I guess if the serious thing you’re doing is a CRUD app?
Tell that to YouTube and Spotify. Or astronauts on the ISS. Or anyone doing science really…
Machine learning and CV? Geospatial? Math in general?
dallen
joined 2 years ago
God forbid they had Christmas holidays 🙄
It’s probably just that I got used to it with XFCE at some point. My main two concerns:
- I love having the path in the navbar (and not have to Ctrl-L)
- I don’t like having devices tucked behind “Other Locations” rather than in the sidebar
Otherwise, I find Nautilus much more aesthetically pleasing.
I’m a gnome guy but always swap to Thunar on a fresh install.
Server is meant for all users of a single server.
So, you could buy 1-3 individual licenses or the server license for 4+ users.
Really looking forward to running type checks with pre-commit. Mypy is just too slow with most code bases.
Basic HTML hosted at cv.dallen.co
I have a pipeline that creates a PDF version with weasyprint: https://github.com/damienallen/cv
The market share and generally more tech savvy user base are probably discouraging.
Well, time to edit .bash_aliases…
Can’t speak to your exact machine but nowadays the license tends to be tied to the hardware.
If you are capable of manual partitioning then you should be able to reinstall Windows quickly if needed.
Repo: https://github.com/damienallen/urban-heat
cross-posted from: https://programming.dev/post/14939898
I wanted to share a small project I've been working on. The goal was to make the data from NASA's Landsat Thermal Infrared Sensor more accessible to the general public.
I worked with the raw temperature band data to general annual maximum surface temperature raster images for large urban areas covered by the Eurostat GISCO Urban Audit. In the browser, these images are transformed into easier to interpret isotherm contours with some adjustable settings.
I don't have a specific target audience in mind. The map could help identify areas of refuge for the warmer months, or overheated neighborhoods to avoid as we march towards a toasty future.
Feedback is welcome :)
repo: https://github.com/damienallen/urban-heat
cross-posted from: https://programming.dev/post/14939898
I wanted to share a small project I've been working on. The goal was to make the data from NASA's Landsat Thermal Infrared Sensor more accessible to the general public.
I worked with the raw temperature band data to general annual maximum surface temperature raster images for large urban areas covered by the Eurostat GISCO Urban Audit. In the browser, these images are transformed into easier to interpret isotherm contours with some adjustable settings.
I don't have a specific target audience in mind. The map could help identify areas of refuge for the warmer months, or overheated neighborhoods to avoid as we march towards a toasty future.
Feedback is welcome :)
I wanted to share a small project I've been working on. The goal was to make the data from NASA's Landsat Thermal Infrared Sensor more accessible to the general public.
I worked with the raw temperature band data to general annual maximum surface temperature raster images for large urban areas covered by the Eurostat GISCO Urban Audit. In the browser, these images are transformed into easier to interpret isotherm contours with some adjustable settings.
I don't have a specific target audience in mind. The map could help identify areas of refuge for the warmer months, or overheated neighborhoods to avoid as we march towards a toasty future.
Feedback is welcome :)
EDIT: For UK visitors, sorry to leave you with an empty map...
I've taken a look at older urban extent data and found the geometry I need to process the UK (from before leaving Eurostat). However, there are still some UI limitations to overcome since it seems that cities are split into many boroughs that could only be viewed one at a time. The reason I went with the Eurostat dataset to begin with was a nice delineation of what a city was (for the purposes of this project).
Don't have a timeline, but I do want to add the UK and automatic loading of cities as you pan!
view more: next ›
I’m running Immich on an old ThinkCentre with the default feature set. Currently looking at:
There is a bit more overhead for the control plane and cloud-native PG operator/backup pods but my instance fits comfortably inside a ~4GB allocation.