poly
Benthos
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poly | Benthos | |
---|---|---|
24 | 76 | |
648 | 7,559 | |
2.5% | 4.5% | |
8.2 | 9.6 | |
about 1 month ago | 7 days ago | |
Go | Go | |
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)
Benthos
- Ask HN: Who is hiring? (December 2023)
- Structured Logging with Slog
- Fancy stream processing made operationally mundane
- Benthos: Fancy stream processing made operationally mundane
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Any golang library to batch process a queue ?
I’ve used https://www.benthos.dev/ and it’s really easy and well implemented. The author is also very responsive
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Show HN: Arroyo – Write SQL on streaming data
Looks cool. What is the difference between this tools and benthos (https://www.benthos.dev/)?
- Benthos: Open-source stream processing tool
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book about golang and kafka
You might want to gradually replace that one with https://github.com/twmb/franz-go because Shopify is looking to find a new owner for Sarama and, until or if they do, it seems to be falling behind with maintenance: https://github.com/Shopify/sarama/issues/2461 For example, they still haven’t addressed this breaking change https://github.com/Shopify/sarama/issues/2358. franz-go has worked well so far in Benthos https://github.com/benthosdev/benthos/tree/main/internal/impl/kafka and it will likely end up as the only implementation once the Sarama-based one will be deprecated
- Show HN: Open-source Auth0 alternative Ory Kratos v0.13 released – nearing v1.0
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Go in depth youtube channels?
I upload a mix of code reviews and live streams on https://www.youtube.com/@Jeffail, mostly building https://www.benthos.dev out in the open so the content ranges from beginner friendly stuff to more advanced things like stream processing, parser combinators, etc.
What are some alternatives?
Raylib-CsLo - autogen bindings to Raylib 4.x and convenience wrappers on top. Requires use of `unsafe`
Confluent Kafka Golang Client - Confluent's Apache Kafka Golang client
pg-mem - An in memory postgres DB instance for your unit tests
appsmith - Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.
linaria - Zero-runtime CSS in JS library
watermill - Building event-driven applications the easy way in Go.
seq - A high-performance, Pythonic language for bioinformatics
sarama - Sarama is a Go library for Apache Kafka. [Moved to: https://github.com/IBM/sarama]
m4b-tool - m4b-tool is a command line utility to merge, split and chapterize audiobook files such as mp3, ogg, flac, m4a or m4b
salsa - A generic framework for on-demand, incrementalized computation. Inspired by adapton, glimmer, and rustc's query system.
full_spectrum_bioinformatics - An open-access bioinformatics text
azure-event-hubs-go - Golang client library for Azure Event Hubs https://azure.microsoft.com/services/event-hubs