# Streamlit Web App

This guide demonstrates how to create an interactive web application for data science and machine learning using **Streamlit**. Streamlit turns data scripts into shareable web apps in minutes, all in pure Python.

**Modules Used:**
*   `streamlit`: The framework for building the web app.
*   [[programming/python/modules/pandas-module|pandas]]: For data manipulation.
*   `numpy`: For generating dummy data.

## Installation

```bash
pip install streamlit pandas numpy
```

## The Code

Save this as `app.py`.

```python
import streamlit as st
import pandas as pd
import numpy as np

# 1. Page Configuration
st.set_page_config(
    page_title="My Streamlit App",
    page_icon="📊",
    layout="wide"
)

# 2. Title and Text
st.title("Simple Data Dashboard")
st.markdown("""
This is a demo app built with **Streamlit**. 
It allows you to visualize data and interact with widgets easily.
""")

# 3. Sidebar
st.sidebar.header("Settings")
num_points = st.sidebar.slider("Number of data points", 10, 100, 50)

# 4. Data Generation
def get_data(points):
    data = pd.DataFrame(
        np.random.randn(points, 3),
        columns=['A', 'B', 'C']
    )
    return data

df = get_data(num_points)

# 5. Layout: Columns
col1, col2 = st.columns(2)

with col1:
    st.subheader("Data Table")
    st.dataframe(df)

with col2:
    st.subheader("Line Chart")
    st.line_chart(df)

# 6. Interactive Widgets
st.divider()
st.subheader("User Input")

name = st.text_input("Enter your name", "Streamlit User")
if st.button("Say Hello"):
    st.success(f"Hello, {name}! Welcome to the app.")

# 7. Expander
with st.expander("See explanation"):
    st.write("""
        The chart above shows random numbers generated by NumPy.
        The slider in the sidebar controls how many rows are generated.
    """)
```

## Usage

To run a Streamlit app, you use the `streamlit run` command, not `python`.

```bash
streamlit run app.py
```

This will automatically open your default web browser to `http://localhost:8501`.

[[programming/python/python]]