mrocklin

6 ms·

1.
by mrocklin 8mo ago
Blas and faer are used only for small corners of the API (linalg and fft) which is exactly what numpy does. I encourage you to follow your own advice and look more closely at the interaction of ufuncs, strides, and dtypes.
2.
by mrocklin 8mo ago
Yup.
3.
by mrocklin 8mo ago
One can have fun with all manner of things. Take wood-working for example. One can have fun with a handsaw. One can also have fun with a table saw. They're both fun, just different kinds
4.
by mrocklin 8mo ago
If you read on in the post you might be interested in the section titled Drop Python: Use Rust and Typescript https://matthewrocklin.com/ai-zealotry/#big-idea-drop-python...
5.
by mrocklin 8mo ago
Original author of the post here. Just to give credit where it's due, that was a quote from this other excellent article written by someone else: https://www.stochasticlifestyle.com/a-guide-to-gen-ai-llm-vi...
6.
by mrocklin 1y ago
I mean, Dask doesn't have money. We're definitely not in a place to pay them a bounty. I imagine this is just marketing on their part, or driving up some metric to show customers. "Our powerful AI has identified vulnerabili
7.
by mrocklin 1y ago
I'm not convinced that human judgement was ever applied during this situation.
8.
AI published a bogus CVE for my project
20 points by mrocklin 1y ago|4 comments
9.
by mrocklin 2y ago
Hey folks, original author here. It seems like people here are really connecting with the specifics of the code review example. The main point of the article is really "what we learn in reviewing code in community open source might n
10.
by mrocklin 3y ago
Parallel for loops are the new black I guess
11.
by mrocklin 3y ago
$25 to process 250TiB seems cheaper than what I would expect. I've had (very good) beers that cost that much :)
12.
by mrocklin 11y ago
See http://dask.pydata.org/en/latest/ghost.html
13.
by mrocklin 11y ago
Thanks for the comments. I wrote most of that document so I'll try to explain my reasoning in line. > First and foremost, it would make more sense to compare against the DataFrame API of Spark, which is very Pandas like. It would m
14.
by mrocklin 11y ago
Flat CSV or JSON files are hard to parse. Fast CSV parsers and gzip decompression both run at around 100MB/s. If you want to get faster than this you'll need to use better (ideally binary) formats. This notebook might interest y
15.
by mrocklin 11y ago
Interesting. What are your thoughts on the costs of dependencies? What about toolz makes you hesitate to depend on it?
16.
by mrocklin 11y ago
http://toolz.readthedocs.org/en/latest/
17.
by mrocklin 11y ago
You can manage this by composing merge and merge_with In [1]: data = [{'a': {'b': 1}}, {'a': {'c': 2}}] In [2]: from toolz import merge, merge_with In [3]: merge_with(merge, data) Out[3]: {'a&#x2