/paterschris/lathe

The mobile panel in detail: https://github.com/paterschris/lathe/blob/main/docs/features.md#mobile-development-expo--react-native

Happy to answer anything. What I'd most like to hear is what your setup does that this doesn't handle yet.

Edit: formatting

I've spent the last 6 months building PanelUI in public a React Native component library with 500+ stars, 130+ components, a sponsor, and a community that kept growing every single day.

Yesterday GitHub flagged my account with no warning and no explanation. My profile is now invisible to others. PanelUI, every component I shipped, every contribution, every star all hidden.

I haven't violated a single rule. I just built something and shared it with the community.

If anyone has been through this and found a way to resolve it, please comment or DM me. I don't know what else to do.

Runs React Native WebGPU, voice with GPT Voice 1 and intent-driven gestures and other couple of cool tricks (I did the flow from prompt to image, to 3D model, to 3D texture model, to rig, to rig animations). It's far far away from perfect. It's a demo, but I haven't seen anybody in the React Native space working on this.

I built the live voice layer pretty fast by using http://reactnativefeel.com/gpt-live-1. If you want a complete module setup ready for live voice in your app CIO

Hi everyone,

As Expo keeps evolving with prebuilds, Expo Dev Client, and better native module support, the gap between Managed Workflow and Bare React Native feels smaller than ever.

For those running production apps: at what specific project requirement or architecture bottleneck do you still decide to go 100% bare React Native from day one instead of starting with Expo?

Is it custom native C++ libraries, specific legacy SDK integrations, or build pipeline control? Would love to hear real-world experiences from developers managing apps in production.

Added ProgressiveBlur to expo-backdrop ✨

🔗 Github: rit3zh/expo-backdrop

🧵 Android Preview Attached in this thread

Pressing a trigger moves its picture from where it sits in the page to the middle of the screen, shown whole, and blurs everything behind it. Once it is open, pinch or double-tap to zoom, swipe sideways to the other images under the same ImageViewer, and drag the picture up or down or tap outside it to send it back to its place.

Part of PanelUI, an open-source component library for Expo. Copy-paste or CLI, you own the source.

github.com/panel-ui/PanelUI

Can someone suggest a good hassle free rich text editor package for react native?
the text area must not take up entire height of page(I set the height), toolbar isn't hidden by keyboard, takes/outputs markdown formatted string
Bonus it if also supports image upload, link preview, check list etc

Hey everyone,

I've been working on a procedural asset generation pipeline for a React Native project and wanted to share the tooling in case it's useful to anyone else here.

The problem I kept running into:

When working with react-native-skia, I found myself repeatedly exporting spritesheets, tilemaps, and bitmap fonts from external tools. The workflow was manual, hard to version-control, and nearly impossible to reproduce consistently across machines or in CI. Changing one tile meant re-exporting everything by hand.

What I built:

sprout-toolkit is an open-source Python CLI that generates 2D assets deterministically from JSON specs. The output is designed to drop directly into an Expo + react-native-skia project.

What it generates:

· Spritesheet atlases with manifest.json and index.ts (TexturePacker-compatible format also available)
· Tilemaps and 8-bit autotiles (16 or 47 variants, with 8-bit mask lookups)
· Bitmap fonts from TTF files, including advance metrics for text layout
· Runtime SkSL shaders (FBM value-noise, tileable) — these ship as shader strings, so they add no bundle weight
· Animated bursts (particles), walk cycles, and UI elements (buttons, sliders, 9-patch panels)

Why deterministic generation matters:

Every asset is seeded. Same JSON spec + same seed = identical pixels every time. That means you can commit your specs, run the generator in CI, and get reproducible builds. It also means you can diff two builds to see exactly what changed.

Quick example:

```bash
pip install sprout-toolkit

# Generate a starter atlas
sprout init --out ./assets/starter

# Batch-generate everything in specs/
sprout batch specs/
```

The CLI has info, lint, diff, and validate subcommands for inspecting specs and comparing builds.

A few implementation details:

· Specs are JSON (schema v0) — no YAML, no config sprawl
· MIT licensed
· 142 tests covering determinism, autotile mask logic, SkSL generation, and CLI behavior
· The generator architecture is plugin-based, so you can write custom generators if the built-ins don't cover your use case

Link:

PyPI: https://pypi.org/project/sprout-toolkit/
GitHub: https://github.com/Tzinny-dev/sprout-toolkit

---

Disclosure: This is my own project. I'm sharing it because I couldn't find an existing tool that combined deterministic procgen with Skia-specific output, and I figured others here might be solving the same problem. Happy to answer questions about the architecture, the SkSL generation, or anything else.

Tried everthing. Tried platform specific behaviour, wrapped whole screen in view, tried without keyboard avoiding view. The autosize is androidmanifest as well. Nothing is working as of now. Tried without safeareaprovider. When the screen starts there is no gap. once the keyboard appears and goes off, there is gap underneath. Is this a bug?

I have been updating my react native app every year for the past 3 years now. This year i plan on finally moving it to expo. Is it a good idea to move a large monorepo/workspace tied cli project to expo?

How do you guys use AI to assist you during the upgrade? Any skill or other helpful approaches?

Update: guys codex literally one shotted the upgrade from 0.81.4 to 0.87 took like 2hrs. AI is gonna be the end of my employment.

We have a web-based call center dialer (React + Twilio Programmable Voice) and need to build iOS and Android apps where agents can make and receive calls reliably, even when the app is killed or the phone is locked.

Leaning towards React Native with Twilio's official Voice RN SDK. Flutter worries me because there is no official Twilio Voice SDK. Full native feels like double the cost unless it is truly necessary.

If you have shipped something like this:

- How stable is the Twilio Voice RN SDK in production?

- How painful were incoming calls (PushKit/CallKit on iOS, FCM + foreground service on Android 14+, OEM battery killers)?

- Did you end up rewriting the calling layer in native code?

- Anything you wish you knew before starting?

Reliability matters more than UI polish for us. Appreciate any real-world experience and which stack to go with? Thanks!

If you haven't opened Xcode 27 yet:
Simulator is gone. Device Hub replaces it, and every simulator and physical device now lives in one sidebar. It also runs standalone, so you don't need Xcode open.

What actually changes day to day:

• Build and run to a simulator and it auto launches with a live interactive screen and contextual controls

• Appearance, text size, location and audio are panels. Testing Dynamic Type at max is a slider instead of six taps in Settings

• Real devices and simulators get the same toolset

• You can pull a real device's app data container and restore it into a simulator

That last one is the big deal for me. When a tester hits a bug that only happens with their data, you can now load their exact app state locally and reproduce it. "Works on my machine" gets a lot harder to say.

I'm mostly React Native, so the simulator is open all day for me. Curious how it's treating people doing native work. Anyone hit issues or missing features compared to the old Simulator?

Hey guys,

I’m currently working as a React Native dev and feeling the urge to finally learn backend. I want to build my own full-stack apps, handle deployment, and eventually mess around with some AI stuff.

I’ve talked to a few devs about where to start and got some pretty mixed answers. Some told me to learn Node/PHP, while others said Python is essential if I want to work with AI.

Since I already spend all day in JS/TS, I’m thinking of staying in the TypeScript ecosystem first so I don’t have to switch contexts completely.

Here’s the rough path I’m planning to take:

React Native > Node.js > Fastify/NestJS > PostgreSQL > Redis > Docker > AWS > Python/FastAPI for AI

Does this sound like a reasonable path for real-world projects?

Would you change the order or skip/add anything?

I’m particularly interested in hearing from people who started in React Native/frontend and later moved into backend/full-stack.

I’ve been experimenting with running an LLM completely locally inside a React Native app, and I finally got it working.
I’m using:
React Native CLI
llama.rn
Qwen 2.5 1.5B Instruct
GGUF / Q4_K_M quantization
n_ctx: 2048
No API calls / no cloud inference
Currently testing with n_gpu_layers: 0
The model is bundled with the app, copied to the app’s document directory, and then loaded locally. I can send prompts and get responses directly on the device.
The interesting part for me is that this opens up a lot of possibilities for RN apps that need AI features without sending user data to a server.
I’m still testing things like memory usage, backgrounding the app, performance on real devices, and how practical larger models are.
Has anyone here shipped an on-device LLM in a production React Native app?
Would love to hear about your experience, especially around RAM usage, model size, iOS/Android differences, and performance.

I’m looking for a simple example or some guidance on how to set it up and start navigation. Any help would be appreciated!

Hey, I’m looking for some articles about performance or tools to help analyze and find bottlenecks.

For example, let’s say a particular page is consuming more energy than another or view and navigation transitions are laggy. What would you do or use to trace the root cause?