Writing Datasette Plugins

Writing Datasette Plugins

Use this skill to build plugins for Datasette, the open source multi-tool for exploring and publishing data.

Quick Start with Cookiecutter Template

Start a new plugin using the datasette-plugin cookiecutter template with newline-delimited variables:

echo "plugin_name
description of plugin
plugin-hyphenated-name
plugin_underscored_name
github_username
Author Name
y
y" | uvx cookiecutter gh:simonw/​datasette-plugin

Example for a plugin called "my-cool-plugin":

echo "my cool plugin
A plugin that does cool things
my-cool-plugin
my_cool_plugin
username
Your Name
y
y" | uvx cookiecutter gh:simonw/​datasette-plugin

The last two y responses enable static/ and templates/ directories.

After creating the plugin:

cd datasette-my-cool-plugin
python -m venv venv
source venv/​bin/​activate
pip install -e '.[test]'
datasette plugins  # Verify plugin is visible
python -m pytest   # Run tests

Plugin Structure

A typical plugin structure:

datasette-my-plugin/
├── datasette_my_plugin/
│   ├── __init__.py        # Plugin hooks go here
│   ├── static/            # Optional: CSS, JavaScript
│   └── templates/         # Optional: Custom templates
├── tests/
│   └── test_my_plugin.py
├── setup.py or pyproject.toml
└── README.md

Essential Plugin Hooks

prepare_connection(conn, database, datasette)

Register custom SQL functions. Called when SQLite connections are created:

from datasette import hookimpl

@hookimpl
def prepare_connection(conn):
    conn.create_function("hello_world", 0, lambda: "Hello world!")

register_routes(datasette)

Add custom URL routes. Return list of (regex, view_function) pairs:

from datasette import hookimpl, Response

async def my_page(request):
    return Response.html("<h1>Hello!</​h1>")

@hookimpl
def register_routes():
    return [
        (r"^/​-/​my-page$", my_page)
    ]

View functions can accept: datasette, request, scope, send, receive.

render_cell(row, value, column, table, database, datasette, request)

Customize how table cell values are displayed:

from datasette import hookimpl
import markupsafe

@hookimpl
def render_cell(value, column):
    if column == "stars":
        return markupsafe.Markup("⭐" * int(value))

extra_template_vars(template, database, table, columns, view_name, request, datasette)

Add variables to template context:

@hookimpl
def extra_template_vars(request, datasette):
    return {
        "user_agent": request.headers.get("user-agent"),
        "custom_data": "value"
    }

Can also return async functions for database queries.

table_actions(datasette, actor, database, table, request)

Add menu items to table pages:

@hookimpl
def table_actions(datasette, database, table):
    return [{
        "href": datasette.urls.path(f"/​-/​export/​{database}/​{table}"),
        "label": "Export this table",
        "description": "Download as CSV"
    }]

actor_from_request(datasette, request)

Implement authentication. Return actor dict or None:

@hookimpl
def actor_from_request(request):
    token = request.args.get("_token")
    if token == "secret":
        return {"id": "user123", "name": "Alice"}

Can return async function for database lookups.

permission_allowed(datasette, actor, action, resource)

Control permissions. Return True (allow), False (deny), or None (no opinion):

@hookimpl
def permission_allowed(actor, action, resource):
    if action == "execute-sql" and actor and actor.get("id") == "admin":
        return True

Request and Response Objects

Request Object

Available in many plugin hooks:

request.method          # "GET" or "POST"
request.url             # Full URL
request.path            # Path without query string
request.full_path       # Path with query string
request.query_string    # Query string without ?
request.args            # MultiParams object for query params
request.args.get("key") # Get single param value
request.args.getlist("key")  # Get list of values
request.headers         # Dict of headers (lowercase keys)
request.cookies         # Dict of cookies
request.actor           # Current authenticated actor or None
request.url_vars        # Variables from URL regex

# Async methods:
body = await request.post_body()      # Raw POST body as bytes
form_vars = await request.post_vars() # Form data as dict

Response Object

Create responses in view functions:

from datasette.utils.asgi import Response

# HTML response
return Response.html("<h1>Hello</​h1>")

# JSON response
return Response.json({"status": "ok"})

# Text response
return Response.text("Plain text")

# Redirect
return Response.redirect("/​other-page")

# Custom response
return Response(
    body="Content",
    status=200,
    headers={"X-Custom": "value"},
    content_type="text/​plain"
)

# Set cookies
response = Response.html("<h1>Hello</​h1>")
response.set_cookie("session", datasette.sign({"id": "123"}, "cookie"))

Database API

Access databases in plugins:

# Get database object
db = datasette.get_database("mydb")  # Named database
db = datasette.get_database()        # First database

# Execute read query
results = await db.execute("SELECT * FROM mytable WHERE id = ?", [123])
for row in results:
    print(row["column_name"])

# Query properties
results.rows         # List of Row objects
results.columns      # List of column names
results.truncated    # True if results were truncated
results.first()      # First row or None
results.single_value()  # Single value if query returned one

# Execute write query
await db.execute_write(
    "INSERT INTO mytable (name) VALUES (?)",
    ["value"]
)

# Execute multiple writes
await db.execute_write_many(
    "INSERT INTO mytable (id, name) VALUES (?, ?)",
    [(1, "Alice"), (2, "Bob")]
)

# Execute function with write connection
def insert_and_count(conn):
    conn.execute("INSERT INTO mytable (name) VALUES (?)", ["Alice"])
    return conn.execute("SELECT COUNT(*) FROM mytable").fetchone()[0]

count = await db.execute_write_fn(insert_and_count)

# Introspection
tables = await db.table_names()
views = await db.view_names()
columns = await db.table_columns("mytable")
exists = await db.table_exists("mytable")

Plugin Configuration

Users configure plugins in datasette.yaml:

plugins:
  datasette-my-plugin:
    api_key: secret123
    enabled: true

Or per-database:

databases:
  mydb:
    plugins:
      datasette-my-plugin:
        setting: value

Access in plugin code:

config = datasette.plugin_config("datasette-my-plugin")
api_key = config.get("api_key") if config else None

# With database/​table context
config = datasette.plugin_config(
    "datasette-my-plugin",
    database="mydb",
    table="mytable"
)

Configuration lookup: table → database → instance level.

Static Assets and Templates

Static Files

Place in static/ directory, reference with:

# In Python
url = datasette.urls.static_plugins("datasette_my_plugin", "app.js")

# In templates
<script src="{{ urls.static_plugins('datasette_my_plugin', 'app.js') }}"></​script>

Templates

Place in templates/ directory. Override Datasette templates:

• database.html - Database page
• table.html - Table page
• row.html - Row page
• query.html - Query page

Access template functions:

{{ csrftoken() }}                    {# CSRF token for forms #}
{{ urls.instance() }}                {# Homepage URL #}
{{ urls.database("mydb") }}          {# Database URL #}
{{ urls.table("mydb", "mytable") }}  {# Table URL #}

Common Patterns

Add a custom SQL function

@hookimpl
def prepare_connection(conn):
    import hashlib
    def md5(text):
        return hashlib.md5(text.encode()).hexdigest()
    conn.create_function("md5", 1, md5)

Add a custom page

@hookimpl
def register_routes(datasette):
    async def stats_page(request):
        db = datasette.get_database()
        tables = await db.table_names()
        return Response.html(
            await datasette.render_template(
                "stats.html",
                {"tables": tables},
                request=request
            )
        )

    return [(r"^/​-/​stats$", stats_page)]

Render custom output format

@hookimpl
def register_output_renderer(datasette):
    def render_csv(columns, rows):
        import csv, io
        output = io.StringIO()
        writer = csv.writer(output)
        writer.writerow(columns)
        writer.writerows(rows)
        return Response(
            output.getvalue(),
            content_type="text/​csv"
        )

    return {
        "extension": "csv",
        "render": render_csv
    }

Check permissions

@hookimpl
def register_routes(datasette):
    async def admin_page(request):
        # Check if user has permission
        allowed = await datasette.permission_allowed(
            request.actor,
            "admin-page",
            default=False
        )
        if not allowed:
            from datasette import Forbidden
            raise Forbidden("Admin access required")

        return Response.html("<h1>Admin Page</​h1>")

    return [(r"^/​-/​admin$", admin_page)]

URL Design

Use /​-/ prefix to avoid conflicts with database names:

• /​-/​my-plugin - Instance-level page
• /​dbname/​-/​my-plugin - Database-level page
• /​dbname/​table/​-/​my-plugin - Table-level page

Build URLs with base_url support:

datasette.urls.path("/​-/​my-page")
datasette.urls.database("mydb")
datasette.urls.table("mydb", "mytable")

Testing Plugins

Create tests in tests/​test_my_plugin.py:

from datasette.app import Datasette
import pytest

@pytest.mark.asyncio
async def test_my_plugin():
    datasette = Datasette()
    await datasette.invoke_startup()

    # Test with client
    response = await datasette.client.get("/​-/​my-page")
    assert response.status_code == 200

    # Test database operations
    db = datasette.get_database()
    result = await db.execute("SELECT hello_world()")
    assert result.first()[0] == "Hello world!"

Run tests: pytest

Publishing

To GitHub

git init
git add .
git commit -m "Initial commit"
git branch -m main
git remote add origin [email protected]:username/​datasette-my-plugin.git
git push -u origin main

To PyPI

Configure GitHub release environment with PyPI trusted publisher, then create a GitHub release matching your version number. The GitHub Action will automatically publish to PyPI.

Key Resources

• Plugin hooks reference: https://docs.datasette.io/en/stable/plugin_hooks.html
• Internals documentation: https://docs.datasette.io/en/stable/internals.html
• Example plugins: https://datasette.io/plugins
• Cookiecutter template: https://github.com/simonw/datasette-plugin

Important Notes

• Accept only the parameters you need in hook functions (dependency injection)
• Use @hookimpl decorator for all plugin hooks
• Async functions need async def and await
• CSRF tokens required for POST forms: <input type="hidden" name="csrftoken" value="{{ csrftoken() }}">
• Plugin package name uses underscores, pip name uses hyphens
• Use - prefix in URLs: /​-/​plugin-path
• Access internal database with datasette.get_internal_database()