4 ms·

Most popular product on the planet acquires a random python packaging org for mindshare? What am I not seeing here?

__float 7mo ago
"uv" is a very widely used tool in the Python ecosystem, and Python is important to AI. Calling it "a random Python packaging org" seems a bit unfair.
nilkn 7mo ago
I feel like it's pretty easy to predict what OpenAI is trying to do. They want their codex agent integrated directly into the most popular, foundational tooling for one of the world's most used and most influential programming languages. And, vice versa, they probably want to be able to ensure that tooling remains well-maintained so it stays on top and continues to integrate well with their agent. They want codex to become the "default" coding agent by making it the one integrated into popular open source software.
- MoreQARespect 7mo ago
  This makes much more sense as an zoom-buys-keybase style acquihire. I bet within a month the astral devs will be on new projects. Bundling codex with uv isnt going to meaningfully affect the number of people using it. It doesnt increase the switching costs or anything.
aldanor 7mo ago
One of the popular products on the planet acquires the most popular python packaging org
KeplerBoy 7mo ago
The dev market? Anthropic's services are arguably more popular among a certain developer demographic. I guess this move might end up in a situation where the uv team comes up with some new agent-first tooling, which works best or only with OAI services.
mcmcmc 7mo ago
This just seems like panic M&A. They know they aren’t on track to ever meet their obligations to investors but they can’t actually find a way to move towards profitability. Hence going back to the VC well of gambling obscene amounts of money hoping for a 10x return… somehow
OJFord 7mo ago
What you're not seeing, edited inline, is: Not-most popular LLM software development product on the planet acquires most popular/rapidly rising python packaging org for mindshare.
Ygg2 7mo ago
I didn't know Claude bought Astral! /S
everforward 7mo ago
I think this is more about `ruff` than `uv`. Linting is all about parsing the code into something machines can analyze, which to me feels like something that could potentially be useful for AI in a similar way to JetBrains writing their own language parsers to make "find and replace" work sanely and what not. I'm sort of wondering if they're going to try to make a coding LLM that operates on an AST rather than text, and need software/expertise to manage the text->AST->text pipeline in a way that preserves the structure of your files/text.
- skydhash 7mo ago
  Writing a parser is not that much of work to buy a company in order to do it. Piggybacking on LSP servers and treesitter would be more efficient.
  - everforward 7mo ago
    Writing a literal parser isn’t too hard (and there’s presumably an existing one in the source code for the language). Writing something that understands all the methods that come in a Django model goes way beyond parsing the code, and is a genuine struggle in language where you can’t execute the code without worrying about side effects like Python. Ty should give them a base for that where the model is able to see things that aren’t literally in the code and aren’t in the training data (eg an internal version of something like SQLAlchemy).
    - skydhash 7mo ago
      If you’re talking about magic methods/properties enabled by reflection and macros, then you’re no longer statically analyzing the code.
      - everforward 7mo ago
        Static analysis just requires that you don't actually execute the code. It's possible (sometimes) to infer what methods/properties would be create without actually statically analyzing the code. E.g. mypy has a plugin to read the methods and return types of SQLAlchemy records, I believe without actually executing them. Obviously not globally true, but in limited domains/scenarios you can see what would exist without actually executing the code.

"uv" is a very widely used tool in the Python ecosystem, and Python is important to AI. Calling it "a random Python packaging org" seems a bit unfair.

nilkn 7mo ago

I feel like it's pretty easy to predict what OpenAI is trying to do. They want their codex agent integrated directly into the most popular, foundational tooling for one of the world's most used and most influential programming languages. And, vice versa, they probably want to be able to ensure that tooling remains well-maintained so it stays on top and continues to integrate well with their agent. They want codex to become the "default" coding agent by making it the one integrated into popular open source software.

MoreQARespect 7mo ago
This makes much more sense as an zoom-buys-keybase style acquihire. I bet within a month the astral devs will be on new projects. Bundling codex with uv isnt going to meaningfully affect the number of people using it. It doesnt increase the switching costs or anything.

aldanor 7mo ago

One of the popular products on the planet acquires the most popular python packaging org

KeplerBoy 7mo ago

The dev market? Anthropic's services are arguably more popular among a certain developer demographic. I guess this move might end up in a situation where the uv team comes up with some new agent-first tooling, which works best or only with OAI services.

mcmcmc 7mo ago

This just seems like panic M&A. They know they aren’t on track to ever meet their obligations to investors but they can’t actually find a way to move towards profitability. Hence going back to the VC well of gambling obscene amounts of money hoping for a 10x return… somehow

OJFord 7mo ago

What you're not seeing, edited inline, is: Not-most popular LLM software development product on the planet acquires most popular/rapidly rising python packaging org for mindshare.

Ygg2 7mo ago

I didn't know Claude bought Astral! /S

everforward 7mo ago

I think this is more about `ruff` than `uv`. Linting is all about parsing the code into something machines can analyze, which to me feels like something that could potentially be useful for AI in a similar way to JetBrains writing their own language parsers to make "find and replace" work sanely and what not. I'm sort of wondering if they're going to try to make a coding LLM that operates on an AST rather than text, and need software/expertise to manage the text->AST->text pipeline in a way that preserves the structure of your files/text.

skydhash 7mo ago
Writing a parser is not that much of work to buy a company in order to do it. Piggybacking on LSP servers and treesitter would be more efficient.
- everforward 7mo ago
  Writing a literal parser isn’t too hard (and there’s presumably an existing one in the source code for the language). Writing something that understands all the methods that come in a Django model goes way beyond parsing the code, and is a genuine struggle in language where you can’t execute the code without worrying about side effects like Python. Ty should give them a base for that where the model is able to see things that aren’t literally in the code and aren’t in the training data (eg an internal version of something like SQLAlchemy).
  - skydhash 7mo ago
    If you’re talking about magic methods/properties enabled by reflection and macros, then you’re no longer statically analyzing the code.
    - everforward 7mo ago
      Static analysis just requires that you don't actually execute the code. It's possible (sometimes) to infer what methods/properties would be create without actually statically analyzing the code. E.g. mypy has a plugin to read the methods and return types of SQLAlchemy records, I believe without actually executing them. Obviously not globally true, but in limited domains/scenarios you can see what would exist without actually executing the code.