2,176 karma · joined March 18, 2013
Anyway, I think you’re totally right, in your general message. Python will never be the fastest language in all contexts. Still, there is a lot of room for optimization, and given it’s a popular language, it’s worth the effort.
What would be a "better" vibe than requesting an escalation? if you buy something and you don't get something you've bought? Just say "oh well, it is what it is"?
I am curious though, do you have any suggestions for alternative DNS that is better?
> How Quad9 protects your privacy?
> When your devices use Quad9 normally, no data containing your IP address is ever logged in any Quad9 system.
Of course they have some kinds of logs. Aggregating resolved domains without logging client IPs is not what the implication of "Quad9 is reselling the traffic logs" seems to be.
But, to help those wondering about RnR vs Django for dealing with GIS data, the answer is the python ecosystem is just larger for dealing with GIS data. There are more libraries like fiona, shapely, gdal examples, etc. Django ORM supports all of the PostGIS functions, geos and ogr object helpers.
Rails does not have an alternative for PolygonField, Raster support, or geometry field queries like filter(geom__intersects=area)
Does anyone have a good backup for CF? I certainly don't want to rely on my ISP, has they've done MITM before.
If the "industry" default has new JS/Node powered ecosystem, perhaps some people, including myself, would agree that PHP frameworks are still ahead of the overly modular JS frameworks, there isn't anything like Laravel or Django for the JS world.
But, for simple cases, templates are still very common, including static site generators, but even PHP.
> But after a few weeks, it compiled and the results surprised us. The code was 10x faster than our carefully tuned Kotlin implementation – despite no attempt to make it faster. To put this in perspective, we had spent years incrementally improving the Kotlin version from 2,000 to 3,000 transactions per second (TPS). The Rust version, written by Java developers who were new to the language, clocked 30,000 TPS.
I feel like there is more to this, like some kind of a bottleneck, memory footprint, some IO overhead?
> Our conclusion was to rewrite our data plane entirely in Rust.
The point is well taken, figuring it out is not worth it, if you can just "rewrote" or have green field projects.
> These extension points are part of Postgres’ public API, allowing you to modify behavior without changing core code
Also, interesting. So PostgreSQL evolved to the point that it has a stable API for extensibility? This great for the project, maintain a modular design, and some stable APIs and, you can let people mix and match and reduce duplication of effort.
Yeah, I think I’d rather click and type than talk, all day.
On the other hand, the good part of the job is solving complex technical problem with a team.
No greater Scott’s man can tell you that the reality is surprisingly complex, and sometimes you have resources to organize and fight them, and sometimes you use those resources wiser than the other group of people, and can share the lessons. Sometimes, you just have no idea if your lesson is even useful. Let’s judge the story on its merits and learn what we can from it.