Enjoy and appreciate the discussion. Is this in the same neighborhood of why the reworked dict implementation in python 3.6 had insertion order as a detail, but explicitly claimed it was not a feature that should be relied upon? At least until python 3.7 cemented the behavior as a feature.
In asking that question, my guess is that you’ve never experienced being a Tesla owner. And that’s fair. I’m a Tesla owner myself, for full disclosure.
I’ve found that a Tesla is truly a computer on wheels; not unlike an iPhone is a computer in your hand. In many ways, Tesla is a software company that makes their own hardware. Unlike every other auto manufacturer, their software has full and complete control over every aspect of their hardware. Their hardware-software vertical integration is for real. They also have single software releases that deploy OTA to their whole fleet of in-service “devices.” From a software and release engineering perspective, incumbent auto manufacturers are decades behind.
> Nearly all car manufacturers have adaptive cruise control somewhere in their lineup
I’d argue the difference is that _every_ vehicle Tesla sells today is cable of being upgraded to the latest state of autonomy—just by an OTA software update and/or flipping some feature flags. While the claim of full Level 5 autonomy without lidar is controversial, it’s possible that most Teslas on the road today will be capable of being upgraded to L5 capability via a software update.
All that said, the QA issues in those photos are pretty jarring. No excuses there.
Conda has an .exe installer on Windows and a .pkg installer on macOS. Both signed by Anaconda, Inc. for the OS. There are RPM and deb bootstrap repos for Linux. Then there’s also the .sh shar file installer.
Former conda dev lead here. Definitely interested in more details regarding what part of the conda experience you found to be a hassle, if you’re willing to share.
Conda can create environments with literally nothing in them. If you’re putting the full-blown anaconda metapackage in every environment, then it sounds like you’re using conda wrong for your use case. Just tell conda to install the packages you actually need.
Hi! I was the conda dev lead for 2.5 years. We work really hard to make sure conda does the Right Thing in unpredictable, almost hostile, environments. It’s a large surface area to guard against, but in general we’ve been incredibly successful.
I hate to hear that you had a bad experience. If it’s at all possible, please provide something on our issue tracker (github.com/conda/conda) we can replicate and write regression tests against. Help us improve on what we’ve missed.
> conda seems very very tied to precisely tested version combinations, and (from what I remember - tried and had problems)
Hello. Conda core contributor here. Do you have any more details? Would love to help.
We try to keep version constraints among dependencies as loose as possible. We do actively patch dependency metadata over time, putting upper version bounds on dependencies when incompatibilities eventually arise.