Hello there, fellow coders, data science enthusiasts, and those just curious about cool Python stuff! ๐
Let me guess, youโve been juggling a bunch of data science projects, writing thousands of lines of code, and now you're ready to make your work look shiny and interactive with some cool dashboards. But then reality hits, and you realize that building apps is a whole new ball game. ๐ฐ
Enter Taipy, the superhero framework you didnโt know you needed. ๐ฆธโโ๏ธ๐ฅ
If you're ready to leave the land of static data outputs and leap into the world of interactive data apps โ then buckle up! ๐ This guide is for you. And yes, there will be memes along the way because, well, why not?
What Is Taipy?
Imagine this: Python had a cousin who is super chill, loves data science, and can create interactive applications with just a few lines of code. Meet Taipy.
Taipy is a framework designed to build end-to-end data science applications with minimal hassle.
๐ ๏ธ Setting Up Taipy: Itโs as Easy as Stealing Your Dogโs Snacks
First things first, you need to install Taipy. Donโt worry, itโs quick.
Installation ๐ฆ
Open up your terminal or command prompt and run ๐๐ฒ๐ญ๐ก๐จ๐ง ๐.๐ ๐ฏ๐๐ซ๐ฌ๐ข๐จ๐ง ๐ข๐ฌ ๐ง๐๐๐๐๐:
pip install taipy
Done. Thatโs it. Youโre now ready to create apps like a pro. ๐
๐ฎ Letโs Build Something Awesome (and Easy)
Time to get our hands dirty and build something. It's as simple as a few lines of code. Iโm not kidding.
Step 1: Create a Simple App
Letโs start with the basics graphical interface
Create a file called app.py, and add this code:
from taipy.gui import Gui
import taipy.gui.builder as tgb
from math import cos, exp
value = 10
def compute_data(decay:int)->list:
return [cos(i/6) * exp(-i*decay/600) for i in range(100)]
def on_slider(state):
state.data = compute_data(state.value)
with tgb.Page() as page:
tgb.text(value="# Taipy Getting Started", mode="md")
tgb.text(value="Value: {value}")
tgb.slider(value="{value}", on_change=on_slider)
tgb.chart(data="{data}")
data = compute_data(value)
if __name__ == "__main__":
Gui(page=page).run(title="Dynamic chart")
Step 2: Run the App
Head back to your terminal and run:
python app.py
Now you now have a basic web app showing a visualization chart. Go ahead, open it up in your browser, and bask in the glory of your creation.
Why Taipy?
You might be wondering, why should I care about Taipy when there are other frameworks out there like Dash, Streamlit, or Flask? Good question. Hereโs why Taipy stands out:
- Simplicity: You don't need to be an expert in web development to build interactive apps. Literally a few lines of ๐ฃ๐๐๐ต๐ผ๐ป code, and you're good to go. ๐งโโ๏ธ
- Interactivity: Out of the box, you get sliders, charts, and everything you need to make your data science app engaging. ๐น๏ธ
- Scalability: Taipy is perfect for both small projects and large enterprise-level apps. You can start small and grow big. ๐ฑโก๏ธ๐ณ
And did I mention itโs free? Yep. Free ๐ฎ๐ป๐ฑ ๐ผ๐ฝ๐ฒ๐ป-๐๐ผ๐๐ฟ๐ฐ๐ฒ. ๐ ๐๐ต๐ฒ๐ฐ๐ธ ๐ถ๐ ๐ผ๐๐ ๐ต๐ฒ๐ฟ๐ฒ : https://git.new/nwbwuCe
In Conclusion: Taipy is the Real MVP
Whether youโre a beginner looking to create interactive apps for your data science projects or someone who wants to automate their data pipelines, Taipy has your back.
Easy? โ๏ธ
Interactive? โ๏ธ
Cool enough to impress your friends and colleagues?โ๏ธโ๏ธโ๏ธ
So, what are you waiting for? Use Taipy, and start building the future today. ๐
Top comments (4)
I tried building a dashboard on Taipy, and it is indeed very easy.
Excellent article Jay ๐ค
+1
I have been using Taipy for more than two years now. It is indeed easy to build an application. Now, I have a complete application ready. I have to publish it. I am a forest researcher. Now, I want to give classes using the application I developed. How can I publish that? What do you suggest?
Silvana