161–170 of 620 posts
Earlier quoted context omitted.
Is this an intelligent joke or a dumb business plan? I kept hearing the words "production" and "prototype", but I see half a dozen holes in a real world implementation. Edit: Since this is being downvoted, here are my thoughts. 1.) Plumbing. Pipes are in the walls. Kitchen tables are (usually) closer to the center of a room. (And who will consider open pipes or tubes across a floor or ceiling?). 1b.) Electrical. Same…
Jesus
My team started being more serious about our switching from .NET to a mix of Django, Flask and Vue.js this year, so I've been focusing on those. I personally played around with GraphQL (Apollo, Yoga and Graphene) for a while, but ultimately I didn't find a good use case for it in our setups and kind of left it at that. Our 2019 will be spent on building our AWS and Azure skills along with container setups, as we look…
When have you been using Django compared to Flask? I'm curious, since I often use Flask + vue, but haven't used Django much.
It has a lot of extra stuff included in the framework that you might not need for a smaller app, but if you don't care about that extra overhead (or you need to use it) then Django is a great choice.
It also has a fantastic ecosystem of "apps" (what Django calls plugins or packages) that you can drop into your project which can save a substantial amount of time; which makes it great for consulting work.
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.
Taught myself the basics of embedded systems, and completed a few projects. Learned circuit design, PCB layout, CAD / laser cutting, and embedded C / C++ in the process. Started with a 555 LED blinker [1]. Then built a desk clock, with a goal of writing a device driver for the LED display from the data sheet of a controller I found on DigiKey. After that, built my own USB keyboard, since I wanted to learn more about…
I really dug into APL style languages. I learned Mathematica which really opened my mind to new ways of programming. I also learned a lot about how web pages actually render. I highly recommend everyone checks out Chrome's Advanced Paint Rendering performance panel.
Do you use those at work?
I'm not sure this counts as a "technology" per se, but I've been bitten by the rendering bug and have spent the past year rekindling my traditional artistic passion for visual realism in the context of modern computer graphics techniques and have been fortunate enough to be in a position to apply graduate school for it.