poly
sniffnet
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poly | sniffnet | |
---|---|---|
24 | 84 | |
640 | 13,271 | |
3.1% | - | |
8.2 | 9.8 | |
8 days ago | 3 days ago | |
Go | Rust | |
MIT License | Apache License 2.0 |
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
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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
- 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)
A couple of years ago I realized that there weren't any good open source software packages for designing DNA so I wrote one.
https://github.com/TimothyStiles/poly
Goal is to have a suite of packages and databases that can be used to design entirely novel proteins, metabolic pathways, and DNA constructs at scale because right now that software ecosystem just doesn't exist.
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)
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Ask HN: What's the best source code you've read?
Not that I understand any of the organic science behind it, but Timothy Stiles' Poly is some of the most beautiful Go code I've seen: https://github.com/TimothyStiles/poly
Blew my mind reading through it, honestly. Just perfect.
sniffnet
- Sniffnet – Comfortably monitor your Internet traffic (Like Wireshark)
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Save the date: GitHub Accelerator Demo Day on June 28
I’ll be personally talking about Sniffnet, the Rust-based network monitoring tool I’m working on: I’m so excited to share it with the world!
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Sniffnet – version 1.2.1 has just been released
Sniffnet is a Rust-based network monitoring tool to help everyone inspect their Internet traffic.
- FLaNK Stack Weekly for 22 May 2023
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Sniffnet, a network monitoring tool written in Rust, is currently ranked #4 in Hacker News front page!
It's my pleasure to announce that Sniffnet (a Rust tool to comfortably monitor network traffic) reached two other crucial milestones: being featured HN and surpassing Wireshark GitHub stars!
- Sniffnet: Open-source, cross platform application to monitor network traffic
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Announcing Sniffnet v1.2.0
Sniffnet is an open-source software developed in Rust to comfortably monitor your network traffic. This project has been selected for the GitHub Accelerator Program and I’m currently working on it full-time. Today it’s a pleasure for me to announce version 1.2.0: this is one of the biggest Sniffnet updates so far, introducing several features including host-based traffic analysis.
What are some alternatives?
nuxt - The Intuitive Vue Framework.
zenoh - zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks.
libpnet - Cross-platform, low level networking using the Rust programming language.
sniffglue - Secure multithreaded packet sniffer
flowlogs-pipeline - Transform flow logs into metrics
dioxus - Fullstack GUI library for desktop, web, mobile, and more.
message-io - Fast and easy-to-use event-driven network library.
Raylib-CsLo - autogen bindings to Raylib 4.x and convenience wrappers on top. Requires use of `unsafe`
junodb - JunoDB is PayPal's home-grown secure, consistent and highly available key-value store providing low, single digit millisecond, latency at any scale.
pypandoc - Thin wrapper for "pandoc" (MIT)
pg-mem - An in memory postgres DB instance for your unit tests
linaria - Zero-runtime CSS in JS library