When starting a new Python project, it can be tempting to open up a code editor and start writing some code. This is all well and good if you're just testing something out. But ideally, if you want your code to solve some specific need, then you'll want to structure your project accordingly.

I'm just now getting the chance to reflect on my experience at my very first PyCon. It was held at the Salt Palace Convention Center in Salt Lake City, UT, spanning the dates of April 27 - May 3, 2022. My family and I drove up from Southern California, and after the conference, took a couple of extra weeks on the road. I'm finally home and (somewhat settled). So, time to reflect...

So I intended to code some Python tonight. But, unfortunately for me, I also happened to finish listening to an exhilarating, fantastic, and somewhat infuriating podcast series while doing the dishes—the podcast at fault is The Trojan Horse Affair, from Serial Productions and The New York Times.

This time last year, I didn't really know there was such a thing as PyCon. My mind at the time was pondering the plausibility of making a little blog about what I was learning, but somewhat unsure if I could even do it.

The decline of RSS usage in the late aughts and its eventual near-demise has left many a tech-geek deflated, but not entirely hopeless. The reality is that RSS still exists out there in the wild, and some folks still depend on it for accessible, personalized, and syndicated content. So I decided to add it to my site!

Coding can feel quite daunting—specially with the wealth of information out there to consume. Sometimes, as I stare at the code on my screen, I feel particularly stuck or unmotivated.

Ever since launching this blog, I've been spending a lot of time writing and not as much time coding. I've felt a little bad about that, because I genuinely enjoy working with code when focusing on an interesting feature. On the other hand, I have also been hesitant about posting on this site anything that doesn't feel connected to actual Python code.

I decided to use MongoDB as the backend database solution for my blog, and as a result, there weren't quite as many resources to refer to when trying to find a specific solution. Ergo, how do I search weighted text fields in MongoDB with Python?

I have a feeling this post is going to be quite dense. The idea to write it came from an episode of Talk Python where Michael Kennedy interviewed Roman Right, the creator of Beanie, my Python object-document mapper (ODM) of choice for MongoDB.

A common critique of getting started with Python is how hard it can be to get up and running. It would be great if you could download a thing, code some stuff, hit a button, and voila!

So I switched frameworks from Flask to FastAPI. I'm not totally sure why. It just kind of happened. So maybe I'm kind of jumping the gun here. Talking about switching Python frameworks mid-development hardly seems like an introductory topic for a tiny little blog like this one.

Welcome to my blog. If you're reading this... Yay, I did it! Chances are I was able to overcome the challenge of having an actual day job that has nothing to do with full-stack Python web development and deploying a web app built with Python, MongoDB, HTML, and CSS. Going forward, I plan to write about things I've learned (and things I'm learning).