Recent submissions

Comment · 8 months ago
I’ve been playing around with https://nono.sh/ , which adds a proxy to the sandbox piece to keep credentials out of the agent’s scope. It’s a little worrisome that everyone is playing catch up on this front and many of the builtin solutions aren’t good.
Comment · 1 year ago
I'm also a long time conda user and have recently switched to pixi (https://pixi.sh/), which gives a very similar experience for conda packages (and uses uv under the hood if you want to mix dependencies from pypi). It's been great and also has a `pixi global` similar to `pipx`, etc the makes it easy to grab general tools like ripgrep, ruff etc and make them widely available, but still managed.
Comment · 2 years ago
I've added fasthtml (and its dependencies) to conda-forge, so it's available in conda/mamba now.
Comment · 4 years ago
I use numba quite a bit at work and it's fantastic. I recently, however, did a comparison between numba, cython, pythran and rust (ndarray) for a toy problem, and it yielded some interesting results:

https://github.com/synapticarbors/ndarray_comparison/blob/ma...

Most surprising among them was how fast pythran was with little more effort than is required of numba (still required an aot compilation step with a setup.py, but minimal changes in the code). All of the usual caveats should be applied to a simple benchmark like this.

Comment · 6 years ago
Comment · 7 years ago
It looks like Github, after some push back across various forums, reverted the change and the network graph is back.
Comment · 7 years ago
Comment · 10 years ago
Comment · 10 years ago
Comment · 10 years ago
First class multi-dimensional arrays with natural indexing syntax would be a huge draw. You get that in Numpy, Julia, Fortran and it is extremely powerful in terms of expressing the types of operations that are common across many scientific domains.
Comment · 10 years ago
Comment · 10 years ago
Conda is 100% free and open source, but is developed by Continuum, which is a company (but one that contributes heavily to many of the key components of the open-source pydata/scipy ecosystem, and whose CEO basically created numpy/scipy for the community at the expense of his academic career). Personally I have had nothing but good interactions with people from Continuum and the software they develop. They (as a company and as the individuals in it) do an incredible amount for the open source community and we all benefit from that. They seem to have worked out a sustainable model for running a company and working in/contributing to open source.

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