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datasette-files S3 backend

Project description

datasette-files-s3

PyPI Changelog Tests License

S3 storage backend for datasette-files.

Installation

Install this plugin in the same environment as Datasette.

datasette install datasette-files-s3

Usage

Configure a datasette-files source to use S3 storage by setting "storage": "s3" and providing the required configuration options:

plugins:
  datasette-files:
    sources:
      my-s3-files:
        storage: s3
        config:
          bucket: my-bucket-name
          region: us-east-1
          access_key_id: AKIAIOSFODNN7EXAMPLE
          secret_access_key: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

Or using Datasette's -s flag:

datasette data.db \
    -s plugins.datasette-files.sources.my-s3-files.storage s3 \
    -s plugins.datasette-files.sources.my-s3-files.config.bucket my-bucket-name \
    -s plugins.datasette-files.sources.my-s3-files.config.region us-east-1

You can also use a credentials broker that returns temporary AWS credentials plus the S3 folder to use:

plugins:
  datasette-files:
    sources:
      my-s3-files:
        storage: s3
        config:
          credentials_url: https://example.com/api/s3-credentials
          credentials_url_secret: shared-secret
          region: us-east-1

Credentials Broker Response

When credentials_url is configured, the plugin sends a POST request with secret=... as form-encoded data and expects a JSON response shaped like this:

{
  "AccessKeyId": "ASIAWXFXAIOZGGVU5O6Y",
  "SecretAccessKey": "...",
  "SessionToken": "...",
  "Expiration": "2026-03-20T11:56:23Z",
  "S3Folder": "s3://datasettecloud-dev-files/team-1/"
}

Configuration options

  • bucket (required unless credentials_url is used): The name of the S3 bucket.
  • region (optional, default us-east-1): The AWS region.
  • prefix (optional): A prefix to add to all S3 object keys. This allows you to store files under a specific path within the bucket. A trailing slash will be added automatically if not provided - "uploads" and "uploads/" are equivalent.
  • endpoint_url (optional): A custom S3 endpoint URL, for use with S3-compatible services.
  • access_key_id (optional): AWS access key ID.
  • secret_access_key (optional): AWS secret access key.
  • session_token (optional): AWS session token, for temporary credentials supplied directly in config.
  • credentials_url (optional): URL to POST to for temporary credentials. The plugin sends secret=... as form-encoded data and expects a JSON response containing AccessKeyId, SecretAccessKey, SessionToken, Expiration, and S3Folder.
  • credentials_url_secret (required with credentials_url): Shared secret sent to the credentials endpoint as the form field secret.

Authentication

The plugin resolves AWS credentials using the following priority:

  1. Credentials broker: If credentials_url is configured, the plugin fetches temporary credentials by POSTing secret=... to that URL. It stores the returned AccessKeyId, SecretAccessKey, SessionToken, Expiration, and S3Folder, and automatically fetches a fresh set after the expiration time passes. The returned S3Folder also sets the active bucket and prefix for the source.
  2. Direct configuration: access_key_id, secret_access_key, and optional session_token in the config block.
  3. Default AWS credential chain: If no credentials are provided through the above methods, the plugin falls back to the default AWS credential chain (environment variables, IAM roles, etc.).

Prefix

The prefix option lets you scope all files to a specific path within the bucket. For example, with prefix: "uploads/", a file uploaded as photo.jpg will be stored at the S3 key uploads/photo.jpg.

It does not matter whether you include a trailing slash or not - "uploads" and "uploads/" will both result in files stored under uploads/.

When using credentials_url, the returned S3Folder behaves like a dynamically supplied bucket + prefix. For example, s3://datasettecloud-dev-files/team-1/ means the plugin will use bucket datasettecloud-dev-files and prefix team-1/.

Development

To set up this plugin locally, first checkout the code.

cd datasette-files-s3

Run tests like this:

uv run pytest

You can use SeaweedFS to run a local development server against a local imitation of the S3 API:

brew install seaweedfs
./dev-server.sh

To run a local development server against a real S3 bucket, create a dev-s3.sh script (this file is in .gitignore):

#!/bin/bash
set -e

BUCKET="your-bucket-name"
REGION="us-east-1"
ACCESS_KEY="your-access-key-id"
SECRET_KEY="your-secret-access-key"

uv run datasette data.db --create --internal internal.db --root --secret 1 --reload \
    -s plugins.datasette-files.sources.s3-live.storage s3 \
    -s plugins.datasette-files.sources.s3-live.config.bucket "$BUCKET" \
    -s plugins.datasette-files.sources.s3-live.config.region "$REGION" \
    -s plugins.datasette-files.sources.s3-live.config.access_key_id "$ACCESS_KEY" \
    -s plugins.datasette-files.sources.s3-live.config.secret_access_key "$SECRET_KEY" \
    -s plugins.datasette-files.sources.s3-live.config.prefix "demo-prefix/" \
    -s permissions.files-browse true \
    -s permissions.files-upload true \
    -s permissions.files-edit true

Then run it with bash dev-s3.sh and follow the login token URL printed to the console.

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