dfinninger

That’s interesting. I’ve been told every time (so far) to keep a “neutral face”. I smiled once and the guy let out a heavy sigh and made me take the photo again (Redwood City, CA DMV).

Yes it is, I just converted my work scripts over this afternoon.

    #!/usr/bin/env uv run

The heat keeps going at night too. Waking up at 6:30am for a run and it’s 80F outside at 95% humidity… brutal.

Django+Postgres.

So far I haven’t needed anything fancy like Htmx, but interested in looking into it in the future.

I’ve tried playing with things like Elixir or Go, but I know Python and am instantly productive in it. If I want to do something to play with a new stack, I will. But I want something done, then Python is the fastest way for me to get something useable.

My favorite:

alias gfp=“git commit --amend --no-edit && git push --force-with-lease”

For those “whoops, for got to add $x file” moments or typos

Which is interesting because, anecdotally, I’ve had the exact opposite experience. I’ve lived in Dallas and Austin for a collective 27 years. And the number of outages I’ve had bewilders friends and family that are out of state. Since I’ve moved out of Texas a few years ago I haven’t had a single power outage.

In my family while growing up we kept flashlights and candles handy, and us kids were (very lightly) drilled on where to find them when the power went out. And again, this was in the middle of the metro, not out in any rural parts.

Django was actually fine. They had the same codebase running on Python 2 and three, so you could update whenever. Since Django includes so many batteries, I didn’t have any trouble porting that over.

However, early versions of Python 3 were slower than Python 2, and also some breaking changes were getting rolled back (e.g. PEP-414, which was targeting Python 3.3), which contributed to a lot of library authors dragging their feet in upgrading their support.

So, yes, it was libraries causing the most headaches, but there was a sense at the time of wondering when the upgrade would become “real”. Depreciating py2 took 11 years after the release of 3.0.

In a one-pedal-driving scenario the neutral position is when the gas pedal is slightly depressed.

By default, with no feet on pedals, the EV will decelerate. An ICE car will coast when nothing is depressed.

I highly recommend YNAB. It pulled my financial life together a decade ago. Synced apps on the phone and web. It also introduced me to envelope budgeting, which I found to be super useful.

If you want to do investment tracking, I don’t think it’s the best for that.

Or just shaking your iPhone for undo.

I think the point is that those three senior engineers could figure out how to do some SAML wrapper or remote execution on top of Open-Source Terraform instead of paying for the turn-key “Enterprise” features.

Something that I picked up after watching one of J. Kenji López-Alt’s videos was chaining ingredients. Specifically the difficult ones and not necessarily just reusing the rest of the green onion in the bottom of the fridge.

So, now I give myself a budget of one or two “difficult/time consuming” ingredients. This can be Demi-glacé or some other homemade reduction, soy-marinated eggs, slow-cooked brisket, etc. And I make more of it than I need to.

Then I make and eat the meal I was planning on, but I now have a leftover ingredient. Then for my next meal, I can re-use that ingredient and choose another difficult one. It helps with inspiration and effort level.

An example would be: make homemade tomato sauce then make Spaghetti. Next make dough and reuse the sauce into some homemade pizza. Then use the rest of the dough for garlic bread next to a salad (and maybe there’s a little red sauce left for dipping). Etc.

Of course, I’m not doing this for individual meals, I’m batching it up into 3-4 servings each.