making SwiftUI views in computed properties within views gives me the ick. it feels like it might interfere with perf optimizations in swiftui but I haven't measured. Has anyone seen any official guidance/research on this?
I put SwiftUI vs UIKit scroll performance to the ultimate test: an infinite scrolling feed full of interactive 90s GIFs.
The results? Well, see for yourself...
@SebastianRoehl It is much, much slower than CoreData… for small projects using few entries it is totally fine… for large databases, the performance gap is still massive
Implementing the SwiftData models for my Pomodoro side project. This is soooo easy 👌 Lots of people saying that SwiftData isn't mature enough for "real" apps. Anyone else had problems with it? If yes, which issues did you face?
Grazie al modello danese di #EdiliziaSociale, chiunque può aspirare a una #casa a prezzi accessibili, l’#affitto non supera mai il 30% dello #stipendio, a fare da garante lo Stato e gli stessi cittadini, in un sistema finanziariamente virtuoso.
#PresaDiretta#Danimarca
@stai_laggando@Presa_Diretta Ti assicuro che é cambiato poco, anzi… 😂 non so in quale Copenhagen hanno fatto il servizio 😂… gli affitti sono il 30% dello stipendio, in 40 mq senza bagno
@Presa_Diretta Ero rimasta a pochi anni fa, Copenhagen capitale più cara e mercato immobiliare totalmente inaccessibile, nel paese con le tasse più alte d'Europa.
I redesigned the ASATools reports. The default tab now includes:
1) installs, spends, and proceeds to determine if enough data has been collected
2) CPT bid and CPA goal which you can adjust
3) avg CPT, avg CPA, and LTV to help bid decisions
4) impression share to show the percentage of traffic you're buying
5) match rate to see if installs are actually coming from the keyword you're targeting
6) ROAS to quickly identify profitable keywords
#searchads#asa
@wilterrero Not to be rude but this is misleading 😒. You got a spike due to App Advice and then back to near zero… this is not what good keywords ranking leads to…
Before building any app
Research first. Code later
My app hit 18,000 downloads, 270 reviews
All from organic search (ASO)
Here's why research beats coding every time:
1. I analyzed 50+ competitor apps
⌙ Found features users loved
⌙ Discovered what was missing
2. Identified untapped keywords
• High search volume (8,000+ searches)
• Low difficulty score (under 30)
• Clear user intent
3. Built exactly what users were searching for
• Not what I thought was cool
• Not what tech blogs said was trending
• Just what real users wanted
Before:
• Cool tech stack
• Clever architecture
• Features nobody used
• 0 downloads
After:
• Simple solution
• Core features only
• Solving real problems
• 10,000+ happy users
Most devs build first, then hunt for users
I found the users first, then built what they needed
Stop coding. Start researching
Ptychographic X-ray nanotomography captures the process of water filling nanoscale pores in a hydrogen fuel cell catalyst in unprecedented detail, overcoming previous limits in resolution and speed. @GuizarSicairos#Xraysbrnw.ch/21wOgCc
Very first 3D ptychographic user experiment at #NanoMAX. Impressive work by Maik @kahnt_m and by all #NanoMAX team in making this work… Thanks @jens_wenzel and @aditshuk for all the fun at the beamline!
Don't wait for perfection before you ship.
Here's how some of the biggest products on the internet got their start.
Products evolve. Stop waiting. Just ship it.
For iOS apps, I’m convinced that download volume is the dominant ASO factor than ratings and all other factors for improving organic keyword rankings. The keyword list in AppStore Connect is overrated. Only keywords that matter are that are in title/subtitle. #buildinpublic
Unpopular opinion: #Python sucks! For the sake of simplicity, there are too many trades-off. Now, it is clearly too big to fail. I also wondered why, at some point, we started considering explicit types as useless complexity…
In case you're following the news about the supposed Korean superconductor breakthrough, there's some guys on twitch livestreaming their reproduction attempt (though nothing will happen until they've baked the stuff, 9:40 pm Pacific Time) #LK99twitch.tv/andrewmccalip
Still amazed by the flexibility given by the #blender Python API. I made a small animation making the individual grains of a Ni-YSZ structure appear. This time, I used #Eeevee as a rendering engine, much faster but not ray-traced.
@esrfsynchrotron@SoM_esrf
I needed a way to visualize grain orientation in 3D from 3DXRD data… so I sat down and wrote my own data format, imported it to #blender using the Python interface, and voila’ 😍 😍 😍.
Thanks @jonwright76, @jens_wenzel, for the nice beam time and data!
So, I finally found a way to make the fans of my M1 Mac spin… Cycles render in #blender of a real Ni-YSZ microstructure obtained at ID11 @ESRF, using scanning 3DXRD and a tiny nanobeam of 100 nm 😏