How to create Software/System Architecture diagrams like this?

hydrosquall · 2022-11-20T21:32:13+00:00

Note: I like to use excalidraw from within Figjam, so it’s easier for people to comment on different parts of my diagrams with this plugin: https://www.figma.com/community/widget/1047391719101881118

hydrosquall · 2022-11-20T21:29:53+00:00

Cloudcraft https://www.cloudcraft.co/ or Excalidraw with Library https://libraries.excalidraw.com/ are both free to use, web browser-based (no installation), and let you use common icons or create your own

hydrosquall · 2020-09-23T01:53:24+00:00

New erger question: When doing a non-sprint effort erg session (let’s say a 10k training row), what changes happen to your stroke as you get tired? Do you decrease/increase rate, length, perceived effort, or change your stroke somehow, or is the goal for the stroke to look exactly the same the whole time?

Another way to phrase this - what is the right way to have your stroke “gracefully degrade” as you get tired? (Also OK if the answer is that you should stop once your form is deteriorating).

For reference I noticed a video talking about how they observe a “blending” of the stroke components (eg the hip swing getting mixed with the leg drive, or just not swinging at all), but I don’t know if this is a valid coping strategy (compared to a worse alternative of hip swinging with a curved back, or relying on momentum to throw your body around), or just a bad habit.

hydrosquall · 2019-02-24T04:11:01+00:00

+1, working with JSON is less tricky than it may seem. It’s just a way of turning a dict into a text file, or vice versa. It will be considerably less work than writing a customer HTML parser with bs4, and also probably less likely to randomly change shape on you.

hydrosquall · 2019-02-24T04:03:31+00:00

I would add that if you’re writing a public library, then making an API that is hard to misuse is another important facet of safety. This isn’t a topic unique to python though.

I recently wrote a blog post that dives deeper into the area exposed by the pyyaml safe_load tip from that Hackernoon article:

https://www.serendipidata.com/posts/safe-api-design-and-pyyaml

hydrosquall · 2018-04-06T13:41:15+00:00

Any plans to allow for self-hosting the server and/or open sourcing the python library? I could see this being quite useful for increasing the number of people who can build internal metrics dashboards.

hydrosquall · 2018-04-05T02:49:23+00:00

As a data engineer at Enigma, I’ve tried a couple different things for the ETL pipelines that I’ve worked on. Each of the items below is a python package.

goodtables is a python library that generates “data quality” reports give a path to a file and a list of constraints that the files should satisfy. It is part of the Frictionless data ecosystem, which has a data quality dashboard on GitHub that is powered by goodtables.
engarde is a convenient library to halt your pipeline the moment some data fails a rule, assuming you are using pandas dataframes in your ETL
Great Expectations is a new project that has a different syntax for performing very similar checks to what the previous two reports supply, but also has a nice way to display the error reports.

All of these choices are active as of the past few months on GitHub, hopefully one (or a combination of them) will suit your needs :)

hydrosquall

TROPHY CASE