pea

17 ms·

151.
by pea 6y ago
If you want to share results from your Python analysis (such as visualizations, tables, datasets, files), check out what we're doing at Datapane. It's a Python framework and API for building and sharing reports. Some people use it
152.
by pea 6y ago
Not sure how they got that quite so wrong from an engineering POV. We try and use Slack video calling probably every day and have to revert to Meet/Zoom/Discord/WhatsApp, due to terrible latency, random crashes (like not be
153.
by pea 6y ago
For Python, Datapane may solve your use-case (I am one of the founders). It's an open source framework for creating HTML reports from text, dataframes, plots (altair/bokeh/plotly/folium), and files. We provide a free pub
154.
by pea 6y ago
I also found with lichess that blitz players are a lot stronger than rapid - I'm 200 points higher on rapid than blitz and it seems that's pretty common, which has always confused me (and not hugely different time controls - 5+3 v
155.
by pea 6y ago
One of my favourite things about the old blackberrys was that the alarm went off... even when the phone had 'run out' of battery! seriously awesome feature.
156.
by pea 6y ago
I actually have this pretty much constantly, as well as after images on lights and what not.
157.
by pea 6y ago
Am presuming this is distinct from the problems with the main website (i.e. they aren't trying to push people off of that too), but maybe related in the sense that it seems the strategy is to turn the website into an app instead of kee
158.
by pea 6y ago
This makes a lot of sense. I would rather they either built amazing orthoganal SaaS products and charged me for them, or had some >$100k ACV enterprise plays. On the former, it's of course a massive shift off of their current focus
159.
by pea 6y ago
Not to mention that having 25cl of raki after lunch isn't really a sustainable day-to-day habit unless you are on the beach :)
160.
by pea 6y ago
Altair is SO fantastic. For the Python side, I maintain a gallery of community visualisations built in Altair, Plotly, Bokeh, Folium etc https://datapane.com/gallery/
161.
by pea 6y ago
Yep, there are some websites which _should_ be SPAs because they are actual applications - for instance, I can't imagine Google Docs or Trello as an MPA. But, many websites are a graph of documents (like Reddit), so trying to model the
162.
by pea 6y ago
So this has gotten to the point for me where it is a big enough burning painpoint where I would pay for a service which provided passably fast versions of the web-based tools which I frequently have to use. In my day-to-day as a startup fou
163.
by pea 6y ago
In haskell, a lot of the uptake in financial services is because they are writing internal DSLs to do things like modelling exotic options.
164.
by pea 6y ago
There is a good book on this called "Uncivil Agreement" which I enjoyed. It covers how, on both sides of the US political spectrum, identity trumps political issues in what people care about. I think identity has been more of a fo
165.
by pea 6y ago
BTW, the 5000 restriction is more a "guide" for structuring your data - you can turn it off. Also, Altair plots can certainly be used outside of notebooks! Happy to share some examples..
166.
by pea 6y ago
Hey, that's what we do at Datapane! https://docs.datapane.com/tutorials/tut-creating-a-report - you can create a standalone HTML report which contains interactive tables and plots. You can also publish this to the
167.
by pea 6y ago
I find the big benefit of Altair is that the API is so nice and composable, and because vega provides a ton out of the box to build really high quality visualisations. For instance, if you take this (sample) report using Altair to plot Defa
168.
by pea 6y ago
Cool! Have you checked out https://github.com/bvaughn/react-virtualized too? Might be totally useless to you, but I think they've done a lot under the hood to optimise table loading. Congrats again on a beautiful
169.
by pea 6y ago
Great work - really clean documentation, and it looks beautiful! We currently use `react-table`, which is good in that it can support some reasonably large datasets (for instance, here's 2 million rows on the client-side - https:&#x2F
170.
by pea 6y ago
Do you guys think k8s is doing a job which previously the jvm did in enterprise? i.e. if everything is on the jvm, building distributed systems doesn't require a network of containers. Can k8s success be explained partly due to the nee
171.
by pea 6y ago
Awesome - kind of reminds me of the Renoise interface!
172.
by pea 6y ago
I had this the other day when I was reading about the origin of the word 'bear'. I found this page: https://charlierussellbears.com/LinguisticArchaeology.html This is anecdotal, and I'm not making a "the
173.
by pea 7y ago
I've also seen small teams of smart engineers using decidedly "boring" stack like Django/Rails + MPA on EBS do as much as much work as a larger teams going hard on more cutting edge stuff (React + Redux + Scala on k8s).
174.
by pea 7y ago
The unintended benefit of this is that the battery is soldered to the keyboard. So, when your battery is failing, you can take your keyboard in to get fixed under the service programme and get a new battery for free.
175.
by pea 7y ago
Hey - I'm hacking on a product which allows you to build interactive browser-based apps/dashboards from Python and dataset blocks. You can return altair (vega) plots from your Python and they'll get rendered in the app, and w
176.
by pea 8y ago
I agree. Anecdotally, I've seen a few of companies hire large data science teams and operate them outside the context of any product management; i.e. as basically R&D arms. The problem is that most companies do not have R&D-lev
177.
by pea 8y ago
I grew up and went to school in Silicon Valley ('02 - '08), and remember one of the most stark contrasts was the difference in sociodemographics when you crossed from Palo Alto to EPA. Crazy difference in school quality, poverty,
178.
by pea 8y ago
What really flummoxes me is how my Yamaha SY99, which is a digital FM synth from 1991 with 512kb of memory and, by modern standards, a tiny, tiny CPU, manages to do things that are really CPU intensive on a normal OS (like large plate rever
179.
Not Hot Dog: Exploring the Accuracy Paradox(blog.nstack.com)
2 points by pea 9y ago|0 comments
180.
by pea 9y ago
We're actually building something really similar at https://nstack.com . You can deploy your Python model into an API in one command, and then turn it into an HTTP endpoint, or build plug-and-play workflows with your data wa

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