> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/marimo-team/marimo/llms.txt
> Use this file to discover all available pages before exploring further.
# Quickstart
> Get started with marimo in minutes - from installation to your first interactive notebook
# Quickstart
Get up and running with marimo in minutes. This guide walks you through installation, creating your first notebook, and exploring marimo's core features.
## Installation
Install marimo using pip or conda:
```bash pip theme={null}
pip install marimo
```
```bash conda theme={null}
conda install -c conda-forge marimo
```
```bash recommended theme={null}
# Install with recommended optional dependencies
pip install "marimo[recommended]"
```
The `recommended` extras include SQL support, AI completion, formatting tools, and more features that enhance your experience.
## Your first notebook
The fastest way to learn marimo is through the built-in tutorial:
```bash theme={null}
marimo tutorial intro
```
This launches an interactive notebook that teaches you marimo's core concepts.
Start a new notebook with the `edit` command:
```bash theme={null}
marimo edit
```
This opens marimo in your browser with an empty notebook.
Click the "+ Code" button to add a cell, then write some Python:
```python theme={null}
import marimo as mo
slider = mo.ui.slider(1, 100, value=50)
slider
```
When you run this cell (Ctrl+Enter or Cmd+Enter), you'll see an interactive slider.
Add another cell that uses the slider value:
```python theme={null}
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 2 * np.pi, slider.value)
y = np.sin(x)
plt.plot(x, y)
plt.title(f"Sine wave with {slider.value} points")
plt.gcf()
```
Move the slider and watch the plot update automatically - that's reactivity!
Save your notebook with Ctrl+S (or Cmd+S). You'll be prompted for a filename. marimo saves it as a `.py` file:
```bash theme={null}
# Your notebook is now saved as a Python file
marimo edit my_notebook.py
```
## Core workflows
### Creating notebooks
Create or edit notebooks with the `edit` command:
```bash theme={null}
# Start a new notebook
marimo edit
# Edit an existing notebook
marimo edit notebook.py
# Edit with a specific port
marimo edit notebook.py --port 3000
```
### Running as apps
Deploy your notebook as a web app where code is hidden and non-editable:
```bash theme={null}
marimo run notebook.py
```
This is perfect for:
* Sharing interactive dashboards with colleagues
* Creating internal tools
* Publishing data stories
* Building demos and prototypes
In app mode, users can interact with UI elements but cannot edit the code. The notebook remains fully reactive.
### Executing as scripts
Run notebooks as command-line scripts:
```bash theme={null}
python notebook.py
```
You can pass arguments:
```python theme={null}
import marimo as mo
# Access CLI arguments in your notebook
args = mo.cli_args()
print(args)
```
```bash theme={null}
python notebook.py --arg1 value1 --arg2 value2
```
### Exploring tutorials
marimo includes several built-in tutorials:
```bash theme={null}
# List all available tutorials
marimo tutorial --help
# Run specific tutorials
marimo tutorial intro # Introduction to marimo
marimo tutorial dataflow # How reactivity works
marimo tutorial ui # Interactive UI elements
marimo tutorial plots # Data visualization
marimo tutorial sql # SQL cells
marimo tutorial markdown # Dynamic markdown
```
## Essential features
### Interactive UI elements
marimo provides 40+ UI components that automatically trigger cell re-execution:
```python Slider theme={null}
import marimo as mo
slider = mo.ui.slider(1, 100, value=50, label="Sample size")
slider
```
```python Dropdown theme={null}
import marimo as mo
dropdown = mo.ui.dropdown(
options=["linear", "polynomial", "exponential"],
value="linear",
label="Model type"
)
dropdown
```
```python Table theme={null}
import marimo as mo
import pandas as pd
df = pd.DataFrame({
"name": ["Alice", "Bob", "Charlie"],
"age": [25, 30, 35]
})
table = mo.ui.table(df)
table
```
Access values with `.value`:
```python theme={null}
mo.md(f"Selected {slider.value} samples using {dropdown.value} model")
```
### Dynamic markdown
Create markdown that updates with your data:
```python theme={null}
import marimo as mo
name = "marimo"
count = 42
mo.md(f"""
# Welcome to {name}!
You have processed **{count}** records.
{"🎉" * min(count, 10)}
""")
```
### SQL cells
Query data with native SQL support:
```python theme={null}
import marimo as mo
import pandas as pd
df = pd.DataFrame({"x": [1, 2, 3], "y": [4, 5, 6]})
```
```sql theme={null}
SELECT * FROM df WHERE x > 1
```
The SQL cell creates a dataframe you can use in Python cells.
### Layouts
Organize outputs with flexible layouts:
```python Horizontal stack theme={null}
import marimo as mo
mo.hstack([plot1, plot2, plot3])
```
```python Vertical stack theme={null}
import marimo as mo
mo.vstack([header, content, footer])
```
```python Tabs theme={null}
import marimo as mo
mo.ui.tabs({
"Data": data_table,
"Visualization": chart,
"Analysis": results
})
```
## Converting from Jupyter
Convert existing Jupyter notebooks to marimo:
```bash theme={null}
# Convert to marimo format
marimo convert notebook.ipynb > notebook.py
# Edit the converted notebook
marimo edit notebook.py
```
Automatic conversion works well for simple notebooks, but you may need to refactor cells that have hidden state or out-of-order execution dependencies.
## Next steps
Learn about reactivity, cells, and the marimo execution model
Explore advanced installation options and optional dependencies
## Getting help
* Browse the [examples gallery](https://marimo.io/gallery) for inspiration
* Join the [Discord community](https://marimo.io/discord) for support
* Check the [FAQ](https://docs.marimo.io/faq.html) for common questions
* Watch [YouTube tutorials](https://www.youtube.com/@marimo-team) for video guides