interested in scientific computing and data science. May also be somewhat of a python zealot.
Washington DC area
Joined April 2014
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with module change autorun, the ability to use your own editor, and exporting to scripts,
@marimo_io has merged data science tooling with software engineering tooling!
The feedback loop you get when using @marimo_io is insane!
I recently had the deepest feeling of being in the zone when trying to solve a data analysis problem.
Thank you @akshaykagrawal. I consider this to be a *MAJOR* development in the @PyData stack.
(@DVCorg last mjr dev)
I'm seeing a maturation of the @PyData stack.
env mgt, project mgt, notebooks, data pipelining, distributed compute, viz, dataframes, tensor computation, are the "baseline" problems that seem to be essentially solved to me.
what else is there??
combination of:
* large population with a small percentage of high achievers who basically lift up everyone else (there is a study)
* higher ed: is still the best
* immigration: accommodation for researcher types and (proven) high achievers. (good students face barriers though)
...even if it does, morimo gives you the dep graph, a .py, and the ability to treat a notebook as a module.
jupyter doesn't come close to this. you'd need to create a Frankenstein.
best @PyData tooling progress i've seen in ~24 months,
@marimo_io , @quarto_pub , @mitsuhiko (rye), @astral_sh (ruff), @prefix_dev (pixi).
wtf is this obsession in tech with automating hiring (which is unautomatable). Do the work hiring companies!!
But after picking up egglog, should I not just express a graph as "rules" and go from there?
I'm motivated by category theory.
I just did something like this with minikanren "facts".
The query was just a conjunction of edges (pattern matching). Seems to work.
in python github.com/pythological/kanr…. i'm mainly motivated by symbolics use cases. obviously the machinery is different.
