poly
io-ts
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poly | io-ts | |
---|---|---|
24 | 80 | |
648 | 6,593 | |
2.3% | - | |
8.2 | 4.9 | |
about 1 month ago | 5 months ago | |
Go | TypeScript | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
poly
- Looking for an Open Source project to participate in for Google Summer of Code
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GitHub Accelerator: our first cohort and what's next
- https://github.com/TimothyStiles/poly: Poly is a fast, well tested Go package for engineering organisms.
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These 20 startups are in 1st ever batch of GitHub OS Accelerator
Poly: Fast Go package for engineering organisms
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Ask HN: Burnt out from big tech. What's next?
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
- Any corner cases for Needleman-Wunsch that should be tested?
- Where can I find well-written go code to learn from?
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High-performance language recommendation
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.
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How is GO used in bioinfo?
The most popular bioinformatic package I've seen in go is poly.
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Software engineers: consider working on genomics
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.
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Ask HN: What interesting problems are you working on? ( 2022 Edition)
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)
io-ts
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TDD
Qué rico. Si tenés chance meté un proceso de code review fuerte, y para el tema de I/O probá a usar https://github.com/Effect-TS/schema ó https://github.com/gcanti/io-ts que les da una solución obvia al tema de "tipos para lo que devuelva el backend", aunque es en realidad mucho más capaz que eso.
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Domain modelling with State Machines and TypeScript by Carlton Upperdine
My fave is still io-ts (https://github.com/gcanti/io-ts/blob/master/docs/index.md) as I find it more flexible than zod at the ingress. The author is also working on the Effect ecosystem which also looks interesting.
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Why I Like Using Maps (and WeakMaps) for Handling DOM Nodes
I’ve been using io-ts for this and been very happy with it. [1] It’s similar to Swift’s Coding protocol in case you’re familiar.
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Can someone recommend a library for data parsing similar to Zod, but with better support for input transformations/preprocessing?
Yeah, there are a few new concepts and it's not the easiest to pick up right away. The best introduction is here on the main documentation page.
- libraries you are happy that you discovered them
- Is React for small projects an Overkill?
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how to strictly type this?
We use https://github.com/gcanti/io-ts/blob/master/Decoder.md which has a very similar interface. It can even be used to mutate the data using https://github.com/gcanti/io-ts/blob/master/Decoder.md#the-parse-combinator.
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Typescript advanced bits: function overloading, never and unknown types
A good way to significantly improve the reliability of your app is via improving type-safety by moving away from using any to unknown. One relevant example could be when you type your backend responses and when stringifying JSON to using unknown combined with some sort of runtime type checking. It can be done either by using built-in functionality like type guards or using an external library like io-ts, zod or yup.
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I found 10,000x faster TypeScript validator library
Usage of TypeBox is similar with io-ts and zod, but it is much powerful and faster than them. Also, TypeBox can generate JSON schema very easily. Therefore, if you're looking for a validator library for new project and not suffering from legacy codes, I think TypeBox would be much better choice than io-ts and zod. TypeBox can totally replace them.
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Validate your data with Zod
This check can be done with different libraries like: io-ts, typebox, or zod. These libraries allow you to create objects that represent your typescript definitions. Then, these objects can be used at runtime to validate the received data, in addition, you can also convert this object to a Typescript definition to have all the benefits of using typescript. These objects can be called schema validations because they are responsible for the data validation.
What are some alternatives?
Raylib-CsLo - autogen bindings to Raylib 4.x and convenience wrappers on top. Requires use of `unsafe`
zod - TypeScript-first schema validation with static type inference
pg-mem - An in memory postgres DB instance for your unit tests
class-validator - Decorator-based property validation for classes.
linaria - Zero-runtime CSS in JS library
openapi-generator - OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (v2, v3)
seq - A high-performance, Pythonic language for bioinformatics
runtypes - Runtime validation for static types
m4b-tool - m4b-tool is a command line utility to merge, split and chapterize audiobook files such as mp3, ogg, flac, m4a or m4b
fp-ts - Functional programming in TypeScript
full_spectrum_bioinformatics - An open-access bioinformatics text
joi - The most powerful data validation library for JS [Moved to: https://github.com/hapijs/joi]