Reasons game developers don’t like steam keys from sites like G2A are:

• Exploiting regional price differences.
• Splitting keys out of bundles.
• Scamming game developers for free keys (claiming they want to promote the game with a giveaway).
• Keys bought with stolen cards (that get chargebacked causing direct loss).

The last reason could apply to reselling steam accounts as well.

You can do the notes with shift.

I think it would be very difficult to argue that that is reasonable but that would be up to the courts to decide.

Rossmann has only reuploaded the slicer fork, not any firmware (the article title is inaccurate). But yes, the slicer’s AGPL license does not apply to the firmware.

You aren’t understanding the GPL correctly.

• The GPL applies to code built on top of GPL code, this is the viral nature of the GPL.
• Anyone with a GPL license for the code can license anyone else, it does not have to come from the original creator. So Rossmann has a license granted by the creator of the fork. Also the source that Bambu Lab provide on GitHub provides a license as well.

lime

That page doesn’t say that at all. You can paywall the software and the source together for any price (but note that anyone who buys the software can now give out the source freely). Or you can charge for the source freely but only “for a price no more than your reasonable cost of physically performing this conveying of source”.

But most places have publicly owned garbage collection, no?

Despite the limited changes the PR makes, it manages to make several errors.

According to benchmarks in issue #31130:

• With broadcast: np.column_stack → 36.47 µs, np.vstack().T → 27.67 µs (24% faster)
• Without broadcast: np.column_stack → 20.63 µs, np.vstack().T → 13.18 µs (36% faster)

Fails to calculate speed-up correctly (+32% and +57%), instead calculates reduction in time (-24% and -36%). Also those figures are just regurgitated from the original issue.

The improvement comes from np.vstack().T doing contiguous memory copies and returning a view, whereas np.column_stack has to interleave elements in memory.

Regurgitated information from the original issue.

Changes

• Modified 3 files
• Replaced 3 occurrences of np.column_stack with np.vstack().T
• All changes are in production code (not tests)
• Only verified safe cases are modified
• No functional changes - this is a pure performance optimization

The PR changes 4 files.

Was 204 (#754 medium) possible?