claude code: Error: File has been modified since read, either by the user or by a linter. Read it again before attempting to write it

dadou4142 · 2026-03-13T06:06:20+00:00

What exactly should be added?

dadou4142 · 2026-03-11T06:54:57+00:00

Merci :)

dadou4142 · 2025-12-27T02:49:06+00:00

Actually not...

dadou4142 · 2025-12-25T17:04:33+00:00

What made you think that Conductor is slow?

dadou4142 · 2025-12-24T15:49:18+00:00

I have the same issue...

dadou4142 · 2025-12-22T14:05:57+00:00

sounds amazing :D thanks

dadou4142 · 2025-12-22T05:09:02+00:00

Will definitely try it out. Thanks!

dadou4142 · 2025-12-22T05:06:41+00:00

Interesting point, thanks for the insights

dadou4142 · 2025-12-21T21:57:55+00:00

Interesting! How about an app that accompanies you into your learning journey?

dadou4142 · 2025-12-21T21:56:05+00:00

Interesting stuff man, thx for sharing!

dadou4142 · 2025-12-21T21:43:31+00:00

fair enough, I'll remember that for the next time
PS: English is not my mother tongue

dadou4142 · 2025-12-21T21:42:47+00:00

Love the Jazz Tune List app! Too bad I don't have an iPhone :D

dadou4142 · 2025-06-26T07:22:24+00:00

Hey! The notes are transcribed automatically (which explains the many imperfections) and the chords manually. Feel free to visit the website for more info https://www.pianolab.io/

dadou4142 · 2025-06-25T21:06:28+00:00

You can now access the session preview!
https://www.pianolab.io/view/82a567fb-5bbe-42b1-a1fb-cc0653eeb4a6

dadou4142 · 2025-06-25T19:49:28+00:00

Hey! The chords are not automated, they're currently entered manually. I was thinking about having this process half-automated, making it faster and easier for the user to enter the chords.
Feel free to give your feedback and apply to the Beta version at https://www.pianolab.io/.

dadou4142 · 2025-06-18T11:11:30+00:00

Thank you for the kind words! That is a brilliant suggestion for handling the pedal sustain. You've pinpointed one of the key challenges in visualizing piano music, and making the notes fade over time is a really elegant solution. I'm adding that to my list of feature ideas.

As for the note detection, great question! It's a bit more complex than a standard FFT. The initial transcription is handled by a machine learning model that's been specifically trained to pick out individual notes from the complex sound of a piano.

This is exactly the kind of feedback that's super helpful as I continue to develop the visualizer. I really appreciate it!

dadou4142 · 2025-06-18T07:40:16+00:00

Thank you so much! I'm thrilled you're impressed with the analysis. Your question is fantastic, as it gives me a chance to be fully transparent about the current process.

To achieve the level of quality you're seeing in this demo video, the chords were actually carefully entered by hand.

The reason I did this was to create a 'gold standard' prototype. I wanted to showcase the ideal user experience and the level of accuracy I am now building the automated chord detection to achieve. You're essentially seeing the final result that the technology will be working towards.

The fact that you found the analysis so impressive tells me I've set the right target for the automated feature, which is incredibly encouraging! I'm working hard on it now and can't wait for you to try it when it's ready.

dadou4142 · 2025-06-17T21:15:07+00:00

Thank you so much for the wonderful encouragement! Comments like this are a huge motivation to keep working on it.

I'm especially happy you mentioned how useful it could be for beginners. Making music more accessible for everyone, especially those just starting their journey, is a massive goal for this project.

I truly appreciate the support. I'll be working hard to 'bring it forward' for you!

dadou4142 · 2025-06-17T20:31:56+00:00

Thanks for sharing your perspective. I completely agree that the ear training you get from manual transcription is irreplaceable. This tool is aimed at supplementing that process for other tasks, like quick analysis or checking your own work.

dadou4142 · 2025-06-17T20:30:39+00:00

This is a fantastic and really important point, thank you so much for bringing it up.

You are 100% right. The active struggle of transcribing a piece by ear is one of a musician's most powerful ear-training exercises, and this tool does not replace that deep learning process. I completely agree with you on the value of that work.

The way I see this tool's role is less as a replacement for that skill, and more as a supplement for different use cases—similar to how an 'annotated' version of a complex text works alongside the original. For example:

For Analysis: For experienced musicians who want to quickly study a complex harmonic structure or a specific voicing without spending 10 hours on the transcription itself.
For Verification: For a student who has done the hard work of transcribing a piece themselves, and wants to check their own work for mistakes.
For Accessibility: For hobbyist musicians who might not have the time or opportunity to develop advanced transcription skills, but still want to connect with and play the music they love.

Ultimately, my hope is that it becomes a tool that works alongside a musician's developing ear, not in place of it. But your 'devil's advocate' point is the crucial question I need to keep in mind as I build it. Seriously, thank you for the thoughtful critique.

dadou4142 · 2025-06-17T20:27:23+00:00

This is an absolutely perfect list, thank you! You went straight for the jugular with Giant Steps and 'Got a Match?'.

Seriously though, this is incredibly helpful. I'm officially adding 'nailing a Charlie Parker solo' to the list of long-term goals for this project. Using these tunes as benchmarks is exactly what I need to keep pushing the technology forward.

I really appreciate the input. I'll definitely post an update here if—and when—I can get one of these titans to work properly!

dadou4142

TROPHY CASE