5d749d7da7d5
Joined 6 years ago
Joined 6 years ago
Have not yet had a chance to try the idea, but I am toying with using render-images to bake in pre-built plots + markdown for reporting the output. Queryable report in a file. Dynamic Vega plotting (RShiny-ish) is also in the back of my mind, but that feels too close to magic.
It is an incredibly useful tool, and I appreciate the workflows you have enabled.
Instead, I can dump all of the processed results into a table, create some views highlighting analysis X vs Y, and share links that give others the ability to ask questions I had not even considered. Now the user is empowered to ask anything and they do not need to engage me for "simple questions". Everybody wins. I believe there is also an extension that allows you to generate and save new queries through the web interface.
It is not a tool for a professional analyst, but a means to collaborate with others. There are heavier/more feature rich alternatives, but Datasette is my favorite tool for getting results out the door without hassle (can run it off of a laptop after a pip install).
Perhaps a bit of a far out question - I would be interested in using this for optimizing real-world (ie slow, expensive, noisy) processes. A caveat with this is that the work is done in batches (eg N experiments at a time). Is there a mechanism by which I could feed in my results from previous rounds and have the algorithm suggest the next N configurations that are sufficiently uncorrelated to explore promising space without bunching on top of each-other? My immediate read is that I could use the package to pick the next optimal point, but would then have to lean on a random search for the remainder of the batch?
That was Hershey and Chase [0]. Watson and Crick were the first to solve the structure of DNA.
[0] https://en.wikipedia.org/wiki/Hershey%E2%80%93Chase_experime...
[0] https://www.cbsnews.com/news/koch-brothers-network-will-spen...
I just checked my go-to hardware recommendation site, Logical Increments[0], and not a single Intel CPU makes the list. AMD everything.
If I were the Anu people, I would focus on having a seamless compatibility layer that could manage Git <-> Anu repositories (there are undoubtedly many headaches that would occur synchronizing the two different models). This would allow developers to silently interact with ongoing git repos using the "better" tool. Getting wholesale migration to a new platform seems a significant challenge, but allowing developers to slowly build mind share with an improved workflow would be possible.
Disclaimer: I hate git.
I would be fine taking a healthy performance hit if I knew that the base OS was secure. (At this point I expect the BSD folks to chime in that they have had this for years)
With remote, I am able to do all coding on a non-infested Linux server with almost seamless usability.
My big complaint is the number of titles that receive a Platinum rating on ProtonDB, in spite of technical issues. I have purchased more than one title with a Platinum rating that had significant issues running on my machine.
This is compounded that Steam/ProtonDB user reports typically have an abysmal level of detail to replicate a working configuration. Someone got it to run flawlessly, but there is so much wine configuration jargon that each time I need to dig into the issues, I waste time on something that otherwise would work on Windows. I would love if there was a 'share my Proton configuration' per game that could be made available to the community.