316 karma · joined March 8, 2019
Rather than a way of making money, I like to think about flexibility and fast dispatching as an enabler for way more renewables to come online, and that is crucial for the human race right now.
Overall though, great tool!
I find it interesting how the autocomplete and autosuggestion perform much better in ptpython compared to VS code. Especially the autocompletion is not very reliable in VS Code, as sometimes it just stops working for method calls or function signatures.
Issues are good place for asking input and feedback, and also help in keeping feature branches focused and short lived. Definitely my favorite git workflow.
https://blog.acolyer.org/2016/05/04/btrdb-optimizing-storage...
https://pingthings.io/platform.html
It look very interesting, and I am a bit surprised to see how a tree structure can deliver such high performances in retrieving the data. Querying a long period of time mean that each top node has to be walked to the bottom, right? Isn't that fairly expensive?
The aggregations on node level are also interesting. It is something that also the company I work for (https://www.energy21.com) does for calculations, but we use a relational database and a notification-based system for performing the recalculations and keeping the aggregations up to date.
Cool stuff.
For now I will not move away from Jedi again.
I can think of: 1. Portability of the wasm binaries
Is easier interoperability between data types an advantage as well? Ctypes can be a nightmare when passing around structs and pointers (and pointers of pointers, etc.)
Keep it simple, align to the left and put some margins to center the content.
This other article explains a bit better the technology behind it. It is indeed an ORC, but they seem to have taken some interesting design choices with the working fluid to increase the cost/efficiency ratio