datasette-graphql 0.4

A GraphQL endpoint for Datasette

datasette-graphql

A GraphQL endpoint for Datasette

Try out a live demo at datasette-graphql-demo.datasette.io/graphql.

Installation

Install this plugin in the same environment as Datasette.

$ pip install datasette-graphql

Usage

This plugin sets up /graphql as a GraphQL endpoint for the first attached database.

If you have multiple attached databases each will get its own endpoint at /graphql/name_of_database.

Querying for tables and columns

Individual tables (and SQL views) can be queried like this:

{
  repos {
    nodes {
      id
      full_name
      description
    }
  }
}

In this example query the underlying database table is called repos and its columns include id, full_name and description.

Accessing nested objects

If a column is a foreign key to another table, you can request columns from the table pointed to by that foreign key using a nested query like this:

{
  repos {
    nodes {
      id
      full_name
      owner {
        id
        login
      }
    }
  }
}

Filtering tables

You can filter the rows returned for a specific table using the filters: argument. This accepts a list of filters, where a filter is a string of the form column=value or column__op=value. For example, to return just repositories with the Apache 2 license and more than 10 stars:

{
  repos(filters: ["license=apache-2.0", "stargazers_count__gt=10"]) {
    nodes {
      full_name
      stargazers_count
      license {
        key
      }
    }
  }
}

This is the same format used for querystring arguments to the Datasette table view, see column filter arguments in the Datasette documentation.

Sorting

You can set a sort order for results from a table using the sort: or sort_desc: arguments. The value for this argument should be the name of the column you wish to sort (or sort-descending) by.

{
  repos(sort_desc: stargazers_count) {
    nodes {
      full_name
      stargazers_count
    }
  }
}

Pagination

By default the first 10 rows will be returned. You can control this using the first: argument.

{
  repos(first: 20) {
    totalCount
    pageInfo {
      hasNextPage
      endCursor
    }
    nodes {
      full_name
      stargazers_count
      license {
        key
      }
    }
  }
}

The totalCount field returns the total number of records that match the query.

Requesting the pageInfo.endCursor field provides you with the value you need to request the next page. You can pass this to the after: argument to request the next page.

{
  repos(first: 20, after: "134874019") {
    totalCount
    pageInfo {
      hasNextPage
      endCursor
    }
    nodes {
      full_name
      stargazers_count
      license {
        key
      }
    }
  }
}

The hasNextPage field tells you if there are any more records.

Search

If a table has been configured to use SQLite full-text search you can execute searches against it using the search: argument:

{
  repos(search: "datasette") {
    totalCount
    pageInfo {
      hasNextPage
      endCursor
    }
    nodes {
      full_name
      description
    }
  }
}

The sqlite-utils Python library and CLI tool can be used to add full-text search to an existing database table.

Auto camelCase

The names of your columns and tables default to being matched by their representations in GraphQL.

If you have tables with names_like_this you may want to work with them in GraphQL using namesLikeThis, for consistency with GraphQL and JavaScript conventions.

You can turn on automatic camelCase using the "auto_camelcase" plugin configuration setting in metadata.json, like this:

{
    "plugins": {
        "datasette-graphql": {
            "auto_camelcase": true
        }
    }
}

Still to come

See issues for a full list. Planned improvements include:

• Canned query support
• Ability to allowlist specific tables, views and canned queries

Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

cd datasette-graphql
python3 -mvenv venv
source venv/bin/activate

Or if you are using pipenv:

pipenv shell

Now install the dependencies and tests:

pip install -e '.[test]'

To run the tests:

pytest