bandcamp-downloader VS orange

Two projects I greatly appreciate, allowing me to easily archive my bandcamp and GOG purchases (after the initial setup anyways):

https://github.com/easlice/bandcamp-downloader

https://github.com/Kalanyr/gogrepoc

And I recently learned about archivebox, which I think is going to be a fast favorite and finally let me clear out my mess of tabs/bookmarks: https://github.com/ArchiveBox/ArchiveBox

Reminder to archive all purchases

https://github.com/easlice/bandcamp-downloader

I have a windows oriented “get past setup pain points” tutorial here: https://github.com/easlice/bandcamp-downloader/issues/21

For generating a cookie file, I suggest just using https://github.com/hrdl-github/cookies-txt

Make sure to archive your bandcamp collection, which you can do with the following script: https://github.com/easlice/bandcamp-downloader

I have a straightforward guide on how to get up and running on windows here: https://github.com/easlice/bandcamp-downloader/issues/21

You should always archive your collection anyways. One negative thing about bandcamp is that artists/labels/bandcamp can remove anything at anytime for any reason, so things you paid for can straight up disappear. This was very disappointing to discover. Note that sometimes things are set as hidden, rather than outright removed. This info may be outdated, as the relevant support page seems to gave changed from the last time I looked at it.

Because of their no DRM policy and full on downloads, not just streaming, Bandcamp has basically become the only place I’ll buy music outside of CDs.

I’m happy enough to hand artists money if it’s easy and I can archive a lossless copy, but if they start fucking around with things, I’ll go right back to doing what I was before. That said, if they fix the outright removal of paid things problem, and start treating “artist” as first class instead of “label” in searches and links, I’ll be singing their praises.

Bandcamp is what I use.

One thing to note, is that the artist/label retain full control of what music is present, and as such can be removed at any time, even ones you paid for. See: https://get.bandcamp.help/hc/en-us/articles/4406122372119-Wh...

I use https://github.com/easlice/bandcamp-downloader to immediately archive flac files to my NAS after a purchase, then convert to those to a lossy for space saving format for mobile playback/family sharing as desired with a playlist. This way I have my archive, and the artists I like get their support.

2) Download this code from the repo

I know I've tooted its horn before, but Orange3 is a pretty neat Python-based GUI platform that makes this and a metric buttload of other statistical/ML techniques available to non-programmer types.

Just watch out for null character `x00` in the corpus. That always seems to kill it stone dead.

https://orangedatamining.com/

https://orange3.readthedocs.io/projects/orange-visual-progra...

For all you folks who aren't ace programmer types, the Orange3[1] platform gives you a very miniaturized[2] ability to turn out these sorts of visualizations very rapidly. It's not the most stable thing in the world, but the node-based ML workflow designer is worth the price of admission all by itself.

[1] https://orangedatamining.com/

[2] The Wikipedia extension in Text limits each search result to 25 articles, so sucking all of Wikipedia is . . well, Orange text analytics crashes when I look at it sideways with a null character, so let's not think about what would happen.

First is identifying the "similar" things in a corpus. Best way I know to do that, for non-programmer audiences, is the Orange Data Mining tool, which gives you a node-based text mining interface to perform statistical analysis on text. Hierarchical Clustering shows - very rapidly - how similar your "modules" are, which ones are most similar. There's many other techniques (semantic viewer, similarity hash, etc) as well - the right one will depend on how your content is laying about.

Both tools are ripoffs of a data mining framework named Orange 3

You should also check out Orange Data Mining, it allows to create a lot of charts, filter data from a chart to another, build ML models, predictions and a lot more. And you can do it with zero code.

You can start with a free GUI based tool Orange. It is a component based data science workflow tool, which you can use to handle 60-75% of the traditional data science tasks from classification, regression, to basic neural networks.