SUsuper_linear·Dec 15, 2023Submission
Tangram open sourced their package manager code
1 points · Open discussiontangramdotdev
tangram
Rust2021–2023
tangramdotdev / tangram
tangram
Tangram is a build system and package manager.
3Distinct people
5Mentions
0Explicit recommenders
139GitHub stars
What to know before exploring
What it is
Tangram is a build system and package manager.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month5 dated mentions
Observed mentions: 2021-08-18 14:04:06 UTC to 2023-12-15 00:46:08 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Aug 2021 | 2021-08-01 00:00:00 UTC | 2021-09-01 00:00:00 UTC | 2 | 0 | 2 |
| Sep 2021 | 2021-09-01 00:00:00 UTC | 2021-10-01 00:00:00 UTC | 1 | 0 | 1 |
| Oct 2021 | 2021-10-01 00:00:00 UTC | 2021-11-01 00:00:00 UTC | 1 | 0 | 1 |
| Nov 2021 | 2021-11-01 00:00:00 UTC | 2021-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2021 | 2021-12-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2022 | 2022-01-01 00:00:00 UTC | 2022-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2022 | 2022-02-01 00:00:00 UTC | 2022-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2022 | 2022-03-01 00:00:00 UTC | 2022-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2022 | 2022-04-01 00:00:00 UTC | 2022-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2022 | 2022-05-01 00:00:00 UTC | 2022-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2022 | 2022-06-01 00:00:00 UTC | 2022-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2022 | 2022-07-01 00:00:00 UTC | 2022-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2022 | 2022-08-01 00:00:00 UTC | 2022-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2022 | 2022-09-01 00:00:00 UTC | 2022-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2022 | 2022-10-01 00:00:00 UTC | 2022-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2022 | 2022-11-01 00:00:00 UTC | 2022-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2022 | 2022-12-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2023 | 2023-01-01 00:00:00 UTC | 2023-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2023 | 2023-02-01 00:00:00 UTC | 2023-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2023 | 2023-03-01 00:00:00 UTC | 2023-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2023 | 2023-04-01 00:00:00 UTC | 2023-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2023 | 2023-05-01 00:00:00 UTC | 2023-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2023 | 2023-06-01 00:00:00 UTC | 2023-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2023 | 2023-07-01 00:00:00 UTC | 2023-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2023 | 2023-08-01 00:00:00 UTC | 2023-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2023 | 2023-09-01 00:00:00 UTC | 2023-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2023 | 2023-10-01 00:00:00 UTC | 2023-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2023 | 2023-11-01 00:00:00 UTC | 2023-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
5 sourcesTangram | Senior Rust Programmer | Remote | https://www.tangram.dev
Tangram is an all in one machine learning framework designed for programmers. With Tangram, developers can train models and make predictions on the command line or with libraries for languages including Elixir, Go, JS, Python, Ruby, and Rust, and learn about their models and monitor them in production from a web application. To learn more about what the product does, watch the demo on the homepage at https://www.tangram.dev or check it out on GitHub at https://www.github.com/tangramdotdev/tangram.
We are looking to grow our engineering team with senior Rust programmers. We are currently based in Boston, MA but are looking to build a remote team. At Tangram, you'll get to work on everything from our core machine learning algorithms to writing front-end code in Rust! We are
Read the rest
looking for developers with experience in Rust and familiarity with or willingness to learn machine learning concepts. If this sounds exciting, email me (Isabella, cofounder) at isabella@tangram.dev.
We chose to use Rust instead of TypeScript for the front end of https://github.com/tangramdotdev/tangram.
This allows us to:
* Share code with our server written in Rust.
* Avoid keeping types in TypeScript in sync with Rust.
* Do server rendering without including a JavaScript runtime.
* Avoid maintaining a JS stack, including TypeScript, Prettier, ESLint, and a bundler.
Because we split our project into many crates, incremental build times are about 1-2 seconds on a linux desktop. This is not as convenient for quick iteration on UI/UX as hot reload with React, but on the other hand, code that type checks is more likely to run correctly.
Overall, I would say that the trade offs are not clear, even for our unique case where we have a server written in Rust.
I am hopeful that in the future, browsers will enable native DOM access from WASM,
Read the rest
and the Rust compiler will support code splitting between multiple WASM entrypoints. When this happens, I think there will be a strong case to recommend Rust for more front end projects.
Great idea! We definitely want to do this. We have an open issue to track it: https://github.com/tangramdotdev/tangram/issues/28.
In Show HN: Tangram – Train a model from a CSV file on the command lineHi HN! We are Isabella and David, and we're excited to share Tangram, our attempt to make ML easy for programmers who are not experts. With Tangram, you train a model from a CSV file on the command line, use your model from one of many languages (so far we have libraries for Elixir, Go, JavaScript, Python, Ruby, and Rust), and learn about your models and monitor them in production from a web app. There's a video on our homepage (https://www.tangram.dev) and we're on GitHub at https://github.com/tangramdotdev/tangram.
Over the past few months we have been working with a handful of early users. A team at a small company had a TensorFlow model deployed as a Flask service consumed by their Elixir app. They replaced it with a Tangram model because they didn't want to maintain a server separate from their monolith. A team of front end engineers
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at a large company was looking for a way to to train and deploy models on their own, without the overhead of involving their data scientists, machine learning engineers, or backend engineers. They trained a model on their own and embedded it directly in their React front-end with the Tangram JavaScript library that makes predictions with WebAssembly.
Tangram is written entirely in Rust, from the core machine learning algorithms, to the bindings for each language, to the front and back end of the web application. We have benefited from Rust's fast performance, strong typing, convenient tooling, and high quality libraries (serde, tokio, hyper, sqlx, and more).
We hope to make Tangram a sustainable business with the open core business model. The CLI and language libraries are MIT licensed, while the web application is source available, free to use for testing, but requires a paid license to use in production.
We would love to hear your feedback. Give it a try and let us know what you think!