I was recently in the market for a new personal-use laptop and wanted to try out a Framework Laptop. I was intrigued by the idea of being able to replace any part that failed or even upgrade parts as I went. I also was frustrated with the direction that Windows 10 and Windows 11 was going.

They seemed more interested in advertising, tracking, sending notifications to increase my engagement of their apps, then just building an operating system that got out of my way and let me do my thing.

Since Intuit announced that Mint was going away, I’ve spent several months investigating how to import my Mint data into Firefly-iii, an open source, self-hosted budgeting software. It seemed like a perfect fit. I would fully own the data and get to build whatever tooling I want on top.

However, before we can get there, we need to have cleaned and accurate data from Mint. As it turns out, Mint’s data actually had some errors in it that required me to go back years and fix them. In this post, I walk through the programmatic approach I took to identifying mistakes and fixing them.

Birthing code is not always easy.

Enough puns. Let’s talk about Java exceptions. No matter how hard you try, your code will likely encounter an error and throw an exception (if your language supports exceptions.) It could be anything from unexpected user input to an underlying service outage. An exception will be thrown and it’s important to do something useful with it. That doesn’t mean putting try-catch blocks everywhere or trying to recover everything, in-fact I’ll argue the opposite in a few situations.

This post introduces a few common issues I’ve seen when working with Java code-bases and developers that lead to poor debuggability or other operational pains.

In late 2023, Intuit announced that Mint was going to be shutting down and migrating everybody to Credit Karma. I could try out Credit Karma, but maybe it’s time to explore alternatives. Since that announcement came out, I launched a massive time sink to try and find a new option I liked.

I’ve been slowly reducing the amount of data shared with Google. I’ve been using Google Location History since 2013. I found it really useful just because I could figure out what restaurant I went to when I was traveling or any number of things.

I found OwnTracks which was an open-source location history storage solution. It’s not nearly as polished as Google Maps where it natively integrates your location history, but step one is owning my data, step 2 can be better UIs.