Top Tweets for #PyShiny
๐ฆ peeky: Now extracts complex #Shinylive apps with nested files & binary data!
New vignette walks through converting #RShiny/#PyShiny apps to Shinylive AND back again.
Coming soon to CRAN (?!)
๐ Vignette: https://t.co/eSPGUZkWBp
๐ป Code: https://t.co/l7PUkTSyEF
Excited to share a follow-up to my prior tweet! This time, diving into deploying #python #pyshiny apps on #github using #shinylive. We focus again on saying goodbye to cluttered repo histories - we're keeping it clean and efficient! ๐
Repo: https://t.co/V29ANJmH2S

Just created and deployed a #pyshiny app with @neondatabase Postgres and to @flydotio. This is a low friction way to get up and running quickly with analytics and data science apps that require database access + Python. ๐ ๐
Excited to share a sneak peek of my latest project: a webapp built entirely in #Python, powered by #PyShiny. I like Shiny so far, fingers crossed for a smooth ride ahead!๐ค #WebDevelopment #CodingCommunity
Why Shiny for Python?ย
Since it came out of alpha, many ask how it stacks up against other popular alternatives. Gordon Shotwell explores #PyShiny's design philosophy & how it compares to other frameworks for developing #DataScience web apps.
https://t.co/0U2aASQGZh
#pydata
If you missed #ShinyConf:
{shiny-semantic} is available for #ShinyForPython
Check out the repository: https://t.co/gkryIvxBp6
You can install it from PyPI: https://t.co/32dyEWRZAI
#Python #PyShiny #RShiny #RStats
๐ #CSV data is quick and fun, but real-world data is often stored in #databases.
Learn how to access @MySQL and #PostgreSQL in this #Shiny for #Python databases guide. Check our recent blog post by @RadecicDario.
More๐https://t.co/GDtmQNvXM8
#rstats @ThePSF #PyShiny #mysql

๐๐๐ Welcome to the team, @MichalskiBolek, Angel, Erick, @Gokhan_Kocturk_ ! We work with people who can make a difference and we're delighted to have you onboard! Looking forward to helping you make waves! ๐ #AppsilonTeam #rstats #rshiny #r #pyshiny #shiny

For my DS class, I made a Shiny for Python App that shows Decision Boundaries for 4 classification models:
โ
Logistic Regression
โ
Naive Bayes
โ
Decision Tree
โ
KNN
using Palmer ๐ง, Iris ๐ธ, or Diabetes๐ฉธ datasets.
#pyshiny

Things Iโm most excited about changing:
โ
using Shiny for Python in my intro CS class
This will allow students to DO MORE with their budding coding skills without being overwhelmed #pyshiny
Students get the fun and engagement of working w an interactive/tangible version of their code WITHOUT THE NORMAL MESS๐ฅณ
I think this will be hugely motivating for students๐ฉ๐ปโ๐ป by letting them SEE their code in action.
You can try this Squid Game App here: https://t.co/4nesH1XhRX
For those of you excited about Python for Shiny (announced just now at #RstudioConf), I GOT TO HELP DEVELOP EXAMPLE APPS and Iโm going to be talking about it a lot now that Iโm FINALLY ALLOWED TO.
One of my apps is even a featured example on the website!
https://t.co/nmxAsyX8eO

#ShinyforPython: Unser Partner @rstudio รถffnet #RShiny fรผr die #Python-Community
Erfahren Sie mehr zu #PyShiny und Shinylive - auf unserem Datenanalyse-Blog https://t.co/p7iS3GtWbP
And thanks to #shinylive, #pyshiny can even render ipywidgets without a server!
https://t.co/awSUwcyncO
https://t.co/wfE7OTiEku
But for more complex apps that can't run in the browser, you can also deploy to https://t.co/w26J57ofnN or @rstudio Connect
https://t.co/lS6eHNH0CL

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