1,686 karma · joined September 27, 2017
Congrats on the product BTW. Very promising!
I've been looking forward to something like this for years.
I misspelled the celeb's name and my site was the 3rd result on Altavista when other people made the same spelling error. I put a counter and saw a lot of visits, so I added some banner ads.
A few weeks later I got a nice paper check that I converted from French Francs to Belgian Francs in the bank. It was before the EUR!
It was nice to have some pocket money, but I've always been ashamed of this site. 20 years later, I'm starting to think that it was kind of cool... It's still on archive.org!
[0] https://stackoverflow.com/questions/48726636/draw-d3-axis-wi...
With Vue.js, I use computed properties + v-for in html template.
With D3 I use the the enter/update/exit pattern with d3.selectAll(...).data(...).join(...).
Both seem to only modify the needed DOM elements. Vue.js uses a virtual DOM while D3 attaches a __data__ property to DOM elements.
I tend to leave DOM manipulation to Vue.js unless I need to animate transitions between states. I find it easier to reason about binding data to an html/svg template with Vue than to mess with d3 data joins and enter/update/exit pattern.
d3 is and stays an impressive piece of work.
Misdirected Request
The client needs a new connection for this request as the requested host name does not match the Server Name Indication (SNI) in use for this connection.
Apache/2.4.25 (Debian) Server at example.com Port 443
I need to call my bank to temporarily unlock it if I ever go to the US. Payments with PIN code are allowed by default though even in the US. So the problems seem to be with the swipe system.
That’s more than the ceiling for CEOs of public companies in my country.
Tech salaries in the US really seem out of proportions.
For the front-end I usually use Leaflet with Mapbox (raster) tiles. I should switch to vector tiles but "@2x" raster tiles look good enough on HiDPI/Retina displays.
I'm also an heavy QGIS user. I've managed to convince IT to put it in our internal Software Center so users can install it in one click without needing to be admin. It's becoming quite successful internally ;-). Take this Esri!
However we still pay hundreds of k€ to Esri and nothing to QGIS. I've personnally donated a few euros but it's a really small amount compared to what we pay to Esri.
These days I also tend not to use d3 for DOM manipulation, but only for its powerful helper functions (d3-scale, d3-array, d3-shape, d3-geo etc.)
I even try not to import d3-selection except for very specific cases.
I’m using Vue for DOM manipulation, and computed properties play very well with d3 helper functions (i.e. a scale which auto-updates itself reactively). In a way it’s very similar to ObservableHQ’s reactivity. Most examples from Observable can be relatively easily converted to Vue with computed properties.
I’m not from the US and in my country, “(civil) Engineer” is a legally protected title https://en.m.wikipedia.org/wiki/Civil_engineer#Belgium
[0] https://cli.vuejs.org/guide/deployment.html#github-pages
I asked him if they weren’t shooting themselves in the foot. He responded: “I can either fire everyone now or in a few years, what would you chose?”.
I’m glad I don’t have to take this kind of decision.
Too bad for a (fun and clever) Microsoft advertising.
def fizzbuzz(n):
case (n % 3, n % 5):
match (0, 0): return "FizzBuzz"
match (0, _): return "Fizz"
match (_, 0): return "Buzz"
else: return n |> str
(
range(1, 100)
|> map$(fizzbuzz)
|> x -> '\n'.join(x)
|> print
)During the summer I also took the "CS50's Web Programming with Python and JavaScript" class on edX. It taught me about Flask and Django.
Since then I've made two apps for work:
- one is a data visualization to coordinate railway infrastructure works using Vue.js/D3.js and an API made with Flask
- the other is a standard (server-side rendered) Django app. It is a search engine for scanned PDF documents. There are also scripts to extract text from documents using OCR with ocrmypdf based on tesseract. The text is then loaded in a PostgreSQL database to make it full-text searchable. There are 30k documents and 130k pages.
Both apps are currently running on my company's internal OpenShift cluster so I also had to learn OpenShift, Docker, Kubernetes...
Since September I'm back at the university every Monday for an Executive Master in Datascience. I'm currently learning machine learning (using Python, scikit-learn, numpy/pandas, matplotlib, tensorflow etc.), graph mining and data visualization. Here is our dataviz project: https://ufo.kediss.eu based on the UFO sightings dataset on Kaggle. I'm currently studying for the exams in January.