sql

SQL 🛢️

These examples show how to use marimo's built-in support for SQL, which is powered by duckdb, a fast in-process analytical database.

querying_dataframes.py shows hows to query Pandas or Polars dataframes
paremetrizing_sql_queries.py shows hows to parametrize queries with Python values
read_csv.py shows hows to read CSV data into duckdb
read_json.py shows hows to read JSON data into duckdb
read_parquet.py shows hows to read parquet data into duckdb
connect_to_persistent_db.py shows hows to connect to a duckdb persistent database
connect_to_sqlite.py shows hows to connect to a SQLite database
connect_to_postgres.py shows hows to connect to a PostgreSQL database
connect_to_motherduck.py shows hows to connect to motherduck
histograms.py shows hows to plot histograms of a column's values
misc/ contains illustrative examples

Tip

For a broad overview of using SQL in marimo, run marimo tutorial sql at the command-line.

Consult the duckdb documentation for a comprehensive guide on duckdb.

The requirements of each notebook are serialized in them as a top-level comment. Here are the steps to open an example notebook:

Tip

The --sandbox flag opens the notebook in an isolated virtual environment, automatically installing the notebook's dependencies 📦

You can also open notebooks without uv, with just marimo edit <notebook.py>; however, you'll need to install the requirements yourself.

Name	Name	Last commit message	Last commit date
parent directory ..
misc	misc
README.md	README.md
connect_to_motherduck.py	connect_to_motherduck.py
connect_to_persistent_db.py	connect_to_persistent_db.py
connect_to_postgres.py	connect_to_postgres.py
connect_to_sqlite.py	connect_to_sqlite.py
histograms.py	histograms.py
parametrizing_sql_queries.py	parametrizing_sql_queries.py
querying_dataframes.py	querying_dataframes.py
read_csv.py	read_csv.py
read_json.py	read_json.py
read_parquet.py	read_parquet.py