These two are my favorite balance of fundamentals and getting to purposeful application as quickly as possible (the first link is definitely not enough, but combined with the second she should be comfortable with the syntax and able to get basic things working):
https://www.kaggle.com/learn/intro-to-programming
https://www.kaggle.com/learn/python

This one takes its time with fundamentals and includes some projects to put them in context of building something. It’s presented on Google Colab and Jupyter notebooks: https://allendowney.github.io/ThinkPython/

Working with GIS data means cleaning data. This one covers that and a lot of common analysis tools and techniques. But it assumes a bit of programming knowledge (Good to follow up after one of the options above): https://wesmckinney.com/book/

Good news from September:

Introducing the Ghostty “Quick Terminal” feature: a terminal that drops-down based on a global keybind (also sometimes known as a Doom or Quake-style terminal). This was one of Ghostty’s most requested features.

https://x.com/mitchellh/status/1840449807095394391

I think that Hashimoto is using this project to iron out details that are left unaddressed due to convenience for other projects and the very low impact of any single issue Hashimoto has addressed. But much like with Apple projects, Hashimoto intends for the the end product to have greater value than the sum of the parts. Unlike Apple, it will be perfomant cross platform.

I think the only way to evaluate a project like this is to ignore the feature comparison charts and use it to see if it really is better when those details are addressed. I have a feeling that many people will agree and most will shrug their shoulders and not give it a second look if they even gave it a first one.

I’ll be trying Ghostty out soon. I hope it’s great. But I’m not expecting to be blown away.

He seems to target GTK based on his statement:

"On macOS, the main GUI experience is written in Swift using AppKit and SwiftUI. The tabs are native tabs, the splits are native UI components, multi-window works as you’d expect, etc. On Linux, the GUI experience is GTK using real GTK windows and other widgets.

Features such as error messages are not implemented with a specialized terminal view, we actually use real native UI components. The point is, while the terminal surface and core logic is cross-platform, the user interaction is all purpose-built for each operating system for a true native experience."

https://mitchellh.com/writing/ghostty-and-useful-zig-patterns

Lemmy still doesn’t let someone post an embedded link and picture. People don’t realize that you have to include the linkin the body of the post which is annoying and intuitive, specially because when creating a new post Lemmy will allow you to fill out both form fields for link and picture but only use one.

I’m not sure I understand the trade offs you’re choosing by deploying this way. The benefit of simplicity an speed of deployment seems clear from your write-up. But are those the most important considerations? Why or why not?

How are you liking bearblog.dev?

This is a teaser for the promised future posts. Don’t ghost us.

Yup

Everyone can save time and just read your synopsis. These are billionaires backed by huge investment funds fighting over service fees.

I get the sense that you might appreciate golang.

It seems there’s room for both

FYI the person with enough money to donate $300,000 to a programming language foundation is the founder of HashiCorp.

If each lemmy instance has only a partial dataset

You can stop saying if. It is nearly certain that any instance only has a partial dataset in the same way that a search engine only indexes a partial dataset of every web page.

If this is the case: what happens if a bad actor subscribes to all communities of all servers?

There are bots that were built to do exactly that. I wouldn’t call them bad actors unless the instance owner prohibited such actions.

Ente is a beautiful, private cloud for your memories, with apps for mobile, desktop and web.

At Ente, we use Local AI to deliver features like face recognition and magic search, while respecting the privacy of your photos.

We’ll now join a cohort of builders pushing technology forward for an AI that is light, private and accessible.

That’s more than most SWE graduates have done, which is great! But it makes it difficult to judge what you might benefit from based on what you’ve shared.

To answer the title question, the suggestions provided by others here are all good resources for studying algorithms, but no one mentioned Algorithms Illuminated which is of a similar quality. Choose one of these suggested resources that vibes with your learning style.

But don’t discount the suggestions to work on new projects that are outside of your current experience and requires more than your current knowledge base to complete. Trying things you haven’t tried before really is the only way to do things you couldn’t do previously.

Good luck!

What have you built? What larger projects have you contributed to?

Perhaps the following rewording of your last sentence would be easier for readers to follow along:

With a lack of precision, 1/3 might become 0.33333333. When evaluating the expression 1/3 + 1/3 + 1/3, using 0.33333333 as an approximate representation of 1/3 will return a result of 0.99999999, instead of the correct answer of 1.

That link didn’t work for me.

I agree. I was just using understatment for rhetorical effect.