This is absolutely a painpoint for me and other individuals that prefer to hold as much of their assets as possible in the market. The amount held over in checking for day to day transactions feels like little more than "cash drag" once you have enough saved that you can weather a market downturn. Right now I do expense tracking and budgeting largely so I can figure out how much balance I should keep in my checking account, then transfer the rest to investing. Combining the accounts like you propose would save me substantial time and missed market returns.
A problem you may run into in targeting bogleheads is that they like to see that you're well established before committing their life savings. Putting a substantial amount of money in a non-FDIC insured financial institution without a track record could be a non-starter. Advertising on your landing page that you base your services on top of Fidelity might lower that perception of risk.
I first ran into it when our database was holding negative values that we wanted to show as positive on the front end. To flip the sign we would multiply the stored value by -1. Since 0 was a valid value in our DB, the displayed value after multiplication was -0, which looked like a glitch in the UI.
I'm not a data scientist, but I've been interested in the idea of a "code notebook" ever since Jupyter hit it big. I write mostly in JS/TS for application logic, so this looks like it could be really useful.
Related, does anyone have any recommendations of a (Postgres) SQL "notebook"? I don't really need any visualizations, more just a markdown integrated doc that allows me to lay out the different queries I use to answer a question.
For viz/DS/ML/AI with JS/TS is either observablehq or and IDE with custom extensions; this project looks relevant if you are already into observablehq.
Emacs and Org-mode has great integration with multiple SQL implementations including Postgres (via org-babel). Org-mode tables are pretty neat, and you can have query result directly populated into tables. Read this blogpost if you are interested:
Weirdly my Django SQL Dashboard project may fit the bill a bit here: you can build up a "dashboard" (which is a tiny bit notebook-like if you squint at it the right way) with multiple SQL queries on it, and save that either as a bookmark or as a "saved dashboard" with a URL.
In my own work I've been using it for the kind of things that I would normally use a Jupyter notebook for - gathering together research on problems I'm trying to solve.
Interesting take, I'm not deep in the python ecosystem, but this looks like it's lightweight enough to function as a refreshable notebook. Will give this a try, thanks!
I like the ipython-sql magic in Jupyter: https://github.com/catherinedevlin/ipython-sql Depending on what you're doing you might be able to get away entirely with just using it and some basic queries, i.e. no python glue code in the notebook at all. But worst case you might need a cell to open up the DB connection and make the magic aware of it, then you can execute clean and simple SQL queries in cells using the magic.
It's based on Spark rather than Postgresql directly, but I'm part of an effort to build a workflow system disguised as a notebook callled Vizier [1]. SQL is a first-class primitive in Vizier, and the notebook plays nice with postgres (you can load from and unload to postgres using Spark's native data loader).
Anyone think that users will eventually become desensitized to the "malicious software" popup? If the process is this complex and buggy I imagine a lot of developers simply won't bother with notarization. Eventually if enough legitimate apps don't bother the popup will become common, and users may be annoyed more by Apple than any particular app. Like how the "run as admin" prompt just became an extra automatic click to many users in Windows.
It's not like the big development shops that do take the time to get the notarization process working get a special green checkmark by their app. After the app has been launched the first time, it's back to an even playing field with the apps that didn't notarize.
Will give this a try! With all the UML discussions lately it's made me nostalgic for having an ER diagram of my schema. This even looks simple / dependency free enough to run in a CI tool to keep such a diagram up to date with the codebase.
We use planter in our build process to maintain an up-to-date visualization of the schema. Given that foreign key references are maintained in the schema (using REFERENCES), planter draws all relationships properly.
The Plant UML CLI itself has some limitations if the ER diagram is really large.
> Traditional enterprises were the dominant software employers in the 1990’s, meaning that tech trends likely reflected their interests. That would be a good explanation for UML’s initial rise. Over the past two decades, though, software culture shifted progressively towards large tech-first companies and startups. Neither, historically, was the target audience of CASE vendors. Over time traditional enterprise starts borrowing from tech and startups vs the other way around, leading to the progressive decline of CASE in its extant niches.
This I think was the real thrust of the argument. While UML's death may be exaggerated in many corners of the corporate world, so too is its life in representing our industry as a whole.
I think there's a more positive interpretation to be found as well.
Think of any type of task that you can get "in the zone", or a "flow state" with. Having an audience that reacts positively to your work can create a positive feedback loop that causes you to do better on the task. You tend to do better at things you enjoy doing.
The opposite can also be true. If you do something you're unfamiliar with, chances are your audience won't react positively to watching you do it. This can create a negative feedback loop that causes you to do worse. (I think this is changing though, with the advent of "Let's Play"s, streaming culture, and the voyeuristic enjoyment of watching someone improve at something over time).
Or for the full course: https://ocw.mit.edu/courses/15-s12-blockchain-and-money-fall...