Recently, #Audacity 3.7.5 was released. While we have now integrated applicable fixes into #Tenacity, one notable thing absent is Windows ARM64 support. This is simply because our #CI config is different than Audacity's, so our Windows ARM64 builds will come later.

However, if you're on Linux on ARM64/aarch64 and use #Flatpak, then you should be able to install Tenacity from #Flathub as Flathub builds for both #x86_64 and aarch64 by default. Try it out and let us know what you think! 馃槃

Recently, #Audacity 3.7.5 was released. While we have now integrated applicable fixes into #Tenacity, one notable thing absent is Windows ARM64 support. This is simply because our #CI config is different than Audacity's, so our Windows ARM64 builds will come later.

However, if you're on Linux on ARM64/aarch64 and use #Flatpak, then you should be able to install Tenacity from #Flathub as Flathub builds for both #x86_64 and aarch64 by default. Try it out and let us know what you think! 馃槃

We are investing in integrating with Namespace (namespace.so) environments to be able to build experiences that are triggered remotely and on the fly. From triggering an agentic QA session, to signing an app on install to take the signing hassle off your plate.

Running those environments have traditionally been costly, but Namespace provided an API that鈥檚 a joy to use becoming a foundation for new dev experiences for app developers.

#ci #devx #swift #iosdev

I am currently looking for a #job . I am an experienced (senior) software developer/engineer with 7y of experience. If someone is looking for a capable software engineer or knows someone looking for engineers, please let me know.

I do #python #scheme #django #docker and aim for reproducible software. I learned some #devops and #ansible and can manage servers. Used to do #fullstack dev work, before everything needed to be an SPA.

I am looking for #remote work or work in #berlin or #potsdam .

I also got experience with the following (5 = a lot, 1 = a little) :

#machinelearning #ml (3) (I have implemented some ML models myself in the past, for learning purposes.)
#guix (3) (Using it for reproducible setups of projects.)
#functionalprogramming #fp (5) (Doing it in my own projects.)
#objectorientedprogramming #oop (4) (last job and past 馃槣 in my own projects.)
#CI / #CD (3) (Last job)
#make (4) (using it for my own project setups and convenience)
#testing (4) (last job, own projects)