There's a point in every developer's life when they build their own finance app. It's a rite of passage. Mine has arrived. I built Cashzilla for three reasons: I wanted it to be genuinely free — not free-until-the-useful-parts. It's local-only: no accounts, no server, no cloud, no bank sync. Your data lives on your device and never touches mine. That's also why it's free — there's nothing...
At the start, I was curious to see if I could. It ended up being a rabbit hole, of course.
I can see some use cases for it. The plan is to dogfood it and validate them.
Do you mostly use it through the terminal, a UI like Open WebUI, or via integrations with other tools?
I’m trying to understand where a browser integration would actually fit - if at all
I maintain a Chrome extension that adds an AI support to any input field online.One of my favorite reviews is a 2-star review asking for “local model support”.My first reaction was: who installs a 100KB Chrome extension to talk to a 10GB model running locally?But it did make me curious. Are people actually running Ollama or LM Studio as part of their daily workflow?
Only way to stop is to start fining these companies.
https://github.com/MrCordeiro/barra-ai
Type /ai + your prompt in any textbox and the ChatGPT will do the jobI've made this project so I could learn how to create Chrome extensions.I know there are already a lot of alternatives for it, but this was a learning project and I would love some feedback on the code.( I was unable to make it work on sites that use the React Lexical editor, i.e Reddit, Facebook, etc :( )
Imagine you have an open source project that got a major sponsor. What's the best way to fairly distribute this money among the team? Should it be based on contribution levels, time spent, or something else? What models have worked well for you?
Can anyone confirm (or deny) this to me?
Source: https://docs.github.com/en/repositories/managing-your-reposi...
Codacy is now a somber reminder of what happens when your startup get the short end of the disruption stick. With generative AI on the rise, it seems they have been struggling to keep up.
Layoffs and bad Glassdoor reviews don't paint a pretty picture either. It seems like they changed investors, but are still struggling to find product-market fit again.
https://www.glassdoor.com/Reviews/Codacy-Reviews-E2097649.ht...
Yesterday's winner can be today's cautionary tale.
https://github.com/DareData/lp-foundations
Hey everyone,I work for a data consulting boutique, and we often hire fresh grads who are brilliant at algorithms and coding. However, we noticed they struggle when it comes to team-based coding environments. This isn't a small hiccup; it's a significant gap in their education and a source of real frustration for me and for them.Traditional data courses teach you how to code, how algos works,...
COVID made people realize exactly what companies thought about workers.
- They took you for a sucker for accepting too little for a thankless yet vital job. Then they realized they couldn't operate without you and suddenly you became a "hero."
- Remote work exposed the farce that is the 9-to-5 office grind. It was never about productivity, it was about the appearance of control without trust. Workers got their commuting time back. Companies now want that back for free? Suddenly you're "entitled"
- Companies hoarded cash and posted record profits, while laying off staff and cutting benefits. But ask for a raise, and you're the one who's "arrogant."
- The C-suite execs took home bonuses and stock options, while you took home anxiety and a depleted 401(k). But sure, you're the one who needs an "attitude adjustment."
- The pandemic revealed that many jobs can be done from anywhere, opening up global talent pools. If companies can hire globally, why can't workers demand globally competitive wages and living standards?
So, let's call it what it is: not arrogance, just indignation.
A democracy should have institutions that would ensure it's survival even if the biggest idiots take over - because one day they will.
I mean, so many people want to write production-level code and yet never took the time to actually read the production-level code right in their faces!
Even the standard library is worth seeing. Next time you import pathlib.Path, right click it, select "See Definition" and go find out how the sausage is made.
Obviously you are not expected to understand _everything_. But you will be surprised you will understand a bit. And then a bit more. And you will start getting comfortable dealing with production-level code. Soon you'll start writing it yourself.
This little habit skyrocketed my Python game
Hey there!As a backend dev who's been nosing around frontend land for my side projects, I'm curious to know how you approach your CSS- Are paid templates your thing, or do you stick with the free stuff? - Bootstrap themes, or do you Tailwind it from scratch? - Do you reuse your styles or create a fresh one every time?What works for you? What doesn't?PS: Any must-have resources are also greatly...
I feel I'm ready to leave the Colab environment, and I wanted to start developing PyTorch projects on my local machine. The problem: I have a Windows machine with AMD Radeon GPU (cries in wsl)What is the preferred way to get started? I've tried using WSL, ROCm, and PyTorch-DirectML, but I'm always running into problems when I run `to(device)`.
I was struggling to capture the python nodes and that would bypass it completely. It could even work with other python libraries, such as Click.