streamlit

name	streamlit
version	1.0.0
description	Build interactive data applications and dashboards with pure Python - no frontend experience required
type	reference
author	workspace-hub
category	data-analysis
capabilities	["Rapid prototyping of data applications","Interactive widgets and user inputs","Data visualization integration (Plotly, Matplotlib, Altair)","Caching for performance optimization","Session state management","Multi-page application support","Cloud deployment ready"]
tools	["streamlit","plotly","pandas","polars"]
tags	["streamlit","dashboard","data-app","visualization","python","web-app","interactive","prototyping"]
platforms	["python","web"]
related_skills	["polars","dash","plotly","pandas-data-processing"]
requires	[]
scripts_exempt	true

Streamlit

When to Use This Skill

USE Streamlit when:

• Rapid prototyping - Need to build a data app quickly
• Internal tools - Creating tools for your team
• Data exploration - Interactive exploration of datasets
• Demo applications - Showcasing data science projects
• ML model demos - Building interfaces for model inference
• Simple dashboards - Quick insights without complex setup
• Python-only development - No JavaScript/frontend knowledge required

DON'T USE Streamlit when:

• Complex interactivity - Need fine-grained callback control (use Dash)
• Enterprise deployment - Require advanced authentication/scaling (use Dash Enterprise)
• Custom components - Heavy custom JavaScript requirements
• High-traffic production - Thousands of concurrent users
• Real-time streaming - Sub-second update requirements

Prerequisites

# Basic installation
pip install streamlit

# With common extras
pip install streamlit plotly pandas polars

# Using uv (recommended)
uv pip install streamlit plotly pandas polars altair

# Verify installation
streamlit hello

Complete Examples

Example 1: Sales Dashboard

import streamlit as st
import pandas as pd
import polars as pl
import plotly.express as px
import plotly.graph_objects as go
from datetime import datetime, timedelta

# Page config
st.set_page_config(

*See sub-skills for full details.*
### Example 2: Data Explorer Tool

```python
import streamlit  st
 pandas  pd
 polars  pl
 plotly.express  px

st.set_page_config(page_title=, page_icon=, layout=)

st.title()


*See sub-skills  full details.*


```python
 streamlit  st
 pandas  pd
 numpy  np
 plotly.express  px
 sklearn.ensemble  RandomForestClassifier
 sklearn.model_selection  train_test_split
 sklearn.metrics  accuracy_score, classification_report

st.set_page_config(page_title=, page_icon=, layout=)

*See sub-skills  full details.*





```yaml

streamlit>=
pandas>=
polars>=
plotly>=
numpy>=