I'm the only mobile dex on a react app that ships to about 20k users and I have been doing this alone for around more than a year now. Our release process is me writing the feature, testing it on my iphone and my pixel, push to gi, if it turns green I ship and I refresh the app store reviews page every couple hours for the next week to see if something's fked up.

Last release a bloke in brazil reported the app crashed on launch on a12L and I couldn't reproduce because I don't have that device and had to wait for the fix for a week trying to source one plus my review average dropped 0.5 stars.

The thing is I need someone to verify the stuff I wrote didn't break on devices I literally dont have. Every mobile team I look at either has a QA person or a testing tool for the device matrix but every dev I ask says they can't recommend the tool they use because of n number of reasons idk.

help me devs, what should i actually do here?

I am stuck in a serious problem my startup registered address was in Andhra Pradesh but now our start-up commute in Rajasthan now after 2 months they have assigned a person for physical verification but he will visit the registered address in Andhra Pradesh so is there any solution that it can be done online or they can visit in rajsthan

I wanted to explore how far SVG paths, Skia, and Reanimated could go beyond a looping animation.

So I built Fledge: two eggs hatch into birds, the birds take flight, and the whole scene transforms into a shared savings goal.

The interesting part is that the animation’s elements become the actual interface:

• The birds become contributor avatars.
• The horizon becomes the savings track.
• The eggshell fragments become milestone ticks.
• The headline moves into the goal title.

It all happens inside one mounted React Native tree.

Built with Expo, SVG paths, Skia, Reanimated, and Gesture Handler. No prebuilt animation assets.

Every JS collapsible-tab library (Reanimated ones included) moves the header from the scroll event, so it trails the list by at least a frame. You see it as a gap under the tab bar on a fast fling, especially on Android.

I moved the whole shell native: a paging UIScrollView / ViewPager2 with header and tab-bar bands translated inside the same native scroll callback that moves the list. React still owns the header, tab bar and pages as normal components. Any list that renders an RN ScrollView works as a page (FlatList, FlashList, LegendList).

Extras: mount-on-peek, short tabs still collapse, container pull-to-refresh, `ref` with scrollToTop/collapse/expand, `collapseMode="direction"` for the home-feed feel, and opt-in per-frame events meant for Reanimated worklets.

Limits up front: Fabric only, RN 0.80+, no web, header swipes are inert, platform refresh indicator only.

Repo with example app and GIFs: https://github.com/ramssutharr/react-native-collapsible-tabs-native

Feedback on the native code welcome, it is two files.

https://reddit.com/link/1waflrp/video/7vqibzwhh8oh1/player

1. Design in Figma

Create your mascot with different expressions, like open and closed eyes. Keep all the elements in the same frame and use opacity to hide/show parts. Duplicate the frames to create as many expressions as you need, then use Figma Prototype to animate them.

2. Export with LottieFiles

Use the LottieFiles Figma plugin to export your animation as a .json file.

3. Add it to React Native

Use LottieView from lottie-react-native to load the JSON animation in your app.

Figma + Lottie makes it surprisingly easy to create animated mascots for mobile apps.

Used GPT-6 Astra to bring Dark Magician to life with 3D tilt, layered parallax, and four holographic foil effects.
Stack: Expo + React Native, with Three.js/WebGL running in a WebView.
Which holo effect looks closest to a real collectible card?

A screen in an expense tracker I maintain opened empty on the owner's OPPO Find X9 Pro (ColorOS, density 560 overridden to 480) and never once on my Samsung.

I shipped four fixes before I diagnosed anything: a nested-scroll theory, a 2.0.2 to 2.3.2 bump whose release notes matched my symptom almost word for word ("average measurement always positive", "guard against zero window size"), drawDistance, and moving a line out of ListHeaderComponent. None of them changed a thing, and I had to be told so three times.

Ten minutes of instrumentation on the phone that was actually failing ended it:

[applist] render items=11
[radar]   renderCell #0 ... #5
[applist] onLoad elapsed=38ms
uiautomator: 29 nodes, ZERO cells  ->  77 after a 100px scroll

React rendered six cards. FlashList reported itself loaded in 38ms. The native tree held none of them until a scroll nudged it. Cells built and never placed, somewhere no prop of mine reaches.

Three things I took out of it:

1. The screen stopped needing the recycler. Eighty other screens in the app draw a plain column of cards inside a ScrollView and not one has ever failed this way. Under 40 items that screen now draws the same column, and the recycler stays only for the pathological case (444 duplicate groups at 100k transactions).

2. Virtualization stayed everywhere else. I measured before deleting anything: a 500-card plain column runs 11.95% janky frames. The recycler earns its place on long lists, it just wasn't earning it on that one.

3. Detect the failure, don't name the phone. Copying the OPPO's wm size and density onto the Samsung reproduced nothing, so a device check would have been a guess with an OEM name on it. The list now watches for its own failure (zero-height content under a real viewport with rows still in the data, one second after layout) and falls back to a paged plain column.

The first version of that detector was completely inert on the device, with four green tests behind it. It read onLayout off FlashList, which never sends one, and the tests fired the callback by hand. I found that by setting the threshold so every list in the app would declare itself broken, installing it, and looking at the screen. Measure on a View you own.

Has anyone else seen a recycler build cells and never place them on one specific OEM? Curious whether this is ColorOS-specific or a density-override thing.

Hi everyone,

I'm a mobile dev currently tasked with building a superapp. Since I don't have prior experience with superapp architecture, I'm a bit unsure about choosing the right tech stack for the host app and the bridge/integration layer for mini-apps.

Since I’m proficient in both React Native and Flutter, I’d strongly prefer sticking to a cross-platform solution rather than going fully native.

If you were to build a superapp today, what tech stack / combo would you go with? Would love to hear your recommendations and real-world experiences!

Hey all,

I'm in the middle of planning a side project to upskill on a few things. Simple idea without going into it --> Golf related app whereby a player can talk through a shot or a hole and it gets converted into structured data that they can save and later query using an LLM.

Obviously a big part of this idea is having some form of speech to text that can be converted into structured data and stored.

I'm here to understand what options I have regarding doing this locally on the mobile device or via a react native VS doing the speech to text translation on the API server layer. My understanding so far is that I'm likely going to want to it locally given that signal on golf courses can be somewhat poor and sending audio files into the ether is just simply going to fall short in reality?

That said, I've also read that local speech to text ( native android or ios or react native STT ) is just nowhere near as accurate and may have a hard time understanding specific golf lingo?

Feels like I'm stuck between a rock and a hard place but any input or recommendations are much appreciated here.

Note: this project is mainly for self learning with a touch of 'it could be useful for me so may be useful for others in future' in the back of my mind. I can be pragmatic on my decision but would like to make the right one!

Thanks in advance

I built an Expo app for iOS, Android, and web from one TypeScript codebase. The screens were mostly straightforward. The parts that took real care were the seams between platforms.

RevenueCat was the first one. Native uses react-native-purchases, while web uses purchases-js, so the implementation is not a single API call hidden behind a platform check. I lazy-load the web SDK so it does not affect the initial bundle, persist its anonymous RevenueCat user ID, and change that user to the authenticated app user after login.

The important lesson was to make the entitlement, rather than a successful purchase response, the source of truth for access. After login, purchase, restore, or a connectivity change, the app refreshes CustomerInfo and maps the active pro entitlement into one shared subscription state. Web restore is effectively a fresh CustomerInfo fetch, not the same store restore flow as native, which is worth handling explicitly.

Convex made the reading pipeline pleasantly boring. A reading result is written in one mutation, and that mutation schedules the follow-up lucky-window notification with runAfter. The notification action checks that the reading is still ready, writes an in-app notification, then sends to every active Expo push token. That recheck matters because a scheduled action can fire long after the state that created it has changed.

The tablet layout was the other surprisingly easy-to-miss issue. A phone-first screen can technically work on an iPad while still looking like a narrow phone floating in empty space. Constraining the reading content to maxWidth 720 and treating the surrounding space as part of the composition made the web and tablet versions feel intentional without creating a separate layout system.

PS: First 48 testers on Android and iPhone/iPad TestFlight get 1 year Pro version for free. Go to the website click on the Android/iOS links and add you to TestFlight. Link in my bio or will add it in the first comment :)

I built a study app for university students and I need 12 testers to sit

through Google's 14-day closed testing window. I'd much rather get real

feedback than just install counts, so tell me what's broken.

What it actually does:

You upload your syllabus and it maps out your semester — topics by week,

assessment dates, the lot. Then from your lecture slides, notes or a

recording of the lecture itself, it generates summaries, flashcards,

practice quizzes and a two-voice podcast you can listen to on the walk in.

There's also a PDF reader you can annotate and have read aloud, an AI tutor

that answers from your own uploaded material rather than the open internet,

and an essay co-writer. It runs in 40 languages.

Two steps to join:

1. Join the tester group. Google requires this before it will let you in:

   https://groups.google.com/g/mystudysidekick-testers

   Use the same Google account that's signed into the Play Store on your

   phone. This is the step everyone gets wrong.

2. Then open this and tap "Become a tester":

   https://play.google.com/apps/testing/com.studysidekick.app

Give it 10-15 minutes to show up in Play after you opt in. If it's slow,

force stop the Play Store app and clear its cache.

What I'd genuinely like feedback on:

- Does the syllabus parsing get YOUR course right? That's the part I'm

least confident about, because every university formats these

differently and I've only tested a handful.

- Are the flashcards and quizzes accurate to your material, or does it

invent things that aren't in your notes?

- Anything slow, confusing or plain broken.

Feedback here in the comments, or to mystudysidekick@gmail.com.

Drop your testing link below and I'll join yours today — happy to leave

real feedback on yours too, not just an install.

One ask: Google needs testers opted in continuously for 14 days, so please

keep it installed if you can. If you drop out early it resets my count.

I implemented a the web NFC api for react native but as I cant use it for my goals it was just waste of time.

Android demo of my React Native + Expo particle-dispersion effect.

ML Kit isolates the subject; OpenGL ES 3 renders the particles; Skia + Reanimated handle compositing and timing.

Yesterday’s iOS demo + discussion:

https://x.com/ngocdevv/status/2096146146460880943

Inspired by 60fpsdesign on X.

I’m currently exploring full-time remote opportunities as a Senior React.js Engineer / Frontend Engineer / Tech Lead, and I’m open to working with teams across any time zone.

I have 10+ years of software engineering experience, with a strong focus on React.js, Next.js, TypeScript, JavaScript, and React Native.

A few things that define my experience:

• 🚀 React.js & Next.js — building production-grade applications, reusable component systems, performance-focused UIs, SSG/ISR, and modern frontend architectures.

• 📱 React Native — full ownership from architecture and development all the way to iOS/Android builds, CI/CD, signing, TestFlight/App Store and Google Play releases.

• 🧑‍💻 Strong hands-on ownership — I’ve independently designed and delivered products end-to-end, including working directly with requirements, architecture, development, deployment, and ongoing improvements.

• 🌎 Multiple clients & products — experience working across different client projects and business domains, adapting quickly to new requirements and technologies.

• 👥 Technical leadership — experience leading teams, mentoring developers, conducting interviews, establishing engineering processes, and driving projects from kickoff to delivery.

• 🤝 Client & stakeholder communication — comfortable communicating directly with clients and stakeholders, translating business requirements into practical technical solutions, and working effectively with distributed teams.

• ⚡ Performance & scalability — Core Web Vitals, caching, lazy loading, virtualization, memoization, bundle optimization, and scalable component architecture.

I’ve also worked on enterprise platforms, logistics systems, LLM/RAG applications, content management platforms, and white-label mobile products.

I’m looking for a team where I can stay hands-on technically while also bringing my leadership and ownership experience.

📍 Location: Hyderabad, India
🌍 Preference: Fully Remote
🕐 Timezone: Open to any time zone
💼 Availability: Full-time/ Contract opportunities

LinkedIn: https://linkedin.com/in/anurag-vasi-46595810a

If you’re hiring for a senior React/Next.js/React Native role, or know of a team looking for someone with this background, I’d be happy to connect.

Thanks! 🙌

Hey everyone, working on a college project, an OCR project, for Nepali documents (citizenship certificates, land records etc.) and stuck on one part. Looking for suggestions.

What I've done so far:

Trained a TrOCR model (fine-tuned from a Devanagari pre-trained checkpoint) on Nepali printed text. Current accuracy is CER 3.94% (~96% character accuracy) after 75 epochs.

Training data used:

Real datasets:

gauravgiri/nepali-ocr — 17,765 samples

nahcol — 1,203 samples

iiit-hw-dev (IIIT Hyderabad handwritten Devanagari) — 69,853 samples

doc-recognition — 4,358 samples

Synthetic (generated using PIL + Devanagari fonts, corpus from Nepali textbooks + news text):

100,000 synthetic line images

Total: ~193,000 training samples

The model itself works fine — if I manually crop a line of text from a citizenship certificate and feed it in, it reads it correctly. The problem is automating the cropping.

The issue:

Nepali citizenship certificates have a yellow-green watermark/pattern background. The card is embedded in a scanned white A4 page. I'm using OpenCV to:

Detect the card from the page ✓

Binarize (remove pattern background) ✓

Detect individual text lines using morphological dilation + contour detection — this is where it breaks

The left side of the card has field labels ("जन्म स्थान:", "स्थायी बासस्थान:", "जन्म मिति:" etc.) sitting right next to the photo area. When I dilate horizontally to merge characters into line blobs, these labels merge with the photo region and disappear from detection.

Looking for: A good approach for text line segmentation on structured form documents with patterned backgrounds. Has anyone dealt with something similar? Any OpenCV tricks or layout analysis libraries that handle this well?

Also — if anyone knows of good real labeled Nepali/Devanagari printed document datasets (not synthetic), would appreciate the links. The more real document data the better.

Any suggestion to make this project better is welcomed by heart.

I wanna build a journal app that the user beside creating journal entries be able to draw some basic things, is react native a good choice here?

Hey everyone,

Like a lot of people here, I’ve always struggled with receipt tracking. Personal expenses, freelance work, small business costs, shared household spending it all ends up as a messy pile of paper receipts, screenshots, and half-filled spreadsheets.

Manually entering everything is slow, boring, and easy to mess up.

What I really wanted was something simple:

scan a receipt → extract the data → send it straight to Google Sheets.

No heavy accounting software. No complicated setup.

But I also wanted something that worked beyond just personal tracking especially for families, couples, roommates, or anyone sharing expenses. Things like groceries, household items, bills, eating out, or travel spending are usually paid by different people, and it becomes hard to know where the money is actually going.

I couldn’t find exactly that, so I decided to build it.

After wasting way too many hours manually logging receipts and realizing how many expenses I was missing, I built ReceiptSync an AI-powered app that automates receipt tracking and helps people manage spending individually or together through a shared family wallet.

How it works:

• Snap a photo of any receipt
• AI-powered OCR extracts line items, merchant, date, tax, totals, and category
• Duplicate receipts are automatically detected
• Data syncs instantly to Google Sheets
• Add expenses to a shared family/household wallet
• Track spending together with family, partners, or roommates
• Total time: ~3 seconds

What makes it different:

• Smart search using natural language, like “show my Uber expenses from last month”
• Line-item extraction, not just totals
• Duplicate detection to avoid double logging
• Shared family wallet for household expenses
• Interactive insights for spending patterns and trends
• Built specifically for Google Sheets export
• Useful for personal expenses, freelance work, small business costs, and shared family spending

I’ve been testing it for the past month with a small group, and the feedback has been amazing. People are saving 5–10 hours per month just on expense tracking, and the shared wallet feature has been especially useful for families and households trying to understand where their money is going.

If this sounds useful, here’s the app:
https://apps.apple.com/us/app/receiptsync-receipt-tracker/id6756007251

I use React Navigation anyway, and for things like camera access, there are React Native-specific APIs/libraries available. So I'm not sure what Expo adds.

I may use EAS for builds/deployment, but do I really need the Expo layer itself?

Also, React Native docs recommend using a framework for new apps. Is Expo basically the recommended approach now?