poly VS todomvc

- https://github.com/TimothyStiles/poly: Poly is a fast, well tested Go package for engineering organisms.

Poly: Fast Go package for engineering organisms

You might want to look at computational biology. Jim Allison won the Nobel Prize back in 2018 for his work on immunotherapy for cancer and there's a lot of basic research work to be done to perfect this approach. Epigenetic clocks are really interesting too (see Steve Horvath's work). Also, there's synthetic biology, where you could, for example, explore this package that's written in Go: https://github.com/TimothyStiles/poly

Check out poly. It’s written in go and I’m using it for one of my projects too. The goal is that we should have high performance libraries that we can use knowing what people are working on the forks will give the community a leg up.

The most popular bioinformatic package I've seen in go is poly.

I write synthetic biology software for a living and maintain this open source, Go package for engineering DNA that has high test coverage and a nice little dev community around it.

https://github.com/TimothyStiles/poly

A large part of my project's community are devs that want to get into the field but can't tolerate the ridiculously low pay, laughably bad management, disrespect, and what amounts to 40+ years of technical debt that's endemic to biotech software.

I've had companies here in the Bay Area offer me 100K a year with a straight face. I've had companies during interview tell me they're looking for someone to help, "set up GitHub". I've seen job listings for low paid web dev positions require applicants to have PhDs.

The reality is that except for a growing handful of places management straight up won't know the difference between IT and software engineers. It's what I call the naive buyers problem.

The demand for software engineers in biotech is generated by naive buyers that don't know what they need, why they need it, or how to get it.

Benchling and Recursion Pharmaceuticals have reputations in the industry of paying, "standard software salaries". So do the research divisions at places like deepmind/microsoft/google but in my experience there's even new multi-billion dollar institutes where senior management has never even heard the term devops.

Most places advertise for "data scientist", positions or some analog, instead of software engineers. This is mostly because upper management has never met an actual practicing software engineer in a professional setting. Many come from academia where the culture and work requirements heavily disincentivize standard software engineering practices.

It's also not uncommon for a biotech company to either have a very under qualified CTO whose main programming experience is what they learned doing ML research like stuff during their PhD or not even have one at all which has huge downstream consequences.

This week a software engineer trying to make the switch to biotech actually DM'd me to ask why they were seeing a ton of data science / ML job positions but no software engineering / devops positions.

They were worried that these companies were trying to save on costs by forcing their data scientists to create infrastructure but it's actually worse than that. Most of these companies aren't even aware that there's supposed to be infrastructure.

Despite all of this the future is looking better and I'm starting to find new companies and positions that are well... reasonable. I learned about this thread from a friend at a party last night that works at one of these companies. There's a small, strong new wave of companies and developers out there pushing biotech software forward. Hopefully some (including myself) make it big while pushing the idea that better tech equals better biotech.

It is more like the X Y Z W. However, the X Y Z W bits I am working on as well (https://github.com/TimothyStiles/poly , https://github.com/TimothyStiles/allbase , trilo.bio, freegenes.org). Going for fully automated "make bacterium X produce molecule Y", but still a while away (but surprisingly not THAT far off)

The odd thing is unison started purely as a language. Now there's a platform.

I often find the best way to understand complex things is to dig all the way back to when they were being thought up. In this case there's a blog post from 2017 that I still find useful when thinking about Unison:

https://pchiusano.github.io/2017-01-20/why-not-haskell.html

Key quote:

Composability is destroyed at program boundaries, therefore extend these boundaries outward, until all the computational resources of civilization are joined in a single planetary-scale computer

(With the open sourcing of the language I doubt it will be one computer anymore, but it's an interesting window into the original idea)

Personally I find there's a lot to this. It's interesting that we're really, really good at composing code within a program. I can map, filter, loop and do whatever I want to nested data structures with complete type safety to my heart's content. My editor's autocompleting, docs are showing up on hover, it's easy to test, all's well.

But as soon as I want cron involved, and maybe a little state-- this is all wrecked. Also deployment gets more annoying as they talk about a lot.

So I think Unison always had to have a platform to support bringing this stuff into the language, even though they built the language first.

I'd love to hear some opinions from outside Unison about how they like using this language, tooling and hosting.

I'd like to hear this too.

Also, it would be great if there was something like https://eugenkiss.github.io/7guis/ or https://todomvc.com/ for platforms that we could use to compare Unison, AWS, etc etc. Or is there already a 7GUIs for platforms that I don't know about?

git clone --depth=1 https://github.com/tastejs/todomvc.git

The problem with this question is that, if it's not engineering, what is it? A better question is motivated by studying the history of chemistry and its progenitor, alchemy. That is: is software development alchemy or chemistry?

Software development alchemy. Just like alchemy, software dev is not standardized, everyone has their own idiosyncratic naming systems, classifications and rules-of-thumb. Like alchemists, software engineers are often jealous of their proprietary knowledge. Just like alchemists, they admired, feared and loathed for having secret knowledge. And just like alchemists, you have to be exceedingly brilliant to work in such a chaotic field and get anything done.

What changed alchemy into chemistry, and what is the analog to that in software? Arguably the change started with notion of conservation of mass and energy, and the development of the periodic table (thanks to Lavoisier and Mendeleev, respectively). As for what that analog is for software, first we need a characterization of the field. With alchemy and chemistry both, it's essentially mixing stuff together, heating and cooling it, and seeing what happens. But what is it for software?

Software engineering is often mistaken for computer science. Computer science is a tiny subset of software engineering. In practice, almost all of computer science is encapsulated in a few, tiny standard libraries - the places where bubble-sorts and hash maps live. (This mistake is consistent, and leads to "leet code" style interview questions which are irrelevant to actual work). I'd characterize software engineering as the set of solutions to a boundary value problem[0] described as "a set of interacting screens with behaviors pleasing to humans". The current solutions to this problem have been idiosyncratically shaped by resource constraints that rapidly relaxed over time[1], and characterized by elements discovered at random by necessity: e.g. kernels, processes, files, procedures, terminals, etc. In this analysis "language" functions as a kind of "coordinate system" as in physics[2][3], within which each of these elements are described, and within which elements are combined to make new elements, which eventually yield a solution to the boundary problem (which is termed "application").

I don't particularly know what the standardization of software engineering will look like, but I'm certain that this analysis, or something similar to it, is the first steps in the right direction. Personally, I look forward to the day we can shed the considerable weight of our alchemical origins.

0 - https://en.wikipedia.org/wiki/Boundary_value_problem

1 - https://en.wikipedia.org/wiki/Moore's_law

2 - https://en.wikipedia.org/wiki/Coordinate_system

3 - https://www.rosettacode.org/wiki/Rosetta_Code - the same problem is solved in many languages. For applications: https://todomvc.com/

Compare the source code at https://todomvc.com/ to see what various frameworks bring to the table. VanillaJS is generally 2-3x as much code since you have to implement the MVC logic yourself.

There is an example (not mine) of AnjularJS controllers, how much JS I have to write:https://github.com/tastejs/todomvc/tree/gh-pages/architecture-examples/angularjs/js

Learn by doing. You could recreate the TodoMVC app.

How easy or hard to build Shopify without zero coding experience? Shopify is a big thing =) So that would be hard to build with zero coding experience. Start with a todo list, micro blog, or something small in scope that interests you. https://todomvc.com/ is interesting since it is the identical app, written in many different ways, different languages and frameworks - and you can use them as reference to see how others have built something.