Transforming Python Scripts into Interactive Data Apps with Preswald

Building and deploying data apps used to mean juggling a mishmash of tools — front-end frameworks, complex back-end setups, and endless boilerplate code. Today, Preswald is changing the game by allowing you to turn your Python scripts into fully interactive apps, dashboards, and internal tools — without writing a single line of frontend code.

What is Preswald?

Preswald is an open-source framework designed specifically for data engineers, analysts, and developers who want to create production-ready data applications fast. It takes your standard Python scripts and, with minimal adjustments, transforms them into interactive web apps that you can run locally or deploy to the cloud in just one command.

Some of its key benefits include:

• Code-First Simplicity: Write your logic in Python and let Preswald handle the user interface.

• Pre-Built UI Components: Add tables, charts, text inputs, and buttons without having to learn HTML, CSS, or JavaScript.

• Stateful Execution: Thanks to its DAG-based execution model, only the parts of your code that change are re-run, making your apps both efficient and predictable.

• Instant Deployment: With a single command, your app can go live and be shared with colleagues or clients instantly.

Why Preswald?

Traditional dashboards often require multiple layers of configuration and a steep learning curve for those not well-versed in frontend development. Preswald bridges that gap by offering:

• Rapid Prototyping: Quickly build interactive dashboards to explore data in real time.

• Seamless Collaboration: Share a simple URL with stakeholders who can interact with your app without any local setup.

• Reduced Overhead: Focus on data analysis and insights instead of the intricacies of web development.

In a world where speed and simplicity are key, Preswald empowers teams to iterate faster and communicate insights more effectively.

Getting Started: A Quick Tutorial

Let’s dive into how you can build your first Preswald app. We’ll cover installation, project initialization, writing a simple app, and running it locally.

Step 1: Install Preswald

Install Preswald via pip:

pip install preswald

Step 2: Initialize a New Project

Create a new project directory and get the initial scaffold set up:

preswald init my_project
cd my_project

This command creates essential files including:

• hello.py: Starter application script.

• preswald.toml: Configuration file for your app.

• secrets.toml: Secure file for storing sensitive data.

• README.md: Simple introduction to the preswald project.

• data/: Directory for some sample data.

• images/: Directory with logo, favicon, and readme gif.

Step 3: Write Your First App

Open the hello.py file and add the following code:

from preswald import text, plotly, connect, get_df, table
import pandas as pd
import plotly.express as px

# Display a welcome message
text("# Welcome to Preswald!")
text("This is your first interactive app built entirely in Python.")

# Connect to data sources (by default, a sample CSV is loaded)
connect()
df = get_df('sample_csv')

# Create a scatter plot to visualize data
fig = px.scatter(
    df, 
    x='quantity', 
    y='value', 
    text='item',
    title='Quantity vs. Value',
    labels={'quantity': 'Quantity', 'value': 'Value'}
)
fig.update_traces(textposition='top center', marker=dict(size=12, color='lightblue'))
fig.update_layout(template='plotly_white')

# Render the plot and data table in your app
plotly(fig)
table(df)

This script does the following:

• Uses the text function to add headers and descriptive text.

• Loads data with connect() and get_df().

• Creates a Plotly scatter plot that updates interactively.

• Displays the underlying data in a neat table.

Step 4: Run Your App Locally

Launch your development server with:

preswald run

The tool will output a URL (typically something like http://localhost:8501) where you can view your interactive app in your browser.

Step 5: Generate an API key

1. Go to https://app.preswald.com

2. Sign in using your GitHub account

3. Generate an API key in: Organization > Manage > Settings > API Keys

Step 5: Deploy with a Single Command

Once you’re satisfied with your local app, deploying is just as simple:

preswald deploy - target structured - github <github-username> - api-key <structured-api-key> hello.py

This command packages your app and makes it accessible online, so you can instantly share your work with others.

What Preswald Handles

• Cloud deployment: Automates the process of containerizing your app, configuring the environment, and deploying it to the target platform.

• Local testing: Builds a container locally to let you verify your app before cloud deployment.

• Live preview: Provides a shareable URL (for cloud deployments) so others can interact with your app.

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Preswald Studio Setup

1. Go to https://app.preswald.com

2. Sign in using your GitHub account

3. Click “+ New project” to create a fresh workspace

4. Upload the provided CSV file via the Upload button

Choose a Dataset

Select/download a dataset from any of these sources:

• Kaggle Datasets

• Data.gov

• Open Data Repositories

• Any csv (e.g., weather, finance, sports stats)

Place your dataset in the data/ folder of your project.

Implement Your Preswald App

Modify hello.py to include the following:

1. Load the dataset

from preswald import connect, get_df      
connect()  # Initialize connection to preswald.toml data sources 
df = get_df("my_dataset")  # Load data

2. Query or manipulate the data (For SQL database or Use Pandas as pd for other data manipulation)

from preswald import query      
sql = "SELECT * FROM my_dataset WHERE value > 50" filtered_df = query(sql, "my_dataset")

3. Build an interactive UI

from preswald import table, text  
text("# My Data Analysis App") 
table(filtered_df, title="Filtered Data")

• Add user controls:

from preswald import slider, view 
threshold = slider("Threshold", min_val=0, max_val=100, default=50) 
table(df[df["value"] > threshold], title="Dynamic Data View")

4. Create a visualization

from preswald import plotly 
import plotly.express as px  
fig = px.scatter(df, x="column1", y="column2", color="category") 

plotly(fig)

🔹 Add Other Widgets

Add other widgets to your app. Reference the docs here: Preswald SDK

5. Customize the Branding

Edit the preswald.toml file to customize the branding.

• Change the title of the app

• Change the favicon

• (Optional) Change the logo (will be visibile if you use sidebar() component)

• (Optional) Change the color scheme (will be visibile if you use sidebar() component)

👀 6. Preview Your App

Use the Preview tab in the IDE to view your app.

🚀 5. Get a Shareable Link

1. Generate an API key in: Organization > Manage > Settings > API Keys

2. Deploy your app using the Share button

• Enter your GitHub username and API key

3. View the status of the deployment in the Apps tab

Final Thoughts

Preswald is revolutionizing the way data apps are built by minimizing setup time and eliminating the need to write frontend code. Whether you’re a data scientist needing a quick dashboard to explore insights or an engineer looking to prototype internal tools rapidly, Preswald offers a powerful, streamlined solution.

By leveraging its code-first approach, stateful execution, and one-command deployment, you can transform your Python scripts into engaging, interactive applications in minutes — saving time, reducing complexity, and focusing on what really matters: your data.

Check Out My Project

I have also made one using Preswald.
GitHub: https://github.com/bibekkd/preswald_intern_project
Live Demo: https://my-project-602050-eyh7t8yg.preswald.app/

Check this out and let’s build more together!