### Complete Marimo App Example

Source: https://docs.marimo.io/guides/editor_features/watching?q=

A full example demonstrating setup, top-level functions, classes, and running the Marimo app.

```python
import marimo

app = marimo.App()

with app.setup:
    import numpy as np

    CONSTANT: int = 1

@app.function
def my_function(x: np.ndarray):
    return np.mean(x) + CONSTANT

@app.class_definition
class MyClass:
    ...

@app.cell
def _():
    my_function(np.random.randn(2, 2))
    return

if __name__ == "__main__":
    app.run()

```

--------------------------------

### Correct Setup Cell Initialization

Source: https://docs.marimo.io/guides/lint_rules/rules/setup_cell_dependencies

This example demonstrates a correctly structured setup cell that initializes its own variables. Other cells can then safely use variables defined in the setup cell.

```python
# Setup cell
y = 1  # Setup defines its own variables

# Cell 1
x = y + 1  # Other cells can use setup variables
```

--------------------------------

### Create Sandbox Notebook and Add Local Library

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects?q=

Create a sandbox notebook within your library project and add the library itself as an editable dependency. This setup is for creating example notebooks that use your library.

```bash
# Create a sandbox notebook
mkdir examples
uv run marimo edit --sandbox examples/quickstart.py

# Add your library as editable dependency
uv add --script examples/quickstart.py . --editable

```

--------------------------------

### Create venv and install packages with uv

Source: https://docs.marimo.io/guides/package_management/using_uv

Use `uv venv` to create a virtual environment and `uv pip` to install packages like numpy and marimo. Then, use `uv run marimo edit` to start the marimo editor.

```console
$ uv venv
$ uv pip install numpy
$ uv pip install marimo
$ uv run marimo edit
```

--------------------------------

### Start Marimo in Sandbox Mode

Source: https://docs.marimo.io/guides/package_management/importing_packages?q=

Use the `--sandbox` flag to create an isolated, per-notebook virtual environment. Dependencies installed via the editor will be inlined into the notebook file.

```bash
marimo edit --sandbox my_notebook.py
```

--------------------------------

### Install uv and start marimo in a SkyPilot cluster

Source: https://docs.marimo.io/guides/deploying/deploying_skypilot?q=

Inside the cluster, install uv and then run marimo using uvx with the --sandbox flag for isolated dependencies. Access your notebook via localhost:8080.

```bash
pip install uv
uvx marimo edit --sandbox demo.py --port 8080 --token-password=supersecret
```

--------------------------------

### Install marimo with uv

Source: https://docs.marimo.io/?q=

Installs marimo using uv, a fast Python package installer, and then runs the tutorial introduction. Recommended for faster dependency management.

```bash
uv add marimo && uv run marimo tutorial intro

```

--------------------------------

### Start Marimo Notebook Server

Source: https://docs.marimo.io/cli

Launches the Marimo notebook server. This command can be used without any arguments to start the server.

```text
marimo edit
```

--------------------------------

### Install marimo with SQL support using uv

Source: https://docs.marimo.io/integrations/motherduck?q=

Install the marimo package with SQL capabilities using uv. This is an alternative to pip for package installation.

```bash
uv add "marimo[sql]"
```

--------------------------------

### Install kubectl-marimo plugin

Source: https://docs.marimo.io/guides/deploying/deploying_kubernetes?q=

Install the kubectl-marimo CLI plugin using uv (recommended) or pip.

```bash
# With uv (recommended)
uv tool install kubectl-marimo

# Or with pip
pip install kubectl-marimo
```

--------------------------------

### Populate Marimo Form with Pre-defined Examples

Source: https://docs.marimo.io/recipes?q=

Pre-populate a form with example data for illustration or to showcase complex inputs. Use `mo.ui.dropdown` to select examples and `mo.md.batch` to map example values to form fields. The form can also be populated from URL query parameters.

```python
import marimo as mo

```

```python
examples = mo.ui.dropdown(
    options={
        "ex 1": {"t1": "hello", "t2": "world"},
        "ex 2": {"t1": "marimo", "t2": "notebook"},
    },
    value="ex 1",
    label="examples",
)


```

```python
form = (
    mo.md(
        """
    ### Your form

    {t1}
    {t2}
"""
    )
    .batch(
        t1=mo.ui.text(label="enter text", value=examples.value.get("t1", "")),
        t2=mo.ui.text(label="more text", value=examples.value.get("t2", "")),
    )
    .form(
        submit_button_label="go"
    )
)


```

```python
output = (
    " ".join(form.value.values()).upper()
    if form.value is not None
    else " ".join(examples.value.values()).upper()
)
examples, form, output

```

--------------------------------

### Run Full BigQuery Example

Source: https://docs.marimo.io/integrations/google_cloud_bigquery?q=

Execute a full example of using Google Cloud BigQuery with Marimo by running a Python script from a URL.

```bash
marimo run https://raw.githubusercontent.com/marimo-team/marimo/main/examples/cloud/gcp/google_cloud_bigquery.py

```

--------------------------------

### Example Snapshot Filename

Source: https://docs.marimo.io/guides/exporting/sessions?q=

An example of the generated snapshot filename for a notebook named 'notebook.py'.

```bash
__marimo__/session/notebook.py.json
```

--------------------------------

### Install marimo with pip

Source: https://docs.marimo.io/?q=

Installs marimo using pip and launches the tutorial introduction. Use this method for standard Python environments.

```bash
pip install marimo && marimo tutorial intro

```

--------------------------------

### Run Full BigQuery Example

Source: https://docs.marimo.io/integrations/google_cloud_bigquery

Execute a complete marimo example that utilizes Google Cloud BigQuery by running a command in your terminal.

```bash
marimo run https://raw.githubusercontent.com/marimo-team/marimo/main/examples/cloud/gcp/google_cloud_bigquery.py
```

--------------------------------

### Open the Intro Tutorial

Source: https://docs.marimo.io/cli?q=

Use this command to open the introductory tutorial for marimo.

```bash
marimo tutorial intro

```

--------------------------------

### Open Intro Tutorial

Source: https://docs.marimo.io/cli

Use this command to open the introductory marimo tutorial.

```text
marimo tutorial intro
```

--------------------------------

### Install pylsp

Source: https://docs.marimo.io/guides/editor_features/language_server

Install the core Python language server and Ruff integration for Marimo. This provides completions, hover, go-to-definition, and diagnostics.

```bash
pip install "marimo[lsp]"
```

```bash
uv add "marimo[lsp]"
```

```bash
conda install -c conda-forge python-lsp-server python-lsp-ruff
```

--------------------------------

### Create Sandbox Example Notebook and Add Library

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects

Commands to create a sandbox notebook within an example directory and add the local library as an editable dependency.

```bash
# Create a sandbox notebook
mkdir examples
uv run marimo edit --sandbox examples/quickstart.py

# Add your library as editable dependency
uv add --script examples/quickstart.py . --editable
```

--------------------------------

### Problematic Setup Cell Dependency

Source: https://docs.marimo.io/guides/lint_rules/rules/setup_cell_dependencies

This example shows a setup cell that incorrectly depends on a variable 'x' defined in another cell. Setup cells must be self-contained or only depend on variables defined within themselves.

```python
# Setup cell
y = x + 1  # Error: setup depends on other cells

# Cell 1
x = 1
```

--------------------------------

### Check marimo installation with uv

Source: https://docs.marimo.io/getting_started/installation

Run this command after installation with uv to verify marimo is working correctly. A tutorial notebook should open in your browser.

```bash
uv run marimo tutorial intro
```

--------------------------------

### Initialize Library Project and Add Marimo

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects?q=

Set up a new library project using `uv init --lib` and add Marimo as a development dependency. This is the first step for creating example sandbox notebooks for your library.

```bash
# Initialize the project
uv init --lib my-library && cd my-library

# Add marimo as development dependency
uv add --dev marimo

```

--------------------------------

### start property

Source: https://docs.marimo.io/api/inputs/dates?q=

Gets the minimum selectable datetime for the datetime picker.

```APIDOC
## start property

### Description
Get the minimum selectable datetime.

### Returns
- **datetime** - The start datetime, which is either the user-specified minimum datetime or datetime.min if no start datetime was specified.
```

--------------------------------

### Run Google Sheets Example

Source: https://docs.marimo.io/integrations/google_sheets

Run a full example of using Google Sheets with marimo by executing a Python script from a URL.

```bash
marimo run https://raw.githubusercontent.com/marimo-team/marimo/main/examples/cloud/gcp/google_sheets.py
```

--------------------------------

### Initialize Project and Add Dependencies

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects

Initialize a new project using uv and add marimo and other data science libraries as dependencies.

```bash
# Initialize project
uv init analysis-project && cd analysis-project

# Add marimo as a project dependency
uv add marimo pandas scikit-learn

# Edit notebooks using project environment
uv run marimo edit notebook.py
```

--------------------------------

### Run Google Sheets Example

Source: https://docs.marimo.io/integrations/google_sheets?q=

Execute a full example of using Google Sheets with Marimo by running a provided Python script URL.

```bash
marimo run https://raw.githubusercontent.com/marimo-team/marimo/main/examples/cloud/gcp/google_sheets.py

```

--------------------------------

### Initialize a uv Project

Source: https://docs.marimo.io/guides/package_management/using_uv?q=

Create a new uv project directory named 'hello-world'. This command sets up the project structure and a pyproject.toml file for dependency management.

```bash
uv init hello-world
cd hello-world

```

--------------------------------

### Get Minimum Selectable Datetime

Source: https://docs.marimo.io/api/inputs/dates

Retrieves the minimum selectable datetime from the datetime picker. This will be the user-specified start date or the earliest possible datetime if none was set.

```python
start: datetime
```

--------------------------------

### Run Marimo in Non-Project Environment

Source: https://docs.marimo.io/guides/package_management/using_uv?q=

Start the Marimo editor within a non-project environment where packages have been installed using 'uv pip'. This allows notebooks to import these packages.

```bash
$ uv run marimo edit

```

--------------------------------

### List Marimo Tutorials

Source: https://docs.marimo.io/getting_started/quickstart?q=

Use this command to list all available marimo tutorials.

```bash
marimo tutorial --help

```

--------------------------------

### Recommended Tutorial Sequence

Source: https://docs.marimo.io/cli?q=

Follow this sequence to learn marimo effectively, starting with the intro and progressing through advanced topics.

```bash
- intro
- dataflow
- ui
- markdown
- plots
- sql
- layout
- fileformat
- external-dependencies
- markdown-format
- for-jupyter-users

```

--------------------------------

### Run Marimo Layout Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts?q=

Open the layout tutorial to learn about Marimo's tools for organizing and arranging outputs, including stacks, accordions, and tabs.

```bash
marimo tutorial layout

```

--------------------------------

### Use marimo Prebuilt Container in Dockerfile

Source: https://docs.marimo.io/guides/deploying/prebuilt_containers

Integrate a marimo prebuilt container into your Dockerfile. This example uses the latest SQL variant and sets the default command to start the marimo server.

```dockerfile
FROM ghcr.io/marimo-team/marimo:latest-sql

# Install any additional dependencies here

CMD ["marimo", "edit", "--no-token", "-p", "8080", "--host", "0.0.0.0"]
```

--------------------------------

### Run Marimo Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts

Launch the dataflow tutorial to understand reactive execution and data flow within marimo notebooks. This command opens the tutorial in your default marimo environment.

```bash
marimo tutorial dataflow
```

--------------------------------

### Run Full Google Cloud Storage Example

Source: https://docs.marimo.io/integrations/google_cloud_storage

Execute the complete Google Cloud Storage example provided by marimo using the `marimo run` command.

```bash
marimo run https://raw.githubusercontent.com/marimo-team/marimo/main/examples/cloud/gcp/google_cloud_storage.py
```

--------------------------------

### Compatible Package Dependency (Pure Python Wheel)

Source: https://docs.marimo.io/guides/lint_rules/rules/incompatible_package

This example shows a package (requests) that is not flagged by the MW003 rule. It is compatible with WASM because it provides a pure Python wheel on PyPI, which can be installed via micropip.

```python
import requests  # Pure Python wheel on PyPI
```

--------------------------------

### Initialize Data Science Project and Add Marimo

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects?q=

Set up a new data science project using `uv init` and add Marimo along with common data science libraries as project dependencies. This is for projects where notebooks are integral to the analysis workflow.

```bash
# Initialize project
uv init analysis-project && cd analysis-project

# Add marimo as a project dependency
uv add marimo pandas scikit-learn

```

--------------------------------

### Running Marimo in Headless Mode on a Remote Server

Source: https://docs.marimo.io/faq

To run Marimo on a remote server, use the `--headless` flag and specify a port. This example shows how to start Marimo remotely and forward the port from your local machine.

```bash
marimo edit --headless --port 8080
```

```bash
marimo edit --headless --host 0.0.0.0 --port 8080
```

```text
ssh -N -L 3718:127.0.0.1:8080 REMOTE_USER@REMOTE_HOST
```

--------------------------------

### Run Full Google Cloud Storage Example

Source: https://docs.marimo.io/integrations/google_cloud_storage?q=

Execute a complete example demonstrating Google Cloud Storage integration with Marimo by running a provided Python script.

```bash
marimo run https://raw.githubusercontent.com/marimo-team/marimo/main/examples/cloud/gcp/google_cloud_storage.py

```

--------------------------------

### Sandbox Notebook PEP 723 Metadata Example

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects?q=

This header, automatically generated by `uv add --script`, defines the Python version and dependencies for a sandbox notebook. It also specifies the local path for editable installation of the package.

```toml
# /// script
# requires-python = ">=3.11"
# dependencies = [
#     "my-package",
#     "pandas",
#     "matplotlib",
# ]
#
# [tool.uv.sources]
# my-package = { path = "../", editable = true }
# ///
```

--------------------------------

### Get App Theme and Conditionally Set Plotting Theme

Source: https://docs.marimo.io/api/app?q=

Access the app's display theme using `mo.app_meta().theme`. This example shows how to conditionally enable a dark theme for Altair plots when Marimo is in dark mode.

```python
import altair as alt
import marimo as mo

# Enable dark theme for Altair when marimo is in dark mode
alt.themes.enable(
    "dark" if mo.app_meta().theme == "dark" else "default"
)
```

--------------------------------

### Open MotherDuck example notebook

Source: https://docs.marimo.io/integrations/motherduck?q=

Open the MotherDuck example notebook in marimo to see a full demonstration of its integration. This command launches the specified notebook for editing.

```bash
marimo edit https://github.com/marimo-team/marimo/blob/main/examples/sql/connect_to_motherduck.py
```

--------------------------------

### Access Request URL Path and User Authentication Status

Source: https://docs.marimo.io/api/app?q=

Get the current HTTP request object via `mo.app_meta().request` to access user details and the request URL path. This example prints authentication status, username, and the URL path.

```python
import marimo as mo

request = mo.app_meta().request
user = request.user
print(
    user["is_authenticated"], user["username"], request.url["path"]
)
```

--------------------------------

### Run Marimo Tutorials

Source: https://docs.marimo.io/getting_started/key_concepts

Use these commands to run specific Marimo tutorials from the command line.

```bash
marimo tutorial markdown
```

```bash
marimo tutorial plots
```

```bash
marimo tutorial layout
```

```bash
marimo tutorial ui
```

```bash
marimo tutorial sql
```

--------------------------------

### Run Marimo with MCP Support using uv

Source: https://docs.marimo.io/guides/editor_features/mcp?q=

Use uv to run Marimo with MCP support. This command installs the necessary dependencies and starts Marimo with the `--mcp` flag to expose the MCP server endpoint and `--no-token` for local development.

```bash
# run with uv in a project
uv run --with="marimo[mcp]" marimo edit notebook.py --mcp --no-token

```

--------------------------------

### Install marimo SQL dependencies

Source: https://docs.marimo.io/guides/working_with_data/sql?q=

Install the necessary dependencies to enable SQL functionality in marimo. Choose the installation method that suits your package manager.

```bash
pip install "marimo[sql]"

```

```bash
uv add "marimo[sql]"

```

```bash
conda install -c conda-forge marimo duckdb polars

```

--------------------------------

### List Marimo Tutorials

Source: https://docs.marimo.io/cli

Command to display available marimo tutorials.

```text
marimo tutorial --help
```

--------------------------------

### Run Marimo Tutorial

Source: https://docs.marimo.io/faq

Run Marimo tutorials to learn about specific features like plots or layout.

```bash
marimo tutorial plots
```

```bash
marimo tutorial layout
```

--------------------------------

### Install Packages with micropip

Source: https://docs.marimo.io/guides/wasm?q=

Use `micropip` to install packages within a WebAssembly environment. Ensure `micropip` is imported in a separate cell before installing other packages.

```python
import micropip

```

```python
await micropip.install("plotly")
import plotly

```

--------------------------------

### Install marimo pair with uvx

Source: https://docs.marimo.io/guides/generate_with_ai/marimo_pair

Install the marimo pair agent skill using uvx and Deno. This is an alternative installation method for the agent skill.

```bash
uvx deno -A npm:skills add marimo-team/marimo-pair
```

--------------------------------

### Run Marimo Markdown Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts?q=

Access the markdown tutorial to learn how to use Marimo's dynamic markdown features for rich text and content integration.

```bash
marimo tutorial markdown

```

--------------------------------

### Run Marimo UI Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts?q=

Execute this command in your terminal to launch the interactive UI tutorial for Marimo.

```bash
marimo tutorial ui

```

--------------------------------

### Install Marimo with Recommended Dependencies (uv)

Source: https://docs.marimo.io/getting_started/quickstart?q=

Installs marimo and its recommended optional dependencies using the uv package installer. This command is an alternative to using pip.

```bash
uv add "marimo[recommended]"

```

--------------------------------

### Run Marimo SQL Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts?q=

Execute this command in your terminal to launch the SQL tutorial for Marimo, covering data querying capabilities.

```bash
marimo tutorial sql

```

--------------------------------

### Marimo New with Prompt Example

Source: https://docs.marimo.io/cli?q=

Generate a Marimo notebook from a specific prompt. This example shows how to create a notebook that plots an interactive 3D surface.

```bash
marimo new "Plot an interactive 3D surface with matplotlib."
```

--------------------------------

### Install pylsp with Marimo

Source: https://docs.marimo.io/guides/editor_features/language_server?q=

Install the python-lsp-server package along with Marimo for core Python language server features. This command also installs Ruff integration for linting.

```bash
pip install "marimo[lsp]"
# or
uv add "marimo[lsp]"
# or
conda install -c conda-forge python-lsp-server python-lsp-ruff
```

--------------------------------

### Install or Update Marimo with uv

Source: https://docs.marimo.io/security?q=

Use `uv` to install or upgrade marimo to the latest version, ensuring you have the most recent security fixes and improvements. This command installs or updates marimo to its latest release.

```bash
# Install or update to the latest version
uv pip install --upgrade marimo

```

--------------------------------

### Run Marimo Plots Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts?q=

Launch the plots tutorial to explore how to generate and display various types of plots within your Marimo notebooks.

```bash
marimo tutorial plots

```

--------------------------------

### Run Polars Example Notebook

Source: https://docs.marimo.io/guides/working_with_data/dataframes?q=

Open the comprehensive Polars example notebook using the marimo edit command. This notebook demonstrates the integration of Polars with Marimo.

```bash
marimo edit https://raw.githubusercontent.com/marimo-team/marimo/main/examples/third_party/polars/polars_example.py

```

--------------------------------

### Install marimo-operator

Source: https://docs.marimo.io/guides/deploying/deploying_kubernetes?q=

Apply the installation manifest to deploy the marimo operator on your Kubernetes cluster.

```bash
kubectl apply -f https://raw.githubusercontent.com/marimo-team/marimo-operator/main/deploy/install.yaml
```

--------------------------------

### Install marimo with recommended dependencies using conda

Source: https://docs.marimo.io/getting_started/installation

Install marimo with recommended dependencies using conda. This command installs additional packages for features like SQL cells, AI completion, and enhanced plotting.

```bash
conda install -c conda-forge marimo "duckdb>=1.0.0" "altair>=5.4.0" pyarrow "polars>=1.9.0" "sqlglot[c]>=23.4" "openai>=1.55.3" "ruff" "nbformat>=5.7.0" "vegafusion>=2.0.0" "vl-convert-python>=1.0.0"
```

--------------------------------

### Initialize Storage Client and List Buckets

Source: https://docs.marimo.io/integrations/google_cloud_storage

Load necessary libraries and initialize a StorageClient to interact with Google Cloud Storage. This code lists all available buckets.

```python
# Cell 1 - Load libraries
import marimo as mo
from google.cloud import storage

# Cell 2 - Load buckets
client = storage.Client()
buckets = client.list_buckets()
```

--------------------------------

### Install pyrefly

Source: https://docs.marimo.io/guides/editor_features/language_server

Install pyrefly for completions, hover, go-to-definition, and diagnostics in Marimo. Requires Node.js.

```bash
uv pip install pyrefly
```

--------------------------------

### Run Marimo Dataflow Tutorial

Source: https://docs.marimo.io/getting_started/key_concepts?q=

Execute this command to launch the dataflow tutorial, which helps visualize and understand how data flows through your Marimo notebook.

```bash
marimo tutorial dataflow

```

--------------------------------

### Install ty

Source: https://docs.marimo.io/guides/editor_features/language_server

Install ty, a type checker from Astral, for diagnostics in Marimo. Requires Node.js.

```bash
uv pip install ty
```

--------------------------------

### Initialize Storage Client and List Buckets

Source: https://docs.marimo.io/integrations/google_cloud_storage?q=

Load necessary libraries and initialize a StorageClient to interact with Google Cloud Storage. This code lists all available buckets.

```python
# Cell 1 - Load libraries
import marimo as mo
from google.cloud import storage

# Cell 2 - Load buckets
client = storage.Client()
buckets = client.list_buckets()

```

--------------------------------

### Initialize Library Project and Add Marimo

Source: https://docs.marimo.io/guides/package_management/notebooks_in_projects

Steps to initialize a new Python library project using uv and add Marimo as a development dependency.

```bash
# Initialize the project
uv init --lib my-library && cd my-library

# Add marimo as development dependency
uv add --dev marimo
```

--------------------------------

### Text Area Example

Source: https://docs.marimo.io/api/inputs/text_area?q=

A minimal example demonstrating the instantiation of a text area UI element.

```python
text_area = mo.ui.text_area()

```

--------------------------------

### Install gspread and oauth2client

Source: https://docs.marimo.io/integrations/google_sheets?q=

Install the required Python packages for Google Sheets integration using pip.

```bash
pip install gspread oauth2client

```

--------------------------------

### Marimo Tutorial Command Usage

Source: https://docs.marimo.io/cli?q=

This shows the general usage pattern for the `marimo tutorial` command, including the required tutorial name and available options.

```bash
marimo tutorial [OPTIONS] {intro|dataflow|ui|markdown|plots|sql|layout|fileformat|external-dependencies|markdown-format|for-jupyter-users}

```

--------------------------------

### Run a Single Notebook as an App

Source: https://docs.marimo.io/guides/apps

Use the `marimo run` command to start a web server for a single notebook, displaying its outputs as an app. Code is hidden by default.

```text
marimo run notebook.py
```

--------------------------------

### Install Google Sheets Libraries

Source: https://docs.marimo.io/integrations/google_sheets

Install the required gspread and oauth2client Python packages using pip.

```bash
pip install gspread oauth2client
```

--------------------------------

### Install OpenAI Client

Source: https://docs.marimo.io/guides/configuration/llm_providers

Install the OpenAI client library for Python. This is a prerequisite for using most LLM providers.

```bash
pip install openai
```

```bash
uv add openai
```

--------------------------------

### Marimo Tutorial Command Usage

Source: https://docs.marimo.io/cli

This shows the general usage pattern for the `marimo tutorial` command, including the required tutorial name and available options.

```text
marimo tutorial [OPTIONS] {intro|dataflow|ui|markdown|plots|sql|layout|fileformat|external-dependencies|markdown-format|for-jupyter-users}
```

--------------------------------

### Install basedpyright

Source: https://docs.marimo.io/guides/editor_features/language_server

Install basedpyright for diagnostics (type checking errors and warnings) in Marimo. Requires Node.js.

```bash
uv pip install basedpyright
```

--------------------------------

### Install marimo with uv

Source: https://docs.marimo.io/getting_started/installation

Use this command to install marimo with uv. Ensure your virtual environment is activated.

```bash
uv add marimo
```

--------------------------------

### Marimo Convert Example (Markdown)

Source: https://docs.marimo.io/cli

Example of converting a Markdown file to a marimo notebook, saving to a file.

```text
marimo convert your_nb.md -o your_nb.py
```